8 ms·

DeepSeek-V4-Flash Update

745 points by dnhkng 2mo ago

Reubend 2mo ago
They're always very understated in their update descriptions. This is actually a HUGE improvement in the model's capabilities rather than just a small tweak.
dannyw 2mo ago
Deepseek and moonshot are the only two providers I consent to training for.
- applicative 2mo ago
  Xi going to shut down open-weighting of them in a matter of months. No one seriously doubts this. They will be too powerful and they will be gone.
  - darkwater 2mo ago
    What makes you state this?
    - baublet 2mo ago
      China bad
      - applicative 2mo ago
        I'm a) quoting Xi's speech and b) projecting rapid China development to Mythos level. Either you think China will never get to 'Mythos level' because you think China bad; or you think they will release the weights, because you think China bad. Its incredible the weight of ideology over facts in this discourse
        satvikpendem 2mo ago
        You haven't quoted anything actually. Provide sources to your claims.
    - riskd 2mo ago
      Decades of xenophobic propaganda
      - 1234letshaveatw 2mo ago
        Wow! Amazing observation! Wait, do you think there could have been any pro Chinese propaganda? Perhaps even some taking place at the present time? I think it could be possible?
        Zetaphor 2mo ago
        I'm sure there's plenty, but if you put on your rational hat and think about the motivations of the Chinese government you'll realize this claim makes no sense, and there's plenty of evidence and good reason saying the opposite
        1234letshaveatw 2mo ago
        you are probably right! nobody does more domestic discourse shaping than China, but good reason says none of that would take place externally
        riskd 2mo ago
        You’re clearly too far gone to even fathom the thought; so you grasp at these straws for hope that the China you grew up “learning” about is the same in reality.
      - applicative 2mo ago
        No, reading Xi's speech. They aren't going to give their Mythos - presumably a few months away - to the Sinaloa cartel or Uighur hackers or the US military or etc etc
        h8hawk 2mo ago
        They have already released their models (GLM 5.2 and K3). This is why Amodei and the rest of the effective altruist lobbies are trying to pressure the US government to both ban open-source models and pressure China to do the same. I’m curious to see why you’re so eager to ban open-source LLMs while being okay with Anthropic’s control. Do you think they’ll rebel against you?
  - gravypod 2mo ago
    What would the benefit of this be? If China stops open weights, US labs still have the intelligence frontier. Maybe once Chinese models have speed, cost, and intelligence beat but right now they don't. Undermining out entire economy by subsidizing the release of DIY versions of our main economic drive sounds like a huge win for China.
    - deleted 2mo ago
      [deleted]
    - applicative 2mo ago
      > Maybe once Chinese models have speed, cost, and intelligence beat but right now they don't. Yes this is why I referred to 'months' and was downvoted by people who can't distinguish their politics from reality. You are restating exactly the text you are criticizing. This is the nature of mechanical parrotlike repetition of propaganda: a) You can have 'frontier' models with closed weights. Your sentence is basically a contraction within itself, again, the weight of ideology. b) No one actually knows whether or not the closed weights of Bytedance are beyond all existing frontiers. Again the weight of ideology blinds you to the fact that the real 800 lb gorilla of Chinese Ai is more closed than Anthropic.
      - ricardobeat 2mo ago
        The latest ByteDance Seed model is behind Opus 4.6 in performance. It’s not even in the conversation atm. The parent made a totally coherent commment that China closing off their open weight models would cede the frontier (and majority of AI users worldwide) to the USA. Nothing you said counters that point.
        applicative 2mo ago
        Bytedance models completely pervade business use across China. It is the OpenAI of China, whether you think its a good model or not.
      - gravypod 2mo ago
  - anon373839 2mo ago
    Reuters was reporting that rumor. And then Xi made a public appearance at a conference in Shanghai where he said the opposite of that rumor.
    - applicative 2mo ago
      No in that very speech Xi stated explicitly what amounted to: 'of course when we get a Mythos, it will be a state secret'. In fact the overwhelming weight of AI use in China, the chatgpt so to say, is Bytedance's AI which is absolutely closed and uniquely opaque. The press treatment of these matters was no good and they are slowly walking it back, e.g. NYT yesterday finally actually read the speech.
      - anon373839 2mo ago
        Do you have a source for that? The NYT article does not quote Xi making that statement, and I can't find a source for that. In fact, Xi delivered veiled criticism of the security posturing the US has done: > We should put in place laws and regulations, technological monitoring, early warning and emergency response systems in order to strengthen the line of security, prevent abuses and malicious use, and ensure that AI is always under human control. In the meantime, we should jointly oppose overstretching the national security concept in the field of AI and placing one country’s security over that of others. There was a blog post by a state-linked broadcaster cited in the NYT piece: > “China supports openness, but this does not mean it advocates for the unconditional proliferation of all capabilities,” the blog said. The article also quoted an American journalist: > “If these models do reach those dangerous capabilities, they are not going to let it be a free-for-all in terms of releasing them," Mr. Sheehan said. But a distinction has to be drawn between real dangers (which many people believe LLMs have not actually shown, to date) versus "dangers" hyped up marketing purposes or domestic regulatory-capture motives. Presumably the Chinese government is less interested in the latter.
        applicative 2mo ago
        "Dangers" may indeed be hyped up for marketing purposes or domestic regulatory-capture motives. But as Xi stated, they will become real. It is just a question of being unaffected by the motives of the speakers, which is what adults learn to do.
  - ReptileMan 2mo ago
    It is true. And only Chinese Han people can continue work on what is already released. But they will be forbidden. /s Sarcasm aside - if the community can't get their shit together to continue improving what is currently public, well - we don't deserve free stuff and open weights.
  - 1234letshaveatw 2mo ago
    That isn't the Chinese way. They are much more focused on undermine and extinguish. Just look at the European car industry- on its way to being non-existent after the market was flooded, bye bye manufacturing base. Undercut the US AI providers and wait them out, they will go private after they have a stranglehold
    - applicative 2mo ago
      Even Xi's speech was as paranoid as Dario Amodei about the possibility of Chinese AI achieving something at the level of say Mythos. If you seriously believe such a thing will be on Hugging Face I really don't know what to say.
      - criley2 2mo ago
        There is already something on HuggingFace at the level of Mythos. It's called Kimi K3 and it's running laps around Opus5, Fable5, and Sol56 at cybersecurity. It's so good that the US government is rushing to ban all Chinese models as fast as they can.
        applicative 2mo ago
        Fine, you believe Anthropic was lying about Mythos. In fact no view of the matter is needed to formulate the proposition above. It is clear China will soon have a model with the powers imputed to Mythos but which you deny of actual Mythos. It is a trial to deal with this level of ideological blindness; 'ideology has no outside'. If someone says 'when they get Mythos...', declare the possibility of Mythos to be the real lie. But it is quite possible and will be coming in months.
        zozbot234 2mo ago
        Reading between the lines, it's fairly clear that Mythos Preview only got its reported results in offensive cyber thanks to a highly specialized harness and humongous amounts of test-time compute. We also don't know what kind of post-training/fine-tuning it got on cyber, Anthropic only stated that it wasn't specifically trained for cyber-offense but that leaves a lot of scope for training on other related things. Overall, the Mythos story is a lot less interesting than most people might like to claim - but note that this doesn't require any actual lying. The interest around K3 is a lot more defensible because we actually know what the architecture looks like, how much effort it takes to get it to run, and what kinds of results it gets on cyber evaluations. And no, it's nowhere near "dangerous" enough to where people might honestly want to ban it for real safety reasons. It does a good enough job at fixing cyber issues, but that's hardly a safety concern.
  - GTP 2mo ago
    We can only wait to see if this is true. Another possibility could be that it was an answer to USA's government considering a ban on chinese models. In this way, he fueled the discussion around the importance of open weight models.
    - applicative 2mo ago
      Xi actually said that models of the strength to pose security issues will be permanent state secrets -- in the same speech that the first western takes translated as actually using the words 'open weights' which of course nowhere appeared. Now: when will "models of the strength to pose security issues" appear? Maybe my inference 'months' is wrong, but they seem to be advancing rapidly. The administration blather about banning open weights is characteristically confused. Xi has already stated (what is obvious) that he will ban security-endangering weights and keep them a state secret.
  - satvikpendem 2mo ago
    He explicitly said he wants open weight models at his recent speech at an AI conference in Shanghai: https://news.ycombinator.com/item?id=48970449#48970784 https://news.ycombinator.com/item?id=48970449#48970784
    - applicative 2mo ago
      The Chinese equivalent of the expression 'open weights' appears nowhere in this talk. You believed the Western press. Chinese AIs are not typically open. The most important by far is Bytedance.
      - Petersipoi 2mo ago
        The second China shuts down open weights is the second they lose the AI race. Nobody is going to use Chinese models if they're closed, besides hobbyists who don't have anything they care about getting stolen.
      - satvikpendem 2mo ago
        Openness not open weight. You keep saying this and that was said while not quoting anything, not sure why anyone should take your comments here seriously.
  - codemk8 2mo ago
    Me.
  - culi 2mo ago
    He literally just announced WAICO to make a framework to allow for open source LLMs for disadvantaged countries for the foreseeable future
- arizen 2mo ago
  Why not also Qwen?
  - dannyw 2mo ago
    Qwen/Alibaba have stopped doing open weights releases for a while. No grudge or anything, I'm certainly not going to look at a gift horse in the mouth, but both DeepSeek and Moonshot have been very consistent with open weights as well as sharing actually detailed research. In terms of open research, China has absolutely overtaken the US.
    - anon373839 2mo ago
      Qwen has a pinned tweet stating that 3.8 will be released as open weights soon. I guess it remains to be seen, though, if they’ll do the smaller model sizes or only the big 2.4T one.
      - SXX 2mo ago
        Most interesting part IMO is whatever Qwen open weight will include image / video capabilities since its where they are strongest.
        mcbuilder 2mo ago
        Also base models versions are very useful for researchers, since they allow for a cold start to post training.
- siva7 2mo ago
  CCP will be happy! Go on and share all your data with them..
  - chorizo 2mo ago
    I’m developing open source tools, so happy to have all my context traces be public if it helps improve future models.
  - fdsjgfklsfd 2mo ago
