granite-4.1-8b-AWQ-INT4
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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. 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
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> [!NOTE] > ### 🏆 2026 Sparse Operator Acceleration & Race (SOAR) is Now Live! > > **"The MiniCPM-SALA architecture is just the beginning. Realizing its full potential requires deep system-level synergy and cross-layer compilation optimization."** > > In collaboration with **SGLang** and **NVIDIA**, OpenBMB invites global geeks to push the boundaries of 9B-scale, 1M-token inference on **NVIDIA 6000D**. > > 💰 **Prize Pool: >$100,000 USD** (🥇 Top Prize: **$89,000**) | 🚀 **Challenge:** Single & Multi-batch Optimization > > 👉 **Click Here to Join the Race @ soar.openbmb.cn** - [2026.02.11] **MiniCPM-SALA** is released! This is the first large-scale hybrid model effectively integrating sparse and linear attention for million-token context modeling. You can find technical report here.🔥🔥🔥 MiniCPM-SALA (Sparse Attention and Linear Attention) is the first large-scale hybrid model effectively integrating sparse and linear attention for million-token context modeling
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