Kimi K2.5
Moonshot AI's Kimi K2.5. Auto-imported from Hugging Face seed; review memory and benchmark details before using for final ranking.
Task Fit
Tool use, repo work, terminal workflows, and coding benchmarks.
Code generation, debugging, refactoring, and benchmark signal.
General writing, Q&A, and assistant use.
Document QA benefits from long context and instruction following.
Image or visual understanding, not necessarily image generation.
Not marked for image generation in the current library.
Not marked for video generation in the current library.
Not marked for voice in the current library.
Source Confidence
Variants and Quant Artifacts
Choose the artifact first; hardware fit follows from RAM, VRAM, format, and runtime.
| Quant | Format | Quality | Min RAM | Reco RAM | Runtime | Action |
|---|---|---|---|---|---|---|
| Q4_K_M | gguf | balanced | 32GB | 48GB | llama.cpp, lm-studio | Plan with this |
| Q5_K_M | gguf | balanced | 40GB | 64GB | llama.cpp, lm-studio | Plan with this |
| Q8_0 | gguf | high | 64GB | 96GB | llama.cpp, lm-studio | Plan with this |
| FP16 | safetensors | high | 2TB | 3TB | transformers, vllm | Plan with this |
Recommended Hardware
Lowest estimated 5-year cost that can run this model.
Plenty of fast-memory headroom for this model.
Highest local performance signal among compatible hardware.
Benchmarks
No benchmark data is available for this model yet.
Source and Review
Similar Models
Moonshot AI's Kimi K2.7 Code. Auto-imported from Hugging Face seed; review memory and benchmark details before using for final ranking.
Moonshot AI's Kimi K2.6. Auto-imported from Hugging Face seed; review memory and benchmark details before using for final ranking.
Moonshot AI Kimi K3 is an open-weight 2.8T-parameter multimodal MoE model with 104B active parameters, native MXFP4 weights, always-on reasoning, tool use, and a 1M-token context window. The official release targets large multi-accelerator deployments through vLLM, SGLang, or TokenSpeed rather than consumer local hardware.