Smaller alternatives
Models that need less memory than Kimi K2 Thinking and score about as well or better.
Kimi K2 Thinking
MoE
Moonshot AI · 1T (32B active) · Mixture of experts
Kimi K2 Thinking is a 1T model from Moonshot AI with a 256K-token context. At Q4_K_M with an 8K context it needs about 579.4 GB; 726 GB leaves room for longer chats.
Mixture of experts
Parameters: 1T · Active: 32B
All 1T parameters load into memory, but only 32B work on each token, so it runs at the speed of a much smaller model.
Quantization options
| Quant | Bits | Memory | Quality | On your hardware |
|---|---|---|---|---|
| Q2_K | 3.16 | — | Noticeably worse | … |
| Q3_K_M | 4 | — | Some loss | … |
| Q4_K_M | 4.89 | — | Good | … |
| Q5_K_M | 5.7 | — | Good | … |
| Q6_K | 6.56 | — | Near original | … |
| Q8_0 | 8.5 | — | Near original | … |
| F16 | 16 | — | Original | … |
Memory by context length
At Q4_K_M. The context cache grows with every token the model keeps in mind.
| Context | Context cache | Total |
|---|---|---|
| 4K | 0.3 GB | 579.1 GB |
| 8K | 0.5 GB | 579.4 GB |
| 32K | 2.1 GB | 581 GB |
| 128K | 8.6 GB | 587.5 GB |
| 256K | 17.2 GB | 596 GB |
Next steps
Compare it with
Scored models of a similar size, side by side on your device.
Least hardware that runs it well
Desktop devices with the least memory that give Kimi K2 Thinking grade A or S at Q4_K_M.
No desktop device in our catalog runs it at grade A or better.
Can I run Kimi K2 Thinking locally?
Can I run Kimi K2 Thinking locally?
Yes, if your GPU or Mac has about 579.4 GB free for it at Q4_K_M. Open this page on that computer to see the grade for your exact hardware, then start it with llama.cpp, Ollama or LM Studio.
How much memory does Kimi K2 Thinking need?
About 579.4 GB at Q4_K_M with an 8K context and 1,017 GB at Q8_0. Lower quantizations fit smaller cards with some loss in quality; longer contexts add to the total.