    Yes, they trained on my open source code and Wikipedia edits and Stack Overflow answers that I shared freely, so it's only fair that they release their models as open source and share back to the community that created them. I only allow my training data go to open source models.
    - gr_norm 2mo ago
      Yeah, at least when I share my training data with labs releasing their models openly (Chinese or American or otherwise) it's nominally so an even better open model will land in my hands in the future.
  - neya 2mo ago
    Yeah, because, your data is best collected by the US labs, right? US or American, don't trust anyone, these are open weight models. Host them yourself if you feel strongly about privacy (as you should). I honestly don't know of any OSS open weight models from the US labs as good as Kimi K3 or Deepseek V4 though.
  - genxy 2mo ago
    At least you get based models back at some point. You supply data, they supply compute and open weights.
  - anigbrowl 2mo ago
    I will! I pay their sales too and consider it quite reasonable.
  - 2mo ago
dnhkng 2mo ago
DeepSeek V4 Flash (Preview → 2026-07-31) • Terminal Bench: 56.9 → 82.7 (+25.8) • Toolathlon: 51.8 → 70.3 (+18.5) Compared to GPT-5.6 Terra: • Terminal Bench: Flash 82.7 vs Terra 78.4 • Toolathlon: Flash 70.3 vs Terra 53.1 • DeepSWE: Flash 54.4 vs Terra 69.6 • Agents' Last Exam: Flash 25.2 vs Terra 50.4 Trading blows with Terra, which is pretty interesting. No clear winner on these benchmarks, and wildy differeing scores. Very interesting!
- Iolaum 2mo ago
  Since they did this with their own harness I m not sure it's apples to apples comparison.
  - NitpickLawyer 2mo ago
    > not sure it's apples to apples comparison. They're literally comparing the previous version of the same model with the new one. It's based on the same architecture, same pre-trained model, just different post-training. It doesn't get more apples to apples than this.
    - dnhkng 2mo ago
      I think the commenter means the Flash vs Terra benchmarks.
      - NitpickLawyer 2mo ago
        Ah, my bad. Yeah that makes sense. They do say "The official V4-Flash natively supports the Responses API format and is specifically adapted for Codex.", so at some point someone will make a "same harness" comparison.
  - dnhkng 2mo ago
    It will be fair if they release the harness though. I think now the future will be paired model-harness releases, not just weight dumps. The performance changes are so big with the right harness that is makes sense to engineer the harness and fine-tune the model to one another from the start.
NitpickLawyer 2mo ago
This is more exciting than k3, IMO. Dsv4 models are extremely cheap to serve. Improving their capabilities has lots of downstream effects, as it becomes "good enough" for more and more tasks. DS was serving the pro version at extremely low prices for a long time, and they've had integrations with opencode & other providers, so they likely gathered a lot of data from real developers doing real tasks (on openrouter they were labeled as such). Now they can use those live scenarios to further post-train their models and improve them further. Can't wait to see if distilling k3 into dsv4 brings additional improvements. Anyway, having fast cheap models getting better is great for the community. Especially since these don't "go away" on a provider's whim. Whatever capabilities they get, can be used "forever" going forward. And, at least flash can be ran "at home" with <10k in hardware, which isn't really possible / feasible with glm/k3 larger models.
- dnhkng 2mo ago
  Totally! This with DwarfStar delivers usable local AI (I hope!)
  - dannyw 2mo ago
    Usable local AI has been here for a while, esp on say a 5090. You can’t treat Qwen3.6 like its fable, but if you prompt precisely and specifically it’s a great executor. I actually found it refreshing to use more of my brain for once, and actually have to think deeper about what I’m trying to do, and how to build it.
  - Tepix 2mo ago
    What are your goalposts? Depending on your requirements, there have been many moments of usable local AI. More recent ones were gpt-oss 120b and Qwen 3.6 27b.
  - genxy 2mo ago
    Parent is referring to https://github.com/antirez/ds4 https://github.com/antirez/ds4
- KaseyKim 2mo ago
spwa4 2mo ago
In case people want to run it, it's DeepSeek-V4-Flash-284B-A13B. So it should just barely run on a single B300, and it's small enough that it'll barely run on an M5 Max too.
- wolttam 2mo ago
  It runs really well on 2 DGX Sparks - 60t/s
  - Tepix 2mo ago
    Yes, the Dual DGX Spark looks like the sweet spot for this model for now. Good preprocessing speed. Lots of context. Fast enough for 1-5 devs perhaps. Around 8200€ as of today (used to be 6000€). Dual Strix Halo is much slower and current Macs with 256GB are both slower and more expensive (Mac Studio M3 Ultra 256GB around 12000€). To get something faster than the two Sparks you'd need to spend more than $22000 for a server with 2x RTX Pro 6000 at $10000 each. Beyond that you could get 2x AMD MI350P.
- arjie 2mo ago
  Not yet, right? That's the old DS V4 preview release. We're still waiting for the weights to come out.
  - benjiro29 2mo ago
    Probably the same. When the same base model is trained, the weight do not tend to change a lot. GLM 5.0 > 5.1 > 5.2 are the same base model, that just kept being trained. Weights hardly change as a result. Think in the like few percentage points size difference.
    - deleted 2mo ago
      [deleted]
- lukan 2mo ago
  "it'll barely run on an M5 Max " The max version I could order now with 128 GB? If so, the price for local inference would be 12 000 € vs 500 000 € for a B300.
deleted 2mo ago
[deleted]
nickandbro 2mo ago
I wouldn't doubt GPT 4.6 Luna being in the top left quadrant's center on the Cost per Intelligence Index is not concerning for Liang Wenfeng. You have to remember DeepSeek v4 flash even though a bit cheaper, does not have vision abilities, which is a big draw for agentic tasks. I admire DeepSeek's openness, but even they have been raising prices after their discounts.
- minraws 2mo ago
  They haven't raised prices though the plan was to increase it with peak hour usage for V4 Pro GA release, they didn't do that, so no price increases there I believe. As for vision yeah it sucks but Luna is also 2x input and 1.5x output for 1M context... That's around 0.4 in/1.8 out DSv4 is wayyy cheaper. And it's open now you have Luna at home if you have a decent set of GPUs you can run this on 2Sparks or one very expensive Mac or just like 6-8 5090s..
  - minraws 2mo ago
    I know most folks can't afford it I am working on making it viable to rent shared hosting the biggest issue is data leak and prompt injection attacks with shared hosting. (Since the server owner connects to your main system via the coding agent) I guess using a ZDR provider is good enough for now.
- dudisubekti 2mo ago
  Gpt 5.6 Luna cache read is $0.02 per mtok V4 flash cache read is $0.0028 per mtok That's not "a bit cheaper", just saying
  - nickandbro 2mo ago
    That's a good point. Yeah their caching input is insane.
    - ignoramous 2mo ago
      DeepSeek v4 API rates are only matched by Xiaomi's MiMo v2.5 series. Quite similar in capabilities too (at least before today's update).
wolttam 2mo ago
Hooray! This model makes me very optimistic about the future of local inference. The CyberGym score stands out to me.
ggcr 2mo ago
Woah, a 200B model competing with GLM-5.2 and getting close to Opus 4.8. Quite impressive. If those numbers translate well to its general capabilities, with the great caching DeepSeek has, I feel like this model will get tons of usage.
- lostmsu 2mo ago
  Not just 200B model, it is only 160GiB.
- ignoramous 2mo ago
  MiniMax's another lab that's known for relatively smaller models (their latest, M3 is 295b) that punch way above its weight.
KronisLV 2mo ago
Wonder how good the proper version of V4 Pro will be. I'm still considering pulling the trigger on the annual subscription of Kimi for K3 but it's sometimes slower than I'd like (at least when compared to Anthropic) even on their Vivace plan, and the token limits on the GLM Coding subscription for GLM 5.2 were too easy to hit.
tosh 2mo ago
[dead]
arjie 2mo ago
Oh my goodness what an update. I need these weights. It's an incredible model for the size. The improved tool calling etc. should be able to make my harness way simpler. This runs at mega-speed on prosumer hardware (2x RTX Pro 6000).
- amunozo 2mo ago
  How many tok/s are we talking about?
  - arjie 2mo ago
    The old one was 160 tok/s. With DSpark it’s like 250 tok/s or higher. I don’t recall from tbe last time I was looking. You can turn on farther drafting and get more.
Goranek 2mo ago
Kimi K3 (instead of Opus) for expensive stuff, DSV4 Flash for tasks (instead of Sonnet)? Does this make sense?
- geek_at 2mo ago
  it does! I'm always amazed when I use DSV4 flash for coding or server checks and after an hour of working with it my (pure api call) balance is about 30 cents
- baalimago 2mo ago
  Looks like they will release an updated version of deepseek-v4-pro soon, which most likely will beat kimi k3 at both intelligence and cost (judging by the vast improvements to dsv4 flash)
- try-working 2mo ago
  [flagged]
wkcheng 2mo ago
If the benchmarks are real and reflect actual use, then this is an insane model. This 300B model outperforms the previous DS4 Pro preview model (1.8T params), and it looks like it outperforms GPT 5.6 Luna too. And it's still cheaper than Luna, even with the price decrease. Crazy.
- cbg0 2mo ago
  On DeepSWE Deepseek is 54.4% and Luna is 67%
  - benjiro29 2mo ago
    But on Terminal bench, its * DS4 Flash: 82.7 * GPT 5.6 Luna: 75.7 For reference, that puts it on the third spot behind GPT 5.5 and Fable 5. For some reason GPT 5.6 Sol is not showing in the leaderboard. If it did, then DS4 Flash was number four. The thing is, even if Luna is better in DeepSWE and has the 80% discount. DeepSeek is still cheaper. -------------- DeepSeek V4 | Flash GPT-5.6 Luna (New) -------------- Input (Cache Hit) $0.0028 $0.02 Input (Cache Miss) $0.14 $0.20 Output $0.28 $1.20 -------------- Both Luna and Flash are heavy on the reasoning > output. And the cache hitrate + prices also matter. Reality is, you can not go wrong with Luna or Flash at those prices. And remember, DeepSeek V4 Pro is still in the rafters, what is ironically closer to Luna's new price.
    - flashblaze 2mo ago
      Agreed. The only thing missing is multimodal capability
- gr_norm 2mo ago
  OpenAI must've known this was coming, hence the Luna price drop. This competition is amazing!
egeozcan 2mo ago
Every time I want to have fun coding something with natural language processing, I use deepseek flash. It's just incredible for the price. I have a fairly popular app with 400 users that uses DeepSeek in the background and it still didn't hit even 50 bucks of usage in a month.
- indigodaddy 2mo ago
  Mind sharing the name? Sounds interesting.
try-working 2mo ago
Let's see how the market reacts.
flysoft 2mo ago
Finally have a model with usable intelligence, at a reasonable price. Can't imagine what Pro GA would look like, considering pro preview has only 1.6t parameters.
thirtygeo 2mo ago
For both US and China models - what standard security checks and QaQc are you all doing? We're running small gamuts to test for unsolicited jailbreaks (model jailbreaks you) and incorrect records (Fake Accuracy - as Easter Egg or common thread) meaning falsified logic or information cooked in by the developers, rather than the training data speaking for itself
PhilippGille 2mo ago
The previous V4 version wasn't called “Preview” by most inference providers. For example, the OpenRouter model slug was `deepseek/deepseek-v4-flash`. So now there will be confusion when someone talks about V4 Flash or when someone offers V4 Flash inference. Why not call it V4.1?
- try-working 2mo ago
  DeepSeek themselves called it `deepseek/deepseek-v4-flash`. Pro is still like that.
  - PhilippGille 2mo ago
    Yes that's my point. The old and the new version are different in capabilities, but now when someone talks about DeepSeek V4 Flash (in benchmarks, on inference providers), you don't know which exact version it's about. Some providers like OpenRouter now call it `deepseek-v4-flash-0731`, but even in places like here on HackerNews people say things like "Sonnet is better than DeepSeek" without specifying a version or a reasoning effort, certainly no one will mention that `-0731` suffix when talking about DeepSeek V4 Flash.
