2026-08-10

Available context length with and without the patch: Model: QWEN 27B ROCm stock patched Vulkan stock patched IQ4_XS Pure, single 16GB GPU 19.456 76.032 68,352 78,592 Q6_K_L on 16GB + 12GB 64,256 149,248 68,864 151,296 The issue is that llama.cpp overestimates the memory needed for MTP compute-buffer/scheduler allocation during auto-fit, that leaves much less ctx available to the user than what actually needed by MTP. This patch stops the fitter from throwing away context based on an inflated MTP

Tweet by u/hackerllama Could be copium, but I would love to see Gemma 4.1 there with unified audio input for all model sizes perhaps even up to 120B, much improved tool calling (even with the latest template there are still bugs ), higher precision QAT from the start and improved general performance without hurting the things Gemma 4 is good at like creative writing. Gemma 4 is good already but training an upgrade to 4.1 that does all of the above would be huge for the community. They already di

I’m reaching speeds of 260T/s tg and 20k pp on my 3090s lol, because this model is small and meant to run on phones. From what I‘ve been trying it’s surprisingly great for incredibly quick things like “read this massive thing and tell me if it mentions x” or “what’s the summary of this dumb pop sci article” or “what’s that one command that does y on Linux” or for quick autocomplete of something that has similar structure that you don’t feel like typing out (like when someone pastes a long comman

Looks impressive from that site, hopefully they open weight this so we can all play with it.

The AI-focused hedge fund is still making some big bets.

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About 90 percent of the distance driven by Perseverance has been autonomous.

Learning generalizable robot manipulation policies requires large-scale and diverse demonstration data. Egocentric human manipulation videos offer rich scene and task diversity, and prior work has shown that retargeting and rendering such videos into robot-format data can yield effective per-task policies at small scale. However, whether this approach can provide pretraining benefits for vision-language-action models at scale remains unexplored. We present Ego2Robot, a scalable pipeline that con

I am not a meteorologist, but I just read a very interesting article: In a paper published on Thursday in Nature, researchers show that the WeatherNext AI model can predict cyclones with unprecedented accuracy. On average, it gives forecasters a day more lead time than existing models; this means its predictions three days out are as accurate as previous models’ predictions two days out. On the ground, that extra day can mean a lot. What I really find interesting here is that Google has a reposi

The AI that acts as you, right in your browser Discussion | Link

Hi peeps, I am mostly working as a freelancer and FOSS developer. I posted an AI fluff yesterday, and it didn't feel right. So this is written by my own ten fingers. Like many others, I have been using AI extensively for the past few years. And I now have a mix of codebases - some written by hand first and gradually with AI tools, and projects written from the get go using agents and without touching the code itself outside code review and guidance. I wonder how you all are understanding your co