Kimi K2.5 / K2.6 / K2.7 — local AI model by Moonshot AI
Written by Jakub Rusinowski · Last updated
Moonshot AI's cutting-edge coding and agentic model series. Kimi K2.5, K2.6 and the coding-specialised K2.7 Code rank among the top models globally for coding tasks, multimodal understanding, and autonomous agent workflows. Built for developers who need a model that can reason, use tools, browse the web, write and debug code end-to-end.
Variants
The smallest Kimi K2.5 / K2.6 / K2.7 variant needs about 605 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache.
| Model | VRAM at Q4 | VRAM | Context | Run it |
|---|---|---|---|---|
| Kimi K2.5 → 1T/32B active | ~604.6 GB | 256,000 | ollama run hf.co/moonshotai/Kimi-K2.5-Instruct-Q4_K_M | |
| Kimi K2.6 → 1T/32B active | ~604.6 GB | 256,000 | ollama run hf.co/moonshotai/Kimi-K2.6-Instruct-Q4_K_M | |
| Kimi K2.5 1T (32B Active) 1T/32B active | ~604.6 GB | 256,000 | ollama run hf.co/moonshotai/Kimi-K2.5 | |
| Kimi K2.7 Code → 1T/32B active | ~604.6 GB | 262,144 | ollama run kimi-k2 |
Memory is quantized weights plus overhead at Q4_K_M, from the same engine as the GPU & VRAM checker.
How to run Kimi K2.5 / K2.6 / K2.7 locally
Install Ollama, then pull the tag.
ollama run hf.co/moonshotai/Kimi-K2.5-Instruct-Q4_K_MPick a size above for its own VRAM figure, speed estimate and install command.
Licence
Commercial use permitted. No usage restrictions beyond attribution.
Applies to: Kimi K2.5, Kimi K2.6, Kimi K2.7 CodeWeights are downloadable and commercial use is permitted, subject to the licence’s acceptable-use terms.
Applies to: Kimi K2.5 1T (32B Active)Kimi K2.5 / K2.6 / K2.7 — frequently asked questions
How much VRAM does Kimi K2.5 / K2.6 / K2.7 need?
Kimi K2.5 / K2.6 / K2.7 needs about 605 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Kimi K2.5 (605 GB, Q4_K_M); Kimi K2.6 (605 GB, Q4_K_M); Kimi K2.5 1T (32B Active) (605 GB, Q4_K_M); Kimi K2.7 Code (605 GB, INT4 (native)). On Apple Silicon, unified memory counts toward this requirement.
Can I run Kimi K2.5 / K2.6 / K2.7 on an RTX 4090 (24 GB)?
Kimi K2.5 / K2.6 / K2.7's smallest variant needs about 605 GB, which exceeds a single RTX 4090 (24 GB). Use multiple GPUs, a higher-VRAM card, or Apple Silicon with large unified memory.
What quantization should I use for Kimi K2.5 / K2.6 / K2.7?
Q4_K_M is the best balance of quality and VRAM for Kimi K2.5 / K2.6 / K2.7 in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
How do I run Kimi K2.5 / K2.6 / K2.7 with Ollama?
Install Ollama, then run: ollama run hf.co/moonshotai/Kimi-K2.5-Instruct-Q4_K_M. This downloads Kimi K2.5 / K2.6 / K2.7 and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.