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Qwen3-4B-Thinking-2507
- Demiurge 1y agoI've been trying this today, and I'm getting a lot of hallucinations for suggestions. However, the analysis of problems really quite good.
- gok 1y agoSo this 4B dense model gets very similar performance to the 30B MoE variant with 7.5x smaller footprint.
- smallerize 1y agoIt gets similar performance to the old version of the 30B MoE model, but not the updated version. https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507 https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507
- Imustaskforhelp 1y agoI still think that its still very commendable though. I am running this beast on my dumb pc with no gpu, now we are talking!
- esafak 1y agoThis one should work on personal computers! I'm thankful for Chinese companies raising the floor.
- johndhi 1y ago[flagged]
- redman25 1y agoI’m American. Just giving some background to the feeling. There’s some discontent with some western communities (localllama) that Chinese developers have been open weighting all of their models while most western models have been closed weights.
- evilduck 1y agoMeta seems to have now stepped out of the running despite being the local LLM catalyst. Anthropic has done nothing. IBM's Granite and Microsoft's Phi are both very far behind. AWS doesn't even attempt to compete. Grok failed to make good on their promise. OpenAI only even entered the game yesterday so it's hard to tell if they're actually serious since they released such an overly censored model that isn't really better than Qwen options and at its smallest still requires a decent computer. Google seems to be the only domestic contender on the level of what Chinese companies are doing and they're being very careful to not cannibalize Gemini with Gemma. Right now though China is dropping huge improvements across the entire spectrum of model sizes with Qwen, Kimi, DeepSeek, GLM, and Yi. We've also got Mistral doing competitive self-hosted models too, but they're French. Local AI tooling is plainly _not_ being driven forwards by the United States.
- Workaccount2 1y agoChina has a business model where you can lose money and it doesn't matter. The state's modus operandi is just fund things until the leader changes his mind about it. This is why the Chinese labs are so open, they don't ever need to make a profit, they just need to make good AI.
- whimsicalism 1y agoSure, except all of these Chinese labs are attached to large, profitable Chinese tech & finance companies. But yeah, it's all unfair competition.
- Workaccount2 1y ago
- thatwasunusual 1y agoLet's say any country create the most powerful - and thus best - LLMs. They over time infiltrate it with their political will. Over 20-30 years, I'd imagine people asking those LLMs will have their minds' shifted. But. That's just me, my pessimism-sci-fi scenario.
- whimsicalism 1y agoindividualized recommendation systems are enough to drive everyone nuts
- Imustaskforhelp 1y agoI think that just as how perplexity had actually created a deepseek(fine-tune?)[1], then there is more and more incentive towards making uncensored models though I am gonna be honest, Kimi K2 isn't that censored but I tried the gguf variant of this model on local pc and it definitely is censored / biased towards china (like taiwan is part of them and so on) But still, the most recent version of american foss model gpt-oss is just so filled with censorship that its just not worth it in the name of "safety", so to me both are doing censorship but I'd much rather use chinese censorship since its only censored on chinese topics and I mean, I personally wouldn't be ever asking chinese models chinese questions but maybe that's just me. And even if I would, I would probably ask it on some uncensored, in fact I was actually thinking of creating a fine tune like the perplexity, or just this idea to break chinese censorship. I also think that some better idea needs to come up with multi modal approach so that censorship could be removed by mixing and matching american and chinese models, I do think it is far from reality but I read a recent comment about harmony which gpt-oss uses and it does look promising I am not sure. [1]: https://huggingface.co/perplexity-ai/r1-1776 https://huggingface.co/perplexity-ai/r1-1776
- wkat4242 1y agoThe problem I've had with Chinese models is that when they get confused they revert to Chinese which is just gibberish to me of course. American models revert to English in those situations but that's fine for me. And models can be abliterated to remove the censorship. I use llama3 that way.
- whimsicalism 1y agoYou can see not from clicking on their name, I wouldn’t assume every positive comment about China is a ‘shill’ - there are many people unhappy with our current neo-cold war. Astroturf/shill accusations are also against the HN ethos. https://news.ycombinator.com/item?id=11257034 https://news.ycombinator.com/item?id=11257034
- frontsideair 1y agoAccording to the benchmarks, this one is improved in every one of them compared to the previous version, some better than 30B-A3B. Definitely worth a try, it’ll easily fit into memory and token generation speed will be pleasantly fast.
- GaggiX 1y agoThere is a new Qwen3-30B-A3B, you are compare it to the old one. https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507 https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507
- tolerance 1y agoIs there like a leaderboard or power rankings sort of thing that tracks these small open models and assigns ratings or grades to them based on particular use cases?
- esafak 1y agohttps://artificialanalysis.ai/leaderboards/models?open_weights=open_source&size_class=tiny%2Csmall https://artificialanalysis.ai/leaderboards/models?open_weigh...