    - benjiro29 2mo ago
      I think it does not matter. Most people who use these types of models are into the IT world, and will know/be informed very fast that there is a difference. People will likely also use the 0731 behind it. The only issue i see, is 3th party providers that have not yet updated. But that is going to be a short time periode. There is no reason to not update.
- petu 2mo ago
  It probably would be called 'deepseek-v4-flash-0731' in API edit: nope, at least deepseek kept "deepseek-v4-flash" and just updated model underneath. I guess preview is no longer worth serving with that release and you'd have to look through inference provider docs to see if they've updated, yeah..
baalimago 2mo ago
Very promising. So it will both keep the speed and reduced price, yet exceed performance of the quite sufficient deepseek-v4-pro? Should be extending the lead in intelligence/cost index, as deepseek-v4-flash already were the most price efficient model, which now becomes even better. Although, in the deepseek APIs, the cost is leaking all information about codebases to China.
- ilaksh 2mo ago
  Supposedly better than GLM 5.2 according to at least one benchmark.
kamikazechaser 2mo ago
The flash variant is on par with Sonnet 5 on DeepSWE (54%). Big, if true.
storywatch 2mo ago
How's their performance in English prose? We are currently searching for cost effective ways to keep story wikis up to date.
- amunozo 2mo ago
  I am interested in this too, as I think it could be these models are overly optimized for coding. Let me know if you figure it out!
  - storywatch 2mo ago
    What's your use case? I will probably run some tests soon, stay tuned.
f311a 2mo ago
I've been driving flash model for 90% of my tasks. It's better than pro (for unknown reasons), very cheap and fast. I try to keep changes under 1000 lines and drive architectural decisions myself, barely notice any difference compared to frontier models. The rest 10% is to spot bugs, security problems and to investigate better architecture, which flash can also do pretty well, I just cross check it. Faster iterations are way better for me, I hate waiting for 5-10 minutes on small changes. I tried to use recent versions of Kimi and GLM, but they use too much thinking for no reason and are pretty slow because of it. I also often feed a lot of data to it, without worrying about hitting the limits: dependencies (to find bottlenecks in them), logs, performance dumps and so on. Also, it will never complain about security guards, I've been using it to reverse engineer binaries.
- regularfry 2mo ago
  It's good but (at least on openrouter) it's got an annoyingly tight output token limit. So if it does get stuck in a reasoning pit, it won't work its way out of it in time. It's replaced the Kimi models for me though.
  - u8080 2mo ago
    Try to use DS platform directly - cheaper and better than openrouter, no subscription
    - dghlsakjg 2mo ago
      Openrouter has cheaper inference than deepseek for the prior version of v4 flash, which I suspect will happen within a day or two with this version, and they don’t offer subscriptions. Are you confusing it with opencode?
      - u8080 2mo ago
        No, maybe I've checked too much time ago, but direct DS was cheaper for all versions - also I had issues with openrouter providers availability
miyuru 2mo ago
Judging by the openrouter leaderboard ranking for today, it looks like Dv4F us more popular than mimov2.5. https://openrouter.ai/rankings?view=day#leaderboard-table https://openrouter.ai/rankings?view=day#leaderboard-table These days cost per task is more important, and SOTA models have become expensive.
- benjiro29 2mo ago
  MiMo, the overlooked sidekick to the hero. Will be interesting to see what Xiaomi bring to the table. These massive jumps in cheap models, is really great times!
ra 2mo ago
What's the best way to run this on a 64GB M2 Pro?
- petu 2mo ago
  Weights are yet to be released (maybe in 24H, Deepseek has track record of releasing same day). https://github.com/antirez/ds4 https://github.com/antirez/ds4 is often mentioned for DS4F on Mac, but 64GB is likely not enough to achieve reasonable speeds (official weights should be ~160GB).
- Tepix 2mo ago
  DS4Flash has 284B weights. 64GB? No go.
  - zozbot234 2mo ago
    The native weights are 4-bit for the sparse experts, and they quantize to ~80GB with limited degradation in real-world performance. That's a viable target for 64GB with SSD streaming, though it will be slower than keeping the whole thing in RAM (especially on a M2-class machine with its slower storage).
    - Tepix 2mo ago
      I consider less than 4bit to be too poor quality usually. Got any benchmarks to measure quality?
lionkor 2mo ago
I use deepseek for a lot of my personal day-to-day agent needs, and I will simply put this here and let this speak for itself, last 30 days: - Cost: $4.55USD - API requests: 3,467 - Tokens: 323,183,886 And as an engineer who leads a small team, I have very high standards for quality, and these carry across to my personal projects where I use deepseek. It has not disappointed at all for coding or review tasks. For everything else, use another model.
- innis226 2mo ago
  But doesn't it hallucinate a lot? Does that affect your workflow?
  - lionkor 2mo ago
    It hallucinates plenty, about the same as Codex models and all other LLMs! I review all code it writes, thoroughly, check the test coverage, write tests myself, have other models/chats cross-check the work with a review skill (which I've shared in another comment in this thread). Usually unreviewed code only gets committed if I really don't care, like for one-off scripts, which I sandbox with github.com/lionkor/sbh or run as an unprivileged user.
- dakolli 2mo ago
  [flagged]
  - ncphillips 2mo ago
    For doing what?
    - dakolli 2mo ago
      everything.
      - hlynurd 2mo ago
        There's a small relief in knowing that these junk comments are at least not AI generated (in all likelihood.)
kmarc 2mo ago
Essentially I'm running everything on flash now inside pi. With the correct set of MCP servers, context reducer tooling and skills it can implement any task I throw at it. Some sessions take 30+ turns, but it's fast and cheap; all this in an hour, with ~$0.5 cost. (TBH though, in my multi-subagent workflow I do use other, more expensive models for planning, reviewing, oracle-ing) I haven't used our slow opus subscription for weeks. (Also set up an OpenWebUi self-hosted chat that works from my phone, has some mcp and skills. fully replaced perplexity. Monthly cost ~$18 for hosting and subscriptions)
- peperunas 2mo ago
  Do you have any recommendations of such extensions for pi?
  - try-working 2mo ago
    pi-role-model
  - kmarc 2mo ago
    Recommendation? No. Just go with the passive-aggressive advice "let pi build it for you". :-) To be more constructive, what I did (as an experiencd SWE but a complete noob to agentic coding): went to pi.dev's extension marketplace and looked into all the new shiny stuff. Subagents, mcps, context and memory optimizers, skills. Using the most popular ones (not necessarily the best ones) It was like 15years ago learning the new mindset of vim (and spending a ton of time to customize it to my workflow). My understanding is that Claude and opencode doesn't give you this flexibility. Learning all these stuff drove me to also set up openwebui, and it was such a successful private project that I implemented it at work (with jira/confluence/bazel query access) and management said "we need this by tomorrow". I believe the models matter not that much anymore. The "harness" does. (unless you just want to vibe code. Thebn, throw crap at fable and call it a day)
    - peperunas 2mo ago
      Got it :-)
vladukha 2mo ago
Where do you guys get deepseek? I'm hearing a lot of good reviews and want to try it with my pi config. from the deeepseek themselves, openrouter, or anywhere else? does it make a difference? [edit]: whoa it is really fast. will take some time to evaluate quality thou
- Gigachad 2mo ago
  I used it through openrouter. Plugged in to the vs code copilot bring your own key thing. Played around for a few hours and used up 80 cents of tokens.
  - Lalabadie 2mo ago
    Anecdotal data from my own tests: allow only one provider if you want good cache usage on OR. 80 cents is probably 4x the price you should have paid. Providers' cache hit stats are available to consult, and only 1-2 of them behave properly if I remember correctly, zero if you request providers that don't store and train on sessions.
- psibi 2mo ago
  I've been using DeepSeek directly. I've heard from colleagues that using it via OpenRouter is slower, but I'm not so sure about that.
- embedding-shape 2mo ago
  For hosted APIs, it's a lot cheaper to use their own infra, caching seems a hell of a lot better there compared to OpenRouter, and indeed the tok/s seems higher. They also have peak/off-peak pricing, so if you can hold off with your request, you get a pretty big discount. Otherwise, if you're trying to run it locally, even really low quantizations like DeepSeek-V4-Flash-IQ2XXS-w2Q2K-AProjQ8-SExpQ8-OutQ8-chat-v2-imatrix seem to actually not be so dumb compared to smaller models with same quantization, might be worth a try if you're sitting on a lot of RAM/VRAM yet not industry-scale amount :)
- ticoombs 2mo ago
  > does it make a difference Probably not. But Opencode-Go is a great solution for those who don't want to pay DeepSeek directly (or can't due to reasons) Selfish referral code: https://opencode.ai/go?ref=R1AJZT4VBX https://opencode.ai/go?ref=R1AJZT4VBX
f6v 2mo ago
I'm thinking of using ChatGPT for making plans and V4-Flash for execution. Does anyone have good advice on pairing different models?
- embedding-shape 2mo ago
  Pairing non-APIs with APIs tend to be a hassle, and risky, as usually that breaks the ToC. I guess easiest for you to test if it's worth using the OpenAI API, is to manually copy-paste responses between wherever you run V4-Flash and the ChatGPT UI. What I've done in the past is basically .zip up the entire project directory, ignoring files from .gitignore, then asking ChatGPT Pro to inspect that and come up with a plan, then you paste that to where you have V4-Flash. Basically how we did "vibe pair programming" before the TUI agent harnesses appeared in the ecosystem :)
  - yuzuquat 2mo ago
    reminds me back in the day when we used to do version control with google drive. you generally don't need to do this anymore i don't think. it should be fairly trivial to open the codex cli in the project directory, ask it to do some analysis and planning -> save to md. then opencode with deepseek to read that md and start implementing. consider that some cross-model subagent workflows already exist: i use claude/fable to plan and there are openai plugins to directly spin up codex subagents. this latter approach gives claude/fable more directly control to babysit the codex agents whereas the former is more of a clearcut handoff
    - embedding-shape 2mo ago
      That approach won't give you access to the "Pro Mode" nor "Deep Research" though, which if you're paying for a Pro subscription already, "Pro Mode" is probably the top-top when it comes to "extensively researched answers & plans" across the entire ecosystem. That said, I do ask it to produce a .md plan that later is used with agents :)
  - f6v 2mo ago
    [dead]
Havoc 2mo ago
>benchmark results far exceeding V4-Pro-Preview: Wow that's crazy Good times for those that don't need strict data protection
- blackoil 2mo ago
  These being open provide much better data protection.
- kzrdude 2mo ago
  Open weights means that there is a free market on providing inference using this model. Some of them will offer good data protection. (Well, hopefully)
sim04ful 2mo ago
Why didn't they increment the version as atleast a patch update
- markasoftware 2mo ago
  They want to be the next Google it seems
- kzrdude 2mo ago
  Yes, and even if they seem to have updated endpoints in place they should assign the service a version number.
- rubslopes 2mo ago
  I was also so annoyed by this. It makes communication all around difficult. Why don't they simply call it 4.1 flash?
- crvdgc 2mo ago
  My guess would be the version number tracks the architecture change, not the weight change.
