Model Releases
KAT Coder 2.5 dev: Do yourself a favor and try it!
It is so good! I don't know why there aren't more people talking about it. Fewer tokens, faster and more accurate than Qwen 3.6 35b a3b. On my setup it's nearly as good as 27b, but 5x faster. And it c
It is so good! I don't know why there aren't more people talking about it. Fewer tokens, faster and more accurate than Qwen 3.6 35b a3b. On my setup it's nearly as good as 27b, but 5x faster. And it completely trashes the Gemma 4 models. At least for my use case, it feels amazing. I'd love to hear other people's experience with it. If you want an actual measure of performance, I have a GitHub repo explaining how I tested it for my type of use case with a detailed performance comparison with other models . It has the quants I used, OpenCode and llama.cpp version along with all the flags for temp, top-p, top-k etc.; and if there's some detail missing please let me know. But really I think you should just download the model and try it out yourself, because we all have different use cases and those will always be more informative than benchmarks or one person's idiosyncratic experience. EDIT: Based on initial comments I want to say a bit more. My particular use case is a technical one. In my testing, I tested seven local models on a real modification task against my own research code — a computational model from an academic paper, with a written modification plan supplied. The task required synthesizing information across several files, and the codebase carries undocumented assumptions from when I wrote it. That turns out to be the hard part: it's easy to make a change that looks correct, runs without error, and quietly invalidates the measurement the code exists to produce. Most models did exactly that. Grading is based on running the deliverables, not reading them. I say this to highlight that KAT isn't just fast, it's smart. While Orinth 35b was slightly faster than KAT, it performed significantly worse. Here's a simplified table of how I score the models in the GitHub repo: Run Score Notable Qwen 3.6 27B 8/10 only correct measurement KAT-Coder-V2.5-Dev 35B A3B 7/10 only clean four-notebook run Gemma 4 31B (bartowski) 5/10 false zeros Ornith 1.0 35B 3/10 plausible numbers, none real Qwen 3.6 35B A3B 3/10 four blockers, nothing runs Gemma 4 26B A4B (bartowski) 2/10 never converted the multiprocessing Gemma 4 31B QAT (unsloth) 1/10 inverted test rewards submitted by /u/The_Paradoxy [link] [comments]
Source: r/LocalLLaMA | 2026-08-03