- cowpig 1y agoCompare these rankings to actual usage: https://openrouter.ai/rankings https://openrouter.ai/rankings Claude is not cheap, why is it far and away the most popular if it's not top 10 in performance? Qwen3 235b ranks highest on these benchmarks among open models, but I have never met someone who prefers its output over Deepseek R1. It's extremely wordy and often gets caught in thought loops. My interpretation is that the models at the top of ArtificialAnalysis are focusing the most on public benchmarks in their training. Note I am not saying XAI is necessarily nefariously doing this, could just be that they decided it's better bang for the buck to rely on public benchmarks than to try to focus on building their own evaluation systems. But Grok is not very good compared to the anthropic, openai, or google models despite ranking so highly in benchmarks.
- GaggiX 1y agoClaude Opus is in the top 10, also people via OpenRouter mostly use these models for coding and Claude models are particularly good at this, the benchmark doesn't account only for coding capacities tho
- byefruit 1y agoThe openrouter rankings can be biased. For example, Google's inexplicable design decisions around libraries and APIs means it's often worth the 5% premium to just use OpenRouter to access their models. In other cases it's about which models particular agents default to. Sonnet 4 is extremely good for tool-usage agentic setups though - something I have found other models struggle to do over a long-context.
- jampa 1y agoI am reading this right, is this model way better than Gemma 3n[1]? (For only the benchmarks that are common among the models) ===== LiveCodeBench E4B IT: 13.2 Qwen: 55.2 ===== AIME25 E4B IT: 11.6 Qwen: 81.3 [1]: https://huggingface.co/google/gemma-3n-E4B https://huggingface.co/google/gemma-3n-E4B
- meatmanek 1y agoReasoning models do a lot better at AIME than non-reasoning models, with o3 mini getting 85% and 4o-mini getting 11%. It makes some sense that this would apply to small models as well.
- film42 1y agoIs there a crowd-sourced sentiment score for models? I know all these scores are juiced like crazy. I stopped taking them at face value months ago. What I want to know is if other folks out there actually use them or if they are unreliable.
- nurettin 1y agoThis has been around for a while https://lmarena.ai/leaderboard/text/coding https://lmarena.ai/leaderboard/text/coding
- klohto 1y agoopenrouter usage stats
- esafak 1y agohttps://openrouter.ai/rankings https://openrouter.ai/rankings The new qwen3 model is not out yet.
- setsewerd 1y agoSince the ranking is based on token usage, wouldn't this ranking be skewed by the fact that small models' APIs are often used for consumer products, especially free ones? Meanwhile reasoning models skew it in the opposite direction, but to what extent I don't know. It's an interesting proxy, but idk how reliable it'd be.
- matznerd 1y agoAlso, these small models are meant to be run local so not going to appear on openrouter...
- hnfong 1y agoBesides the LM Arena Leaderboard mentioned by a sibling comment, if go to the r/LocalLlama/ subreddit, you can very unscientifically get a rough sentiment of the performance of the models by reading the comments (and maybe even check the upvotes). I think the crowd's knee-jerk reaction is unreliable though, but that's what you asked for.
- svnt 1y agoIt is interesting to think about how they are achieving these scores. The evals are rated by GPT-4.1. Beyond just overfitting to benchmarks, is it possible the models are internalizing how to manipulate the ratings model/agent? Is anyone manually auditing these performance tables?
- nisten 1y agoIf you want to have an opinion on it, just install lmstudio and run the q8_0 version of it i.e. here https://huggingface.co/bartowski/Qwen_Qwen3-4B-Instruct-2507-GGUF/tree/main https://huggingface.co/bartowski/Qwen_Qwen3-4B-Instruct-2507.... you can even run it on a 4gb raspberry pi Qwen_Qwen3-4B-Instruct-2507-Q4_K_L.gguf https://lmstudio.ai/ https://lmstudio.ai/ Keep in mind if you run it at the full 262144 tokens of context youll need ~65gb of ram. Anyway if you're on mac you can search for "qwen3 4b 2507 mlx 4bit" and run the mlx version which is often faster on m chips. Crazy impressive what you get from a 2gb file in my opinion. It's pretty good for summaries etc, can even make simple index.html sites if you're teaching students but it can't really vibecode in my opinion. However for local automation tasks like summarizing your emails, or home automation or whatever it is excellent. It's crazy that we're at this point now.
- Aeroi 1y agohow about on apple silicon for the iphone
- jasonjmcghee 1y agohttps://joejoe1313.github.io/2025-05-06-chat-qwen3-ios.html https://joejoe1313.github.io/2025-05-06-chat-qwen3-ios.html
- esafak 1y agoThank you. To spare Mac readers time: mlx 4bit: https://huggingface.co/lmstudio-community/Qwen3-4B-Thinking-2507-MLX-4bit https://huggingface.co/lmstudio-community/Qwen3-4B-Thinking-... mlx 5bit: https://huggingface.co/lmstudio-community/Qwen3-4B-Thinking-2507-MLX-5bit https://huggingface.co/lmstudio-community/Qwen3-4B-Thinking-... mlx 6bit: https://huggingface.co/lmstudio-community/Qwen3-4B-Thinking-2507-MLX-6bit https://huggingface.co/lmstudio-community/Qwen3-4B-Thinking-... mlx 8bit: https://huggingface.co/lmstudio-community/Qwen3-4B-Thinking-2507-MLX-8bit https://huggingface.co/lmstudio-community/Qwen3-4B-Thinking-... edit: corrected the 4b link
- ckcheng 1y ago