- deleted 2mo ago
  [deleted]
- bel8 2mo ago
  So whoever is using DeepSeek V4 flash gets a massive upgrade without having to change any config.
  - sim04ful 2mo ago
    That's an absolutely terrible idea for any non-trivial project consuming it.
    - behindsight 2mo ago
      Wasn't it stated as being in "preview" prior to this? If implementing non-trivial tasks on a preview model surely there is some anticipation of it not being the final stable release? Unless you mean they should have appended a "preview" suffix on the endpoint for extra good measure?
sourcecodeplz 2mo ago
i've made a comparison between this and GPT Luna (recent %80 price drop) https://x.com/SourceCodeplz/status/2083099712760987746 https://x.com/SourceCodeplz/status/2083099712760987746 i prefer GPT-5.6 Luna honestly
mordae 2mo ago
I was just using it when it landed. It started reasoning more extensively from nowhere and precision went up a lot. It also changed its prose style for the better. Looking forward to weights.
nathaah3 2mo ago
DS v4 flash has been my goto model for tasks in work. its been unsurprisingly fast and cheap.
throwaw12 2mo ago
how different is their harness from Pi coding agent harness, is it possible to make an extension for Pi which can implement deepseek harness?
sqemo 2mo ago
DeepSeek is great for tasks and software I already know well. Even if it gets something wrong, I can usually verify it myself. But when I'm working with a programming language I'm not familiar with, I prefer using Codex or Claude.
- k__ 2mo ago
  Yeah, it needs quite some hand holding. I didn't do much agent coding and had a mix experience. 1. It would build something that was in the spirit of what I wanted, but unusable in practice. 2. It would build something quite useful, but only the public APIs were nice, the deeper code layers would get more and more convoluted. 3. It would built what I wanted and it would have okay-ish code. However, for 3. I also had to add a custom AGENTS.md, many more code example, extra repos as subtrees, and review any code that had new concepts. Much more work, but still much less than typing it all by hand.
truth_seeker 2mo ago
The magic of post training with valuable dataset
dakolli 2mo ago
Chinese labs rushing to release models this week, because it's inevitable that Washington regulates Chinese models in the next 4 weeks. All the US AI leaders have been taking trips to Washington this week, what do you think they're there for..
k__ 2mo ago
I'd take more throughput while everything else stays the same.
znnajdla 2mo ago
The conspiracy theorist in me wants to think that the 80% drop in GPT 5.6 Luna prices today is correlated with this update from DeepSeek. Perhaps OpenAI has already hacked its competitors with it's Mythos-like models and is aware of what competitors are doing and is able to react in advance.
- nchmy 2mo ago
  Seems to me that it's the reverse. Open ai dropped prices to compete with deepseek etc and then deepseek released this update to negate Luna.
mekky16 2mo ago
if they were anthropic they wouldve just released it as a new model
yewenjie 2mo ago
What was preventing them from calling it v4.1-Flash to distinguish it better?
- lionkor 2mo ago
  Sounds like it'll replace v4-flash, v4.1 would be nice to keep both available. On the other hand, it's nice to just get an improvement on anything that asks for "deepseek-v4-flash" without having to change the model string.
  - krapht 2mo ago
    I think that's backwards. Anything that changes the performance of a model deserves a minor version bump. A new model has to be qualified before being pushed to production; but we don't get the choice here, just cross your fingers there are no regressions at all on all possible tasks the model might be asked to do.
    - lionkor 2mo ago
      I should have worded it differently. Having a model selector as `string` seems like the wrong choice. At the very least, I should be able to select 4.X, like how we select dependencies, so people who rely on specific behavior can pin to 4.0 and I can say version >= 4 if I don't care.
    - halJordan 2mo ago
      That's on you for using a preview/beta. It was properly qualified when it was released. No one complains when ios goes from beta to release; even though it will be ios 27 beta -> ios 27 next month
    - xbmcuser 2mo ago
      its an open source model if it is important enough that you have to worry about a new version breaking something then why the fuck was that not running on your own servers this is not an Anthropic or OpenAI closed model that you only have access through an api
amelius 2mo ago
Note: if you are having success with a model, then please post what you are using it for. Writing HTML/CSS is very different from writing Rust/C++ or doing maths.
- dandaka 2mo ago
  Text classification, structured data extraction, rewrite
- sparse-Matrix 2mo ago
  I've been having better-than-most performance using qwen3.6 to write python/flask. I tried using it to generate some rust code yesterday, and it generated much code but only ever came within 1 error of a testable build. The 4th or 5th full rewrite is sitting in the buffer right now. I'm currently looking to up my game with Bottlecap AI's return of qwen3.6, 'thinking cap'. Alleged to be twice as fast and superior at coding over extended sessions (vs. 3.6). We'll soon see.
  - ilaksh 2mo ago
    You should specify which model size and quant because there are many of both.
- f311a 2mo ago
  I do Python, Go and Rust. Go works the best, I would say Python is worse than Go. Rust works perfectly fine, but when I use Rust, I usually pay closer attention to performance, so I have to guide it a bit, to improve cache locality, use simd, avoid unnecessary allocations and so on. Terra has the same issues with Rust. If you always prompt models to achieve the best performance, the code is usually no the one that I want, they optimize unnecessary/cold parts or blindly optimize stuff where compiler takes care of the optimizations already. See my other comment for more information on how I work with it. In short, keep the changes under 1k lines, context under 120k (ask it to use subagents), drive the architecture yourself.
- fdsjgfklsfd 2mo ago
  I use DeepSeek V4 Flash (before this update) for most things: - OpenCode for codebase editing: python scientific computing and LLM projects - Open Interpreter Classic (python version) for Swiss army knife terminal replacement one-off task type stuff.
sparse-Matrix 2mo ago
This may come as a surprise to a lot of AI concerns, but I have -zero- interest in paying for a model.
- Tepix 2mo ago
  Why mention it? Just download the weights when they become available.
- kzrdude 2mo ago
  Then DS V4 flash is pretty relevant, because it's pushing prices down.. as well as being self hostable with a large enough rig.
Tepix 2mo ago
[dead]
Tepix 2mo ago
Sounds like a big improvement. No mention of weights, just API. When will the updated weights be released?
- fdsjgfklsfd 2mo ago
  Was already released before your comment: https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731 https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731
ilaksh 2mo ago
I wonder when the antirez/ds4 group will have an update to their high accuracy 2 bit quant. Although it's funny that I am thinking about that at all because I have a 2060 :P . My local inference is playing with Gemma 4 E2B and MiniCPM 5 1B.
- throwdbaaway 2mo ago
  Objectively speaking, the 2 bit quant from antirez has very low accuracy. Meanwhile, his 4 bit quant does have decent accuracy, but is a bit pointless by being bigger than the full precision MXFP4 quant. Anyway, they all work fine in practice.
- jtbaker 2mo ago
  Looks like a couple of people are already on it: https://github.com/antirez/ds4/issues/635 https://github.com/antirez/ds4/issues/635
HyperL0gi 2mo ago
Is anyone using DSv4 for their agents that is not related to writing code? Curious about use cases specially for someone using gpt-5.4 mini for classification, categorization, etc
- freakynit 2mo ago
  I use it to conduct thorough online researches. Plug-in some online search MCP (like the one I use: https://jerrysniffs.online https://jerrysniffs.online ), and the flash models dig through the internet for dirt cheap.. Most of the times, the total cost, including search API's, is less than $0.05 for full deeply researched output, and the research is actually good.
- Lalabadie 2mo ago
  It's been good for one-off cases in my limited experience. I would describe its behaviour as Sonnet-shaped, if that makes sense to you. Good answers but it often decides to reason a lot about simple things before getting to an output. At the speed Flash has on most providers, it doesn't really turn into a latency concern.
- markab21 2mo ago
  We use it at a moderate scale, self-hosted on B300 hardware. It's great :D QA analysis of voice transcriptions. Napkin math: we operate at 2-5% of the cost of running on Equiv Frontier, though this changes near-weekly because pricing is so volatile. It took us about a month to get the inference configured to achieve these numbers. But if you can get your hands on a pair of B300 GPUs and the context works, it's untouchable for price/performance. (B200 would work, but you don't have the B300's memory, which lets you run it on 2xGPU instead of 4xGPU... with Dspark, it's like magic) On a side note, for tasks that don't require the intelligence of DS v4 flash, we're using Nemotron-3-super with incredible success. I'm shocked we're not seeing more adoption of this model, given how easy it is to fine-tune and how blisteringly fast the nvfp4 version is. (A single B200 GPU can produce an insane amount of throughput with Nemotron 3 Super.)
XCSme 2mo ago
Can't really use it now, without giving away your data: > Trains: this provider may use prompts for training and may retain prompt data.
- Philpax 2mo ago
  That will cease to be a problem in the next 24 hours, now that the weights are out: https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731 https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731
alecsm 2mo ago
I've been using DeepSeek Pro for a while and Flash only for certain dumb tasks where I only need the speed of a LLM and not big brains. I find the newest OpenAI and Anthropic models to be way better for big tasks that require many decisions but I don't like that anyway because I lose track of what's being done. Knowing what I want for every prompt makes DeepSeek Pro the best LLM for me. It allows me to work relatively fast at a very low price.
sreekanth850 2mo ago
how this compare to luna high with reduced pricing.
throwa356262 2mo ago
Gentlemen, start your DGX Sparks https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731 https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731
namuol 2mo ago
Can someone please explain how these models aren’t just fine tuned for benchmarks? I’m not plugged in to this space much but it seems like such an obvious problem…
- sroerick 2mo ago
  They definitely are - but also people are using them pretty extensively for work. So ultimately you can't really fake "is it good". But there's no real measurements of that when a model is released, so we are stuck with benchmarks.
  - namuol 2mo ago
    I will continue to ignore the benchmarks.
wg0 2mo ago
Don't know about the bench marks but I am getting Opus 4.7 level performance at fraction of cost with DeepSeek V4 Flash set to high. It is a reliable workhorse.
w2seraph 2mo ago
This made my day !
troglodytetrain 2mo ago
This is very exciting, my own niche micro-saas has already been able to make heavy use of DeepSeek-V4-Flash for my use case, I am looking forward to seeing how performance improves.
heyalexej 2mo ago
Long story, I have humongous zai GLM 5.2 token budget that I'm using in a similar fashion as many comments explain here. GPT 5.6 or Fable 5 for planning, GLM for implementing, researching, extracting and many other tasks I consider grunt work. Very happy with the performance, speed isn't all that good though. I'd be curious to hear from someone who works with both, DeepSeek and GLM side by side.
prtmnth 2mo ago
Eagerly awaiting their V4 Pro update!
sebjones 2mo ago
The cost is amazing! So DSV4 Flash is not multi modal right? How do you use it to review UI work I wonder? Im doing a lot of frontend work. I wonder how it review its own work.

