Smaller alternatives
Models that need less memory than Kimi K2.7 Code and score about as well or better.
Kimi K2.7 Code
MoEVision
Moonshot AI · 1T (32B active) · Mixture of experts
Kimi K2.7 Code is a 1T model from Moonshot AI with a 256K-token context. At Q4_K_M with an 8K context it needs about 578.8 GB; 725 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 | 578.5 GB |
| 8K | 0.5 GB | 578.8 GB |
| 32K | 2.1 GB | 580.4 GB |
| 128K | 8.6 GB | 586.8 GB |
| 256K | 17.2 GB | 595.4 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 K2.7 Code 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 K2.7 Code locally?
Can I run Kimi K2.7 Code locally?
Yes, if your GPU or Mac has about 578.8 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 K2.7 Code need?
About 578.8 GB at Q4_K_M with an 8K context and 1,017.1 GB at Q8_0. Lower quantizations fit smaller cards with some loss in quality; longer contexts add to the total.