mekpro

7 ms·

1.
by mekpro 1mo ago
It’s interesting in terms of the economics of development. This product takes advantage of advancements in lithium-ion battery technology driven by phones and cars, benefiting from improvements in both performance and cost at scale without
2.
A Programming Paradigm for Spatiotemporal Composability(github.com)
3 points by mekpro 1mo ago|0 comments
3.
by mekpro 1mo ago
why so much hate on this ? Meta releases open Model and it is competitive and confirms the direction, what could we ask more !!
4.
SWE-1.7 Reach Near GPT 5.5 and Opus Intelligence(cognition.com)
272 points by mekpro 2mo ago|139 comments
5.
by mekpro 3mo ago
codex spark is not large model though, much weaker than standard model.
6.
by mekpro 3mo ago
We need more coding benchmark score. Not sure that winning terminalbench 2.1 alone is a clear win over Fable/Mythos yet.
7.
by mekpro 3mo ago
source ?
8.
by mekpro 3mo ago
API server is not hard problem and not make sense for indefinite postpone. I think the more likely explanation is model quality. Too bad for Meta, and very sad day Llama.
9.
Meta Keeps Delaying the Release of Its New AI Model to Developers(wsj.com)
67 points by mekpro 3mo ago|26 comments
10.
by mekpro 4mo ago
The technical report is very detailed and would 'reinforcement learning' of future researchers, Thanks Microsoft!
11.
by mekpro 4mo ago
Yes, 300 MW from SpaceX helps a lot, but I think that’s mainly to support Opus demand, which has grown faster than expected. If Mythos is roughly 5× more expensive to serve than Opus, as the pricing suggests, then 300 MW is nowhere near eno
12.
by mekpro 4mo ago
It’s clear that Anthropic has run out of the compute capacity needed to serve Mythos publicly. They’re using security concerns to mask their inability to deliver the model at scale, while still trying to maintain their lead over OpenAI. As
13.
by mekpro 7mo ago
Opus is definitely in its own league. I use Kimi/Gemini-cli code regularly to save cost and from my experience, Kimi 2.5 is more solid than Gemini Flash 3.0 for coding. While Gemini Flash 3.0 is generally faster, it usually break the s
14.
by mekpro 8mo ago
Except that, In OpenRouter, Deepseek always maintain in Top 10 Ranking. Although I did not use it personally, i believe that their main advantage over other model is price/performance.
15.
by mekpro 8mo ago
I think the opposite. Having NVIDIA investing in TSMC's bleeding-edge process node should benefit Apple rather than disadvantage. It means that Apple doesn't have to be sole investor in latest node development which is more harder
16.
by mekpro 9mo ago
They are so beautiful that i dont want any of these been stole by AI.
17.
by mekpro 10mo ago
How this improvement translate into real world agentic coding task ?
18.
by mekpro 1y ago
i got 70 token/s on m4 max
19.
by mekpro 1y ago
try enable flash attention and offload all layer to GPU
20.
by mekpro 1y ago
Is this limit will also count together with Claude Chat ?
21.
by mekpro 1y ago
you can easily reach 50$ per day. by force switching model to opus /model opus it will continue to use opus eventhough there is a warning about approaching limit. i found opus is significantly more capable in coding than sonnet, especc
22.
by mekpro 1y ago
Just refactored 1000 lines of Claude Code generated to 500 lines with Gemini Pro 2.5 ! Very impressed by the overall agentic experience and model performance.
23.
by mekpro 1y ago
To professionals in the field, I have a question: what jobs, positions, and companies are in need of CUDA engineers? My current understanding is that while many companies use CUDA's by-products (like PyTorch), direct CUDA development s
24.
by mekpro 1y ago
it can use tool to explore directory like ls grep out of the box.
25.
Judge said Meta illegally used books to build its AI(wired.com)
406 points by mekpro 1y ago|341 comments
26.
by mekpro 1y ago
Gemma 3 is way way better than Llama 4. I think Meta will start to lose its position in LLM mindshare. Another weakness of Llama 4 is its model size that is too large (even though it can run fast with MoE), which greatly limits the applicab
27.
by mekpro 1y ago
Google is also the only company that has had their own AI hardware that's worked (TPU). This could lead to more cost-effective training + inference and hence better AI.
28.
by mekpro 1y ago
Also, they open-model gemma-3 is very competitive for its size and actually beats llama-3 from Meta. Not to mention that OpenAI doesn't offer anything open anymore.
29.
by mekpro 2y ago
Still a big bubble considered that the price go up 244% compared to 6 months ago.
30.
by mekpro 2y ago
As a quick estimation, the size of q4 quantized model usually be around 60-70% of the model's parameter. You can preciselly check the quantized model size from .gguf files hosted in huggingface.

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