Kimi K2.5
1026.9B total, 33.3B active · 256k context · Modified MIT License · released 2026-01-01
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In short
Kimi K2.5 is an open model from Moonshot AI with 1026.9B parameters (33.3B active per token). At mlx-3bit, Kimi K2.5 needs about 420 GB of memory at 8k context and 420 GB at 8k, counting the weights, the KV cache and runtime buffers. Nothing we price in the US runs Kimi K2.5 fully in memory at 8k context at a usable speed; see the table for what comes closest.
Updated . Speeds are estimates; how they are worked out.
What to run it on in the US
Fully in memory at 8k context, priced at retailers today.
Nothing we price holds this model fully in memory.
All hardware that runs it
Everything we price, best value first. Two cards split the model by layers.
Nothing we price can run it at this context.
Memory needed
Weights, KV cache and runtime buffers at each context length (KV cache at fp16).
| Quant | File | @8k | @32k | @64k | @128k |
|---|---|---|---|---|---|
| mlx-3bitmlx | 418.5 GB | 419.7 GB | 421.5 GB | 423.8 GB | 428.5 GB |
| Q4_K_Mgguf | 578.6 GB | 579.9 GB | 581.6 GB | 583.9 GB | 588.6 GB |
| Q5_K_Mgguf | 678.7 GB | 680.0 GB | 681.7 GB | 684.1 GB | 688.7 GB |
| Q6_Kgguf | 785.0 GB | 786.3 GB | 788.1 GB | 790.4 GB | 795.0 GB |
| Q8_0gguf | 1016.1 GB | 1017.4 GB | 1019.2 GB | 1021.5 GB | 1026.2 GB |
Run it
Copy a command for the runtime you use.
- mlx-3bit
- LM Studio
lms get mlx-community/Kimi-K2.5-3bit - MLX
mlx_lm.server --model mlx-community/Kimi-K2.5-3bit
- LM Studio
- Q4_K_M
- Ollama
ollama run hf.co/unsloth/Kimi-K2.5-GGUF:Q4_K_M - LM Studio
lms get unsloth/Kimi-K2.5-GGUF@q4_k_m - llama.cpp
llama-server -hf unsloth/Kimi-K2.5-GGUF:Q4_K_M
- Ollama
- Q5_K_M
- Ollama
ollama run hf.co/unsloth/Kimi-K2.5-GGUF:Q5_K_M - LM Studio
lms get unsloth/Kimi-K2.5-GGUF@q5_k_m - llama.cpp
llama-server -hf unsloth/Kimi-K2.5-GGUF:Q5_K_M
- Ollama
- Q6_K
- Ollama
ollama run hf.co/unsloth/Kimi-K2.5-GGUF:Q6_K - LM Studio
lms get unsloth/Kimi-K2.5-GGUF@q6_k - llama.cpp
llama-server -hf unsloth/Kimi-K2.5-GGUF:Q6_K
- Ollama
- Q8_0
- Ollama
ollama run hf.co/unsloth/Kimi-K2.5-GGUF:Q8_0 - LM Studio
lms get unsloth/Kimi-K2.5-GGUF@q8_0 - llama.cpp
llama-server -hf unsloth/Kimi-K2.5-GGUF:Q8_0
- Ollama
Notes
1T-parameter MoE (32B active) with native INT4 quantization; recommended engines are vLLM, SGLang and KTransformers, and transformers must be 4.57.1 or later. Video chat is experimental and only supported in the official API for now.
Questions
- How much VRAM does Kimi K2.5 need?
- At mlx-3bit, Kimi K2.5 needs about 420 GB of memory at 8k context and 420 GB at 8k, counting the weights, the KV cache and runtime buffers.
- Can I run Kimi K2.5 on a 16 GB GPU?
- No: it does not fit in 16 GB at 8k context, even with system RAM.
- Can I run Kimi K2.5 on a 24 GB GPU?
- No: it does not fit in 24 GB at 8k context, even with system RAM.
- How do I run Kimi K2.5 locally?
- With Ollama: ollama run hf.co/unsloth/Kimi-K2.5-GGUF:Q4_K_M (the Q4_K_M build). LM Studio and llama.cpp commands are on this page.
- What licence is Kimi K2.5 released under?
- Modified MIT License.