KAT-Coder-V2.5-Dev

KAT-Coder-V2.5-Dev This repository contains the model weights and configuration files for the post-trained KAT-Coder-V2.5-Dev in the Hugging Face Transformers format. The artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc. Note: this open-weight release ships only the language-model weights and operates as a text-only model; the vision/multimodal components are not included and are unavailable. Following the release of KAT-Coder-V2.5 in July, we are pleased to release the open-weight version **KAT-Coder-V2.5-Dev**, an MOE model with a total parameter count of 35B and 3B activated parameters, to strengthen communication with the community and showcase our research achievements. KAT-Coder-V2.5-Dev Highlights **Performance improvement.** Through SFT/RL training, KAT-Coder-V2.5-Dev achieves SOTA results in the field of Agentic Coding among models with similar parameter scales. **Optimization of abnormal behaviors.** Through RL training, certain abnormal behaviors have been significantly optimized, such as: abnormal tool labels -9pp (9.34% -> 0.28%), single-turn continuous repetition -0.34pp (0.34% -> 0%). Benchmark performance Benchmark KAT-Coder-V2.5-Dev Qwen3.5-27B Qwen3.6-35BA3B Gemma4-31B Qwen3.5-35BA3B Ornith-1.0-35B Gemma4-26BA4B Qwen3-Coder-30B Coding Agent SWE-bench Verified 69.40 68.60 64.40 60.60 58.60 55.80 35.80 31.80 SWE-bench Multilingual 63.00 57.67 57.00 49.33 47.67 51.67 27.33 20.67 SWE-bench Pro 45.96 42.13 40.63 32.97 38.03 34.47 9.58 19.84 Terminal-Bench 2.1 41.02 32.60 / 49.44 34.84 41.57 / 28.10 32.02 34.83 / 29.20 32.59 30.34 / 34.83 26.12 26.44 / 25.80 35.98 35.96 / 36.00 20.94 27.27 / 14.60 13.50 10.11 / 16.90 PinchBench 93.43 90.71 92.21 85.53 88.75 91.62 82.01 72.3 Scicode 44.20 25.58 37.53 33.19 27.73 30.34 30.84 18.27 KAT-Code-Bench 46.21 44.83 42.76 37.93 35.86 33.10 22.06 15.17 For **Terminal-Bench 2.1**, the bold number is the average across two agent harnesses; the small numbers below are the per-ha