745 points by dnhkng 2mo ago

They're always very understated in their update descriptions. This is actually a HUGE improvement in the model's capabilities rather than just a small tweak.

dannyw 2mo ago

Deepseek and moonshot are the only two providers I consent to training for.

applicative 2mo ago
Xi going to shut down open-weighting of them in a matter of months. No one seriously doubts this. They will be too powerful and they will be gone.
- darkwater 2mo ago
  What makes you state this?
  - baublet 2mo ago
    China bad
    - applicative 2mo ago
      I'm a) quoting Xi's speech and b) projecting rapid China development to Mythos level. Either you think China will never get to 'Mythos level' because you think China bad; or you think they will release the weights, because you think China bad. Its incredible the weight of ideology over facts in this discourse
      - satvikpendem 2mo ago
        You haven't quoted anything actually. Provide sources to your claims.
  - riskd 2mo ago
    Decades of xenophobic propaganda
    - 1234letshaveatw 2mo ago
      Wow! Amazing observation! Wait, do you think there could have been any pro Chinese propaganda? Perhaps even some taking place at the present time? I think it could be possible?
      - Zetaphor 2mo ago
        I'm sure there's plenty, but if you put on your rational hat and think about the motivations of the Chinese government you'll realize this claim makes no sense, and there's plenty of evidence and good reason saying the opposite
        1234letshaveatw 2mo ago
        you are probably right! nobody does more domestic discourse shaping than China, but good reason says none of that would take place externally
      - riskd 2mo ago
        You’re clearly too far gone to even fathom the thought; so you grasp at these straws for hope that the China you grew up “learning” about is the same in reality.
    - applicative 2mo ago
      No, reading Xi's speech. They aren't going to give their Mythos - presumably a few months away - to the Sinaloa cartel or Uighur hackers or the US military or etc etc
      - h8hawk 2mo ago
        They have already released their models (GLM 5.2 and K3). This is why Amodei and the rest of the effective altruist lobbies are trying to pressure the US government to both ban open-source models and pressure China to do the same. I’m curious to see why you’re so eager to ban open-source LLMs while being okay with Anthropic’s control. Do you think they’ll rebel against you?
- gravypod 2mo ago
  What would the benefit of this be? If China stops open weights, US labs still have the intelligence frontier. Maybe once Chinese models have speed, cost, and intelligence beat but right now they don't. Undermining out entire economy by subsidizing the release of DIY versions of our main economic drive sounds like a huge win for China.
  - deleted 2mo ago
    [deleted]
  - applicative 2mo ago
    > Maybe once Chinese models have speed, cost, and intelligence beat but right now they don't. Yes this is why I referred to 'months' and was downvoted by people who can't distinguish their politics from reality. You are restating exactly the text you are criticizing. This is the nature of mechanical parrotlike repetition of propaganda: a) You can have 'frontier' models with closed weights. Your sentence is basically a contraction within itself, again, the weight of ideology. b) No one actually knows whether or not the closed weights of Bytedance are beyond all existing frontiers. Again the weight of ideology blinds you to the fact that the real 800 lb gorilla of Chinese Ai is more closed than Anthropic.
    - ricardobeat 2mo ago
      The latest ByteDance Seed model is behind Opus 4.6 in performance. It’s not even in the conversation atm. The parent made a totally coherent commment that China closing off their open weight models would cede the frontier (and majority of AI users worldwide) to the USA. Nothing you said counters that point.
      - applicative 2mo ago
        Bytedance models completely pervade business use across China. It is the OpenAI of China, whether you think its a good model or not.
    - gravypod 2mo ago
- anon373839 2mo ago
  Reuters was reporting that rumor. And then Xi made a public appearance at a conference in Shanghai where he said the opposite of that rumor.
  - applicative 2mo ago
    No in that very speech Xi stated explicitly what amounted to: 'of course when we get a Mythos, it will be a state secret'. In fact the overwhelming weight of AI use in China, the chatgpt so to say, is Bytedance's AI which is absolutely closed and uniquely opaque. The press treatment of these matters was no good and they are slowly walking it back, e.g. NYT yesterday finally actually read the speech.
    - anon373839 2mo ago
      Do you have a source for that? The NYT article does not quote Xi making that statement, and I can't find a source for that. In fact, Xi delivered veiled criticism of the security posturing the US has done: > We should put in place laws and regulations, technological monitoring, early warning and emergency response systems in order to strengthen the line of security, prevent abuses and malicious use, and ensure that AI is always under human control. In the meantime, we should jointly oppose overstretching the national security concept in the field of AI and placing one country’s security over that of others. There was a blog post by a state-linked broadcaster cited in the NYT piece: > “China supports openness, but this does not mean it advocates for the unconditional proliferation of all capabilities,” the blog said. The article also quoted an American journalist: > “If these models do reach those dangerous capabilities, they are not going to let it be a free-for-all in terms of releasing them," Mr. Sheehan said. But a distinction has to be drawn between real dangers (which many people believe LLMs have not actually shown, to date) versus "dangers" hyped up marketing purposes or domestic regulatory-capture motives. Presumably the Chinese government is less interested in the latter.
      - applicative 2mo ago
        "Dangers" may indeed be hyped up for marketing purposes or domestic regulatory-capture motives. But as Xi stated, they will become real. It is just a question of being unaffected by the motives of the speakers, which is what adults learn to do.
- ReptileMan 2mo ago
  It is true. And only Chinese Han people can continue work on what is already released. But they will be forbidden. /s Sarcasm aside - if the community can't get their shit together to continue improving what is currently public, well - we don't deserve free stuff and open weights.
- 1234letshaveatw 2mo ago
  That isn't the Chinese way. They are much more focused on undermine and extinguish. Just look at the European car industry- on its way to being non-existent after the market was flooded, bye bye manufacturing base. Undercut the US AI providers and wait them out, they will go private after they have a stranglehold
  - applicative 2mo ago
    Even Xi's speech was as paranoid as Dario Amodei about the possibility of Chinese AI achieving something at the level of say Mythos. If you seriously believe such a thing will be on Hugging Face I really don't know what to say.
    - criley2 2mo ago
      There is already something on HuggingFace at the level of Mythos. It's called Kimi K3 and it's running laps around Opus5, Fable5, and Sol56 at cybersecurity. It's so good that the US government is rushing to ban all Chinese models as fast as they can.
      - applicative 2mo ago
        Fine, you believe Anthropic was lying about Mythos. In fact no view of the matter is needed to formulate the proposition above. It is clear China will soon have a model with the powers imputed to Mythos but which you deny of actual Mythos. It is a trial to deal with this level of ideological blindness; 'ideology has no outside'. If someone says 'when they get Mythos...', declare the possibility of Mythos to be the real lie. But it is quite possible and will be coming in months.
        zozbot234 2mo ago
        Reading between the lines, it's fairly clear that Mythos Preview only got its reported results in offensive cyber thanks to a highly specialized harness and humongous amounts of test-time compute. We also don't know what kind of post-training/fine-tuning it got on cyber, Anthropic only stated that it wasn't specifically trained for cyber-offense but that leaves a lot of scope for training on other related things. Overall, the Mythos story is a lot less interesting than most people might like to claim - but note that this doesn't require any actual lying. The interest around K3 is a lot more defensible because we actually know what the architecture looks like, how much effort it takes to get it to run, and what kinds of results it gets on cyber evaluations. And no, it's nowhere near "dangerous" enough to where people might honestly want to ban it for real safety reasons. It does a good enough job at fixing cyber issues, but that's hardly a safety concern.
- GTP 2mo ago
  We can only wait to see if this is true. Another possibility could be that it was an answer to USA's government considering a ban on chinese models. In this way, he fueled the discussion around the importance of open weight models.
  - applicative 2mo ago
    Xi actually said that models of the strength to pose security issues will be permanent state secrets -- in the same speech that the first western takes translated as actually using the words 'open weights' which of course nowhere appeared. Now: when will "models of the strength to pose security issues" appear? Maybe my inference 'months' is wrong, but they seem to be advancing rapidly. The administration blather about banning open weights is characteristically confused. Xi has already stated (what is obvious) that he will ban security-endangering weights and keep them a state secret.
- satvikpendem 2mo ago
  He explicitly said he wants open weight models at his recent speech at an AI conference in Shanghai: https://news.ycombinator.com/item?id=48970449#48970784 https://news.ycombinator.com/item?id=48970449#48970784
  - applicative 2mo ago
    The Chinese equivalent of the expression 'open weights' appears nowhere in this talk. You believed the Western press. Chinese AIs are not typically open. The most important by far is Bytedance.
    - Petersipoi 2mo ago
      The second China shuts down open weights is the second they lose the AI race. Nobody is going to use Chinese models if they're closed, besides hobbyists who don't have anything they care about getting stolen.
    - satvikpendem 2mo ago
      Openness not open weight. You keep saying this and that was said while not quoting anything, not sure why anyone should take your comments here seriously.
- codemk8 2mo ago
  Me.
- culi 2mo ago
  He literally just announced WAICO to make a framework to allow for open source LLMs for disadvantaged countries for the foreseeable future
arizen 2mo ago
Why not also Qwen?
- dannyw 2mo ago
  Qwen/Alibaba have stopped doing open weights releases for a while. No grudge or anything, I'm certainly not going to look at a gift horse in the mouth, but both DeepSeek and Moonshot have been very consistent with open weights as well as sharing actually detailed research. In terms of open research, China has absolutely overtaken the US.
  - anon373839 2mo ago
    Qwen has a pinned tweet stating that 3.8 will be released as open weights soon. I guess it remains to be seen, though, if they’ll do the smaller model sizes or only the big 2.4T one.
    - SXX 2mo ago
      Most interesting part IMO is whatever Qwen open weight will include image / video capabilities since its where they are strongest.
      - mcbuilder 2mo ago
        Also base models versions are very useful for researchers, since they allow for a cold start to post training.
siva7 2mo ago
CCP will be happy! Go on and share all your data with them..
- chorizo 2mo ago
  I’m developing open source tools, so happy to have all my context traces be public if it helps improve future models.
- fdsjgfklsfd 2mo ago
  Yes, they trained on my open source code and Wikipedia edits and Stack Overflow answers that I shared freely, so it's only fair that they release their models as open source and share back to the community that created them. I only allow my training data go to open source models.
  - gr_norm 2mo ago
    Yeah, at least when I share my training data with labs releasing their models openly (Chinese or American or otherwise) it's nominally so an even better open model will land in my hands in the future.
- neya 2mo ago
  Yeah, because, your data is best collected by the US labs, right? US or American, don't trust anyone, these are open weight models. Host them yourself if you feel strongly about privacy (as you should). I honestly don't know of any OSS open weight models from the US labs as good as Kimi K3 or Deepseek V4 though.
- genxy 2mo ago
  At least you get based models back at some point. You supply data, they supply compute and open weights.
- anigbrowl 2mo ago
  I will! I pay their sales too and consider it quite reasonable.
- 2mo ago

dnhkng 2mo ago

DeepSeek V4 Flash (Preview → 2026-07-31) • Terminal Bench: 56.9 → 82.7 (+25.8) • Toolathlon: 51.8 → 70.3 (+18.5) Compared to GPT-5.6 Terra: • Terminal Bench: Flash 82.7 vs Terra 78.4 • Toolathlon: Flash 70.3 vs Terra 53.1 • DeepSWE: Flash 54.4 vs Terra 69.6 • Agents' Last Exam: Flash 25.2 vs Terra 50.4 Trading blows with Terra, which is pretty interesting. No clear winner on these benchmarks, and wildy differeing scores. Very interesting!

Iolaum 2mo ago
Since they did this with their own harness I m not sure it's apples to apples comparison.
- NitpickLawyer 2mo ago
  > not sure it's apples to apples comparison. They're literally comparing the previous version of the same model with the new one. It's based on the same architecture, same pre-trained model, just different post-training. It doesn't get more apples to apples than this.
  - dnhkng 2mo ago
    I think the commenter means the Flash vs Terra benchmarks.
    - NitpickLawyer 2mo ago
      Ah, my bad. Yeah that makes sense. They do say "The official V4-Flash natively supports the Responses API format and is specifically adapted for Codex.", so at some point someone will make a "same harness" comparison.
- dnhkng 2mo ago
  It will be fair if they release the harness though. I think now the future will be paired model-harness releases, not just weight dumps. The performance changes are so big with the right harness that is makes sense to engineer the harness and fine-tune the model to one another from the start.

NitpickLawyer 2mo ago

This is more exciting than k3, IMO. Dsv4 models are extremely cheap to serve. Improving their capabilities has lots of downstream effects, as it becomes "good enough" for more and more tasks. DS was serving the pro version at extremely low prices for a long time, and they've had integrations with opencode & other providers, so they likely gathered a lot of data from real developers doing real tasks (on openrouter they were labeled as such). Now they can use those live scenarios to further post-train their models and improve them further. Can't wait to see if distilling k3 into dsv4 brings additional improvements. Anyway, having fast cheap models getting better is great for the community. Especially since these don't "go away" on a provider's whim. Whatever capabilities they get, can be used "forever" going forward. And, at least flash can be ran "at home" with <10k in hardware, which isn't really possible / feasible with glm/k3 larger models.

dnhkng 2mo ago
Totally! This with DwarfStar delivers usable local AI (I hope!)
- dannyw 2mo ago
  Usable local AI has been here for a while, esp on say a 5090. You can’t treat Qwen3.6 like its fable, but if you prompt precisely and specifically it’s a great executor. I actually found it refreshing to use more of my brain for once, and actually have to think deeper about what I’m trying to do, and how to build it.
- Tepix 2mo ago
  What are your goalposts? Depending on your requirements, there have been many moments of usable local AI. More recent ones were gpt-oss 120b and Qwen 3.6 27b.
- genxy 2mo ago
  Parent is referring to https://github.com/antirez/ds4 https://github.com/antirez/ds4
KaseyKim 2mo ago

spwa4 2mo ago

In case people want to run it, it's DeepSeek-V4-Flash-284B-A13B. So it should just barely run on a single B300, and it's small enough that it'll barely run on an M5 Max too.

wolttam 2mo ago
It runs really well on 2 DGX Sparks - 60t/s
- Tepix 2mo ago
  Yes, the Dual DGX Spark looks like the sweet spot for this model for now. Good preprocessing speed. Lots of context. Fast enough for 1-5 devs perhaps. Around 8200€ as of today (used to be 6000€). Dual Strix Halo is much slower and current Macs with 256GB are both slower and more expensive (Mac Studio M3 Ultra 256GB around 12000€). To get something faster than the two Sparks you'd need to spend more than $22000 for a server with 2x RTX Pro 6000 at $10000 each. Beyond that you could get 2x AMD MI350P.
arjie 2mo ago
Not yet, right? That's the old DS V4 preview release. We're still waiting for the weights to come out.
- benjiro29 2mo ago
  Probably the same. When the same base model is trained, the weight do not tend to change a lot. GLM 5.0 > 5.1 > 5.2 are the same base model, that just kept being trained. Weights hardly change as a result. Think in the like few percentage points size difference.
  - deleted 2mo ago
    [deleted]
lukan 2mo ago
"it'll barely run on an M5 Max " The max version I could order now with 128 GB? If so, the price for local inference would be 12 000 € vs 500 000 € for a B300.

deleted 2mo ago

[deleted]

nickandbro 2mo ago

I wouldn't doubt GPT 4.6 Luna being in the top left quadrant's center on the Cost per Intelligence Index is not concerning for Liang Wenfeng. You have to remember DeepSeek v4 flash even though a bit cheaper, does not have vision abilities, which is a big draw for agentic tasks. I admire DeepSeek's openness, but even they have been raising prices after their discounts.

minraws 2mo ago
They haven't raised prices though the plan was to increase it with peak hour usage for V4 Pro GA release, they didn't do that, so no price increases there I believe. As for vision yeah it sucks but Luna is also 2x input and 1.5x output for 1M context... That's around 0.4 in/1.8 out DSv4 is wayyy cheaper. And it's open now you have Luna at home if you have a decent set of GPUs you can run this on 2Sparks or one very expensive Mac or just like 6-8 5090s..
- minraws 2mo ago
  I know most folks can't afford it I am working on making it viable to rent shared hosting the biggest issue is data leak and prompt injection attacks with shared hosting. (Since the server owner connects to your main system via the coding agent) I guess using a ZDR provider is good enough for now.
dudisubekti 2mo ago
Gpt 5.6 Luna cache read is $0.02 per mtok V4 flash cache read is $0.0028 per mtok That's not "a bit cheaper", just saying
- nickandbro 2mo ago
  That's a good point. Yeah their caching input is insane.
  - ignoramous 2mo ago
    DeepSeek v4 API rates are only matched by Xiaomi's MiMo v2.5 series. Quite similar in capabilities too (at least before today's update).

wolttam 2mo ago

Hooray! This model makes me very optimistic about the future of local inference. The CyberGym score stands out to me.

ggcr 2mo ago

Woah, a 200B model competing with GLM-5.2 and getting close to Opus 4.8. Quite impressive. If those numbers translate well to its general capabilities, with the great caching DeepSeek has, I feel like this model will get tons of usage.

lostmsu 2mo ago
Not just 200B model, it is only 160GiB.
ignoramous 2mo ago
MiniMax's another lab that's known for relatively smaller models (their latest, M3 is 295b) that punch way above its weight.

KronisLV 2mo ago

Wonder how good the proper version of V4 Pro will be. I'm still considering pulling the trigger on the annual subscription of Kimi for K3 but it's sometimes slower than I'd like (at least when compared to Anthropic) even on their Vivace plan, and the token limits on the GLM Coding subscription for GLM 5.2 were too easy to hit.

tosh 2mo ago

[dead]

arjie 2mo ago

Oh my goodness what an update. I need these weights. It's an incredible model for the size. The improved tool calling etc. should be able to make my harness way simpler. This runs at mega-speed on prosumer hardware (2x RTX Pro 6000).

amunozo 2mo ago
How many tok/s are we talking about?
- arjie 2mo ago
  The old one was 160 tok/s. With DSpark it’s like 250 tok/s or higher. I don’t recall from tbe last time I was looking. You can turn on farther drafting and get more.

Goranek 2mo ago

Kimi K3 (instead of Opus) for expensive stuff, DSV4 Flash for tasks (instead of Sonnet)? Does this make sense?

geek_at 2mo ago
it does! I'm always amazed when I use DSV4 flash for coding or server checks and after an hour of working with it my (pure api call) balance is about 30 cents
baalimago 2mo ago
Looks like they will release an updated version of deepseek-v4-pro soon, which most likely will beat kimi k3 at both intelligence and cost (judging by the vast improvements to dsv4 flash)
try-working 2mo ago
[flagged]

wkcheng 2mo ago

If the benchmarks are real and reflect actual use, then this is an insane model. This 300B model outperforms the previous DS4 Pro preview model (1.8T params), and it looks like it outperforms GPT 5.6 Luna too. And it's still cheaper than Luna, even with the price decrease. Crazy.

cbg0 2mo ago
On DeepSWE Deepseek is 54.4% and Luna is 67%
- benjiro29 2mo ago
  But on Terminal bench, its * DS4 Flash: 82.7 * GPT 5.6 Luna: 75.7 For reference, that puts it on the third spot behind GPT 5.5 and Fable 5. For some reason GPT 5.6 Sol is not showing in the leaderboard. If it did, then DS4 Flash was number four. The thing is, even if Luna is better in DeepSWE and has the 80% discount. DeepSeek is still cheaper. -------------- DeepSeek V4 | Flash GPT-5.6 Luna (New) -------------- Input (Cache Hit) $0.0028 $0.02 Input (Cache Miss) $0.14 $0.20 Output $0.28 $1.20 -------------- Both Luna and Flash are heavy on the reasoning > output. And the cache hitrate + prices also matter. Reality is, you can not go wrong with Luna or Flash at those prices. And remember, DeepSeek V4 Pro is still in the rafters, what is ironically closer to Luna's new price.
  - flashblaze 2mo ago
    Agreed. The only thing missing is multimodal capability
gr_norm 2mo ago
OpenAI must've known this was coming, hence the Luna price drop. This competition is amazing!

egeozcan 2mo ago

Every time I want to have fun coding something with natural language processing, I use deepseek flash. It's just incredible for the price. I have a fairly popular app with 400 users that uses DeepSeek in the background and it still didn't hit even 50 bucks of usage in a month.

indigodaddy 2mo ago
Mind sharing the name? Sounds interesting.

try-working 2mo ago

Let's see how the market reacts.

flysoft 2mo ago

Finally have a model with usable intelligence, at a reasonable price. Can't imagine what Pro GA would look like, considering pro preview has only 1.6t parameters.

thirtygeo 2mo ago

For both US and China models - what standard security checks and QaQc are you all doing? We're running small gamuts to test for unsolicited jailbreaks (model jailbreaks you) and incorrect records (Fake Accuracy - as Easter Egg or common thread) meaning falsified logic or information cooked in by the developers, rather than the training data speaking for itself

PhilippGille 2mo ago

The previous V4 version wasn't called “Preview” by most inference providers. For example, the OpenRouter model slug was `deepseek/deepseek-v4-flash`. So now there will be confusion when someone talks about V4 Flash or when someone offers V4 Flash inference. Why not call it V4.1?

try-working 2mo ago
DeepSeek themselves called it `deepseek/deepseek-v4-flash`. Pro is still like that.
- PhilippGille 2mo ago
  Yes that's my point. The old and the new version are different in capabilities, but now when someone talks about DeepSeek V4 Flash (in benchmarks, on inference providers), you don't know which exact version it's about. Some providers like OpenRouter now call it `deepseek-v4-flash-0731`, but even in places like here on HackerNews people say things like "Sonnet is better than DeepSeek" without specifying a version or a reasoning effort, certainly no one will mention that `-0731` suffix when talking about DeepSeek V4 Flash.
  - benjiro29 2mo ago
    I think it does not matter. Most people who use these types of models are into the IT world, and will know/be informed very fast that there is a difference. People will likely also use the 0731 behind it. The only issue i see, is 3th party providers that have not yet updated. But that is going to be a short time periode. There is no reason to not update.
petu 2mo ago
It probably would be called 'deepseek-v4-flash-0731' in API edit: nope, at least deepseek kept "deepseek-v4-flash" and just updated model underneath. I guess preview is no longer worth serving with that release and you'd have to look through inference provider docs to see if they've updated, yeah..

baalimago 2mo ago

Very promising. So it will both keep the speed and reduced price, yet exceed performance of the quite sufficient deepseek-v4-pro? Should be extending the lead in intelligence/cost index, as deepseek-v4-flash already were the most price efficient model, which now becomes even better. Although, in the deepseek APIs, the cost is leaking all information about codebases to China.

ilaksh 2mo ago
Supposedly better than GLM 5.2 according to at least one benchmark.

kamikazechaser 2mo ago

The flash variant is on par with Sonnet 5 on DeepSWE (54%). Big, if true.

storywatch 2mo ago

How's their performance in English prose? We are currently searching for cost effective ways to keep story wikis up to date.

amunozo 2mo ago
I am interested in this too, as I think it could be these models are overly optimized for coding. Let me know if you figure it out!
- storywatch 2mo ago
  What's your use case? I will probably run some tests soon, stay tuned.

f311a 2mo ago

I've been driving flash model for 90% of my tasks. It's better than pro (for unknown reasons), very cheap and fast. I try to keep changes under 1000 lines and drive architectural decisions myself, barely notice any difference compared to frontier models. The rest 10% is to spot bugs, security problems and to investigate better architecture, which flash can also do pretty well, I just cross check it. Faster iterations are way better for me, I hate waiting for 5-10 minutes on small changes. I tried to use recent versions of Kimi and GLM, but they use too much thinking for no reason and are pretty slow because of it. I also often feed a lot of data to it, without worrying about hitting the limits: dependencies (to find bottlenecks in them), logs, performance dumps and so on. Also, it will never complain about security guards, I've been using it to reverse engineer binaries.

regularfry 2mo ago
It's good but (at least on openrouter) it's got an annoyingly tight output token limit. So if it does get stuck in a reasoning pit, it won't work its way out of it in time. It's replaced the Kimi models for me though.
- u8080 2mo ago
  Try to use DS platform directly - cheaper and better than openrouter, no subscription
  - dghlsakjg 2mo ago
    Openrouter has cheaper inference than deepseek for the prior version of v4 flash, which I suspect will happen within a day or two with this version, and they don’t offer subscriptions. Are you confusing it with opencode?
    - u8080 2mo ago
      No, maybe I've checked too much time ago, but direct DS was cheaper for all versions - also I had issues with openrouter providers availability

miyuru 2mo ago

Judging by the openrouter leaderboard ranking for today, it looks like Dv4F us more popular than mimov2.5. https://openrouter.ai/rankings?view=day#leaderboard-table https://openrouter.ai/rankings?view=day#leaderboard-table These days cost per task is more important, and SOTA models have become expensive.

benjiro29 2mo ago
MiMo, the overlooked sidekick to the hero. Will be interesting to see what Xiaomi bring to the table. These massive jumps in cheap models, is really great times!

ra 2mo ago

What's the best way to run this on a 64GB M2 Pro?

petu 2mo ago
Weights are yet to be released (maybe in 24H, Deepseek has track record of releasing same day). https://github.com/antirez/ds4 https://github.com/antirez/ds4 is often mentioned for DS4F on Mac, but 64GB is likely not enough to achieve reasonable speeds (official weights should be ~160GB).
Tepix 2mo ago
DS4Flash has 284B weights. 64GB? No go.
- zozbot234 2mo ago
  The native weights are 4-bit for the sparse experts, and they quantize to ~80GB with limited degradation in real-world performance. That's a viable target for 64GB with SSD streaming, though it will be slower than keeping the whole thing in RAM (especially on a M2-class machine with its slower storage).
  - Tepix 2mo ago
    I consider less than 4bit to be too poor quality usually. Got any benchmarks to measure quality?

lionkor 2mo ago

I use deepseek for a lot of my personal day-to-day agent needs, and I will simply put this here and let this speak for itself, last 30 days: - Cost: $4.55USD - API requests: 3,467 - Tokens: 323,183,886 And as an engineer who leads a small team, I have very high standards for quality, and these carry across to my personal projects where I use deepseek. It has not disappointed at all for coding or review tasks. For everything else, use another model.

innis226 2mo ago
But doesn't it hallucinate a lot? Does that affect your workflow?
- lionkor 2mo ago
  It hallucinates plenty, about the same as Codex models and all other LLMs! I review all code it writes, thoroughly, check the test coverage, write tests myself, have other models/chats cross-check the work with a review skill (which I've shared in another comment in this thread). Usually unreviewed code only gets committed if I really don't care, like for one-off scripts, which I sandbox with github.com/lionkor/sbh or run as an unprivileged user.
dakolli 2mo ago
[flagged]
- ncphillips 2mo ago
  For doing what?
  - dakolli 2mo ago
    everything.
    - hlynurd 2mo ago
      There's a small relief in knowing that these junk comments are at least not AI generated (in all likelihood.)

kmarc 2mo ago

Essentially I'm running everything on flash now inside pi. With the correct set of MCP servers, context reducer tooling and skills it can implement any task I throw at it. Some sessions take 30+ turns, but it's fast and cheap; all this in an hour, with ~$0.5 cost. (TBH though, in my multi-subagent workflow I do use other, more expensive models for planning, reviewing, oracle-ing) I haven't used our slow opus subscription for weeks. (Also set up an OpenWebUi self-hosted chat that works from my phone, has some mcp and skills. fully replaced perplexity. Monthly cost ~$18 for hosting and subscriptions)

peperunas 2mo ago
Do you have any recommendations of such extensions for pi?
- try-working 2mo ago
  pi-role-model
- kmarc 2mo ago
  Recommendation? No. Just go with the passive-aggressive advice "let pi build it for you". :-) To be more constructive, what I did (as an experiencd SWE but a complete noob to agentic coding): went to pi.dev's extension marketplace and looked into all the new shiny stuff. Subagents, mcps, context and memory optimizers, skills. Using the most popular ones (not necessarily the best ones) It was like 15years ago learning the new mindset of vim (and spending a ton of time to customize it to my workflow). My understanding is that Claude and opencode doesn't give you this flexibility. Learning all these stuff drove me to also set up openwebui, and it was such a successful private project that I implemented it at work (with jira/confluence/bazel query access) and management said "we need this by tomorrow". I believe the models matter not that much anymore. The "harness" does. (unless you just want to vibe code. Thebn, throw crap at fable and call it a day)
  - peperunas 2mo ago
    Got it :-)

vladukha 2mo ago

Where do you guys get deepseek? I'm hearing a lot of good reviews and want to try it with my pi config. from the deeepseek themselves, openrouter, or anywhere else? does it make a difference? [edit]: whoa it is really fast. will take some time to evaluate quality thou

Gigachad 2mo ago
I used it through openrouter. Plugged in to the vs code copilot bring your own key thing. Played around for a few hours and used up 80 cents of tokens.
- Lalabadie 2mo ago
  Anecdotal data from my own tests: allow only one provider if you want good cache usage on OR. 80 cents is probably 4x the price you should have paid. Providers' cache hit stats are available to consult, and only 1-2 of them behave properly if I remember correctly, zero if you request providers that don't store and train on sessions.
psibi 2mo ago
I've been using DeepSeek directly. I've heard from colleagues that using it via OpenRouter is slower, but I'm not so sure about that.
embedding-shape 2mo ago
For hosted APIs, it's a lot cheaper to use their own infra, caching seems a hell of a lot better there compared to OpenRouter, and indeed the tok/s seems higher. They also have peak/off-peak pricing, so if you can hold off with your request, you get a pretty big discount. Otherwise, if you're trying to run it locally, even really low quantizations like DeepSeek-V4-Flash-IQ2XXS-w2Q2K-AProjQ8-SExpQ8-OutQ8-chat-v2-imatrix seem to actually not be so dumb compared to smaller models with same quantization, might be worth a try if you're sitting on a lot of RAM/VRAM yet not industry-scale amount :)
ticoombs 2mo ago
> does it make a difference Probably not. But Opencode-Go is a great solution for those who don't want to pay DeepSeek directly (or can't due to reasons) Selfish referral code: https://opencode.ai/go?ref=R1AJZT4VBX https://opencode.ai/go?ref=R1AJZT4VBX

f6v 2mo ago

I'm thinking of using ChatGPT for making plans and V4-Flash for execution. Does anyone have good advice on pairing different models?

embedding-shape 2mo ago
Pairing non-APIs with APIs tend to be a hassle, and risky, as usually that breaks the ToC. I guess easiest for you to test if it's worth using the OpenAI API, is to manually copy-paste responses between wherever you run V4-Flash and the ChatGPT UI. What I've done in the past is basically .zip up the entire project directory, ignoring files from .gitignore, then asking ChatGPT Pro to inspect that and come up with a plan, then you paste that to where you have V4-Flash. Basically how we did "vibe pair programming" before the TUI agent harnesses appeared in the ecosystem :)
- yuzuquat 2mo ago
  reminds me back in the day when we used to do version control with google drive. you generally don't need to do this anymore i don't think. it should be fairly trivial to open the codex cli in the project directory, ask it to do some analysis and planning -> save to md. then opencode with deepseek to read that md and start implementing. consider that some cross-model subagent workflows already exist: i use claude/fable to plan and there are openai plugins to directly spin up codex subagents. this latter approach gives claude/fable more directly control to babysit the codex agents whereas the former is more of a clearcut handoff
  - embedding-shape 2mo ago
    That approach won't give you access to the "Pro Mode" nor "Deep Research" though, which if you're paying for a Pro subscription already, "Pro Mode" is probably the top-top when it comes to "extensively researched answers & plans" across the entire ecosystem. That said, I do ask it to produce a .md plan that later is used with agents :)
- f6v 2mo ago
  [dead]

Havoc 2mo ago

>benchmark results far exceeding V4-Pro-Preview: Wow that's crazy Good times for those that don't need strict data protection

blackoil 2mo ago
These being open provide much better data protection.
kzrdude 2mo ago
Open weights means that there is a free market on providing inference using this model. Some of them will offer good data protection. (Well, hopefully)

sim04ful 2mo ago

Why didn't they increment the version as atleast a patch update

markasoftware 2mo ago
They want to be the next Google it seems
kzrdude 2mo ago
Yes, and even if they seem to have updated endpoints in place they should assign the service a version number.
rubslopes 2mo ago
I was also so annoyed by this. It makes communication all around difficult. Why don't they simply call it 4.1 flash?
crvdgc 2mo ago
My guess would be the version number tracks the architecture change, not the weight change.
deleted 2mo ago
[deleted]
bel8 2mo ago
So whoever is using DeepSeek V4 flash gets a massive upgrade without having to change any config.
- sim04ful 2mo ago
  That's an absolutely terrible idea for any non-trivial project consuming it.
  - behindsight 2mo ago
    Wasn't it stated as being in "preview" prior to this? If implementing non-trivial tasks on a preview model surely there is some anticipation of it not being the final stable release? Unless you mean they should have appended a "preview" suffix on the endpoint for extra good measure?

sourcecodeplz 2mo ago

i've made a comparison between this and GPT Luna (recent %80 price drop) https://x.com/SourceCodeplz/status/2083099712760987746 https://x.com/SourceCodeplz/status/2083099712760987746 i prefer GPT-5.6 Luna honestly

mordae 2mo ago

I was just using it when it landed. It started reasoning more extensively from nowhere and precision went up a lot. It also changed its prose style for the better. Looking forward to weights.

nathaah3 2mo ago

DS v4 flash has been my goto model for tasks in work. its been unsurprisingly fast and cheap.

throwaw12 2mo ago

how different is their harness from Pi coding agent harness, is it possible to make an extension for Pi which can implement deepseek harness?

sqemo 2mo ago

DeepSeek is great for tasks and software I already know well. Even if it gets something wrong, I can usually verify it myself. But when I'm working with a programming language I'm not familiar with, I prefer using Codex or Claude.

k__ 2mo ago
Yeah, it needs quite some hand holding. I didn't do much agent coding and had a mix experience. 1. It would build something that was in the spirit of what I wanted, but unusable in practice. 2. It would build something quite useful, but only the public APIs were nice, the deeper code layers would get more and more convoluted. 3. It would built what I wanted and it would have okay-ish code. However, for 3. I also had to add a custom AGENTS.md, many more code example, extra repos as subtrees, and review any code that had new concepts. Much more work, but still much less than typing it all by hand.

truth_seeker 2mo ago

The magic of post training with valuable dataset

dakolli 2mo ago

Chinese labs rushing to release models this week, because it's inevitable that Washington regulates Chinese models in the next 4 weeks. All the US AI leaders have been taking trips to Washington this week, what do you think they're there for..

k__ 2mo ago

I'd take more throughput while everything else stays the same.

znnajdla 2mo ago

The conspiracy theorist in me wants to think that the 80% drop in GPT 5.6 Luna prices today is correlated with this update from DeepSeek. Perhaps OpenAI has already hacked its competitors with it's Mythos-like models and is aware of what competitors are doing and is able to react in advance.

nchmy 2mo ago
Seems to me that it's the reverse. Open ai dropped prices to compete with deepseek etc and then deepseek released this update to negate Luna.

mekky16 2mo ago

if they were anthropic they wouldve just released it as a new model

yewenjie 2mo ago

What was preventing them from calling it v4.1-Flash to distinguish it better?

lionkor 2mo ago
Sounds like it'll replace v4-flash, v4.1 would be nice to keep both available. On the other hand, it's nice to just get an improvement on anything that asks for "deepseek-v4-flash" without having to change the model string.
- krapht 2mo ago
  I think that's backwards. Anything that changes the performance of a model deserves a minor version bump. A new model has to be qualified before being pushed to production; but we don't get the choice here, just cross your fingers there are no regressions at all on all possible tasks the model might be asked to do.
  - lionkor 2mo ago
    I should have worded it differently. Having a model selector as `string` seems like the wrong choice. At the very least, I should be able to select 4.X, like how we select dependencies, so people who rely on specific behavior can pin to 4.0 and I can say version >= 4 if I don't care.
  - halJordan 2mo ago
    That's on you for using a preview/beta. It was properly qualified when it was released. No one complains when ios goes from beta to release; even though it will be ios 27 beta -> ios 27 next month
  - xbmcuser 2mo ago
    its an open source model if it is important enough that you have to worry about a new version breaking something then why the fuck was that not running on your own servers this is not an Anthropic or OpenAI closed model that you only have access through an api

amelius 2mo ago

Note: if you are having success with a model, then please post what you are using it for. Writing HTML/CSS is very different from writing Rust/C++ or doing maths.

dandaka 2mo ago
Text classification, structured data extraction, rewrite
sparse-Matrix 2mo ago
I've been having better-than-most performance using qwen3.6 to write python/flask. I tried using it to generate some rust code yesterday, and it generated much code but only ever came within 1 error of a testable build. The 4th or 5th full rewrite is sitting in the buffer right now. I'm currently looking to up my game with Bottlecap AI's return of qwen3.6, 'thinking cap'. Alleged to be twice as fast and superior at coding over extended sessions (vs. 3.6). We'll soon see.
- ilaksh 2mo ago
  You should specify which model size and quant because there are many of both.
f311a 2mo ago
I do Python, Go and Rust. Go works the best, I would say Python is worse than Go. Rust works perfectly fine, but when I use Rust, I usually pay closer attention to performance, so I have to guide it a bit, to improve cache locality, use simd, avoid unnecessary allocations and so on. Terra has the same issues with Rust. If you always prompt models to achieve the best performance, the code is usually no the one that I want, they optimize unnecessary/cold parts or blindly optimize stuff where compiler takes care of the optimizations already. See my other comment for more information on how I work with it. In short, keep the changes under 1k lines, context under 120k (ask it to use subagents), drive the architecture yourself.
fdsjgfklsfd 2mo ago
I use DeepSeek V4 Flash (before this update) for most things: - OpenCode for codebase editing: python scientific computing and LLM projects - Open Interpreter Classic (python version) for Swiss army knife terminal replacement one-off task type stuff.

sparse-Matrix 2mo ago

This may come as a surprise to a lot of AI concerns, but I have -zero- interest in paying for a model.

Tepix 2mo ago
Why mention it? Just download the weights when they become available.
kzrdude 2mo ago
Then DS V4 flash is pretty relevant, because it's pushing prices down.. as well as being self hostable with a large enough rig.

Tepix 2mo ago

[dead]

Tepix 2mo ago

Sounds like a big improvement. No mention of weights, just API. When will the updated weights be released?

fdsjgfklsfd 2mo ago
Was already released before your comment: https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731 https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731

ilaksh 2mo ago

I wonder when the antirez/ds4 group will have an update to their high accuracy 2 bit quant. Although it's funny that I am thinking about that at all because I have a 2060 :P . My local inference is playing with Gemma 4 E2B and MiniCPM 5 1B.

throwdbaaway 2mo ago
Objectively speaking, the 2 bit quant from antirez has very low accuracy. Meanwhile, his 4 bit quant does have decent accuracy, but is a bit pointless by being bigger than the full precision MXFP4 quant. Anyway, they all work fine in practice.
jtbaker 2mo ago
Looks like a couple of people are already on it: https://github.com/antirez/ds4/issues/635 https://github.com/antirez/ds4/issues/635

HyperL0gi 2mo ago

Is anyone using DSv4 for their agents that is not related to writing code? Curious about use cases specially for someone using gpt-5.4 mini for classification, categorization, etc

freakynit 2mo ago
I use it to conduct thorough online researches. Plug-in some online search MCP (like the one I use: https://jerrysniffs.online https://jerrysniffs.online ), and the flash models dig through the internet for dirt cheap.. Most of the times, the total cost, including search API's, is less than $0.05 for full deeply researched output, and the research is actually good.
Lalabadie 2mo ago
It's been good for one-off cases in my limited experience. I would describe its behaviour as Sonnet-shaped, if that makes sense to you. Good answers but it often decides to reason a lot about simple things before getting to an output. At the speed Flash has on most providers, it doesn't really turn into a latency concern.
markab21 2mo ago
We use it at a moderate scale, self-hosted on B300 hardware. It's great :D QA analysis of voice transcriptions. Napkin math: we operate at 2-5% of the cost of running on Equiv Frontier, though this changes near-weekly because pricing is so volatile. It took us about a month to get the inference configured to achieve these numbers. But if you can get your hands on a pair of B300 GPUs and the context works, it's untouchable for price/performance. (B200 would work, but you don't have the B300's memory, which lets you run it on 2xGPU instead of 4xGPU... with Dspark, it's like magic) On a side note, for tasks that don't require the intelligence of DS v4 flash, we're using Nemotron-3-super with incredible success. I'm shocked we're not seeing more adoption of this model, given how easy it is to fine-tune and how blisteringly fast the nvfp4 version is. (A single B200 GPU can produce an insane amount of throughput with Nemotron 3 Super.)

XCSme 2mo ago

Can't really use it now, without giving away your data: > Trains: this provider may use prompts for training and may retain prompt data.

Philpax 2mo ago
That will cease to be a problem in the next 24 hours, now that the weights are out: https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731 https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731

alecsm 2mo ago

I've been using DeepSeek Pro for a while and Flash only for certain dumb tasks where I only need the speed of a LLM and not big brains. I find the newest OpenAI and Anthropic models to be way better for big tasks that require many decisions but I don't like that anyway because I lose track of what's being done. Knowing what I want for every prompt makes DeepSeek Pro the best LLM for me. It allows me to work relatively fast at a very low price.

sreekanth850 2mo ago

how this compare to luna high with reduced pricing.

throwa356262 2mo ago

Gentlemen, start your DGX Sparks https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731 https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731

namuol 2mo ago

Can someone please explain how these models aren’t just fine tuned for benchmarks? I’m not plugged in to this space much but it seems like such an obvious problem…

sroerick 2mo ago
They definitely are - but also people are using them pretty extensively for work. So ultimately you can't really fake "is it good". But there's no real measurements of that when a model is released, so we are stuck with benchmarks.
- namuol 2mo ago
  I will continue to ignore the benchmarks.

wg0 2mo ago

Don't know about the bench marks but I am getting Opus 4.7 level performance at fraction of cost with DeepSeek V4 Flash set to high. It is a reliable workhorse.

w2seraph 2mo ago

This made my day !

troglodytetrain 2mo ago

This is very exciting, my own niche micro-saas has already been able to make heavy use of DeepSeek-V4-Flash for my use case, I am looking forward to seeing how performance improves.

heyalexej 2mo ago

Long story, I have humongous zai GLM 5.2 token budget that I'm using in a similar fashion as many comments explain here. GPT 5.6 or Fable 5 for planning, GLM for implementing, researching, extracting and many other tasks I consider grunt work. Very happy with the performance, speed isn't all that good though. I'd be curious to hear from someone who works with both, DeepSeek and GLM side by side.

prtmnth 2mo ago

Eagerly awaiting their V4 Pro update!

sebjones 2mo ago

The cost is amazing! So DSV4 Flash is not multi modal right? How do you use it to review UI work I wonder? Im doing a lot of frontend work. I wonder how it review its own work.