Text model · Kimi
KI Kimi K2.7 Code: RAM and VRAM requirements
Kimi K2.7 Code needs about 592.1 GB to run at Q4_K_M (the Q4_K_M GGUF file is ~583.71 GB to download; KV cache and overhead add the rest), or about 1070.9 GB at Q8_0. The lightest hardware that runs it is a high-memory machine.
Kimi family · 1000B params (Mixture-of-Experts: activates only 32B of 1000B params per token, so generation is faster than the total size suggests) · released Jun 2026.
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Q4_K_M and Q8_0 are GGUF download (file) sizes. Memory @ Q4 includes the KV cache and overhead, so it runs larger than the file on disk.
Will it run on your device?
Kimi K2.7 Code runs on 0 of 40 tracked devices at Q4_K_M.
Memory breakdown
How context length changes it
Longer context grows the KV cache, which for Kimi K2.7 Code is sized by its 32B active params, not the full 1000B. It needs ~592.1 GB at 4k and ~827.4 GB at 128k.
Quantization sizes
| Quantization | Size on disk |
|---|---|
| Q2_K | 418.8 GB est |
| Q3_K_M | 488.8 GB est |
| Q4_K_M (default) | 583.71 GB |
| Q5_K_M | 712.5 GB est |
| Q6_K | 820 GB est |
| Q8_0 | 1062.5 GB est |
| FP16 | 2000 GB est |
Lower quant = smaller and faster, slightly lower quality. Q4_K_M is the common default.
Run it
llama-cli -hf unsloth/Kimi-K2.7-Code-GGUF:Q4_K_M lms get unsloth/Kimi-K2.7-Code-GGUF Which devices can run Kimi K2.7 Code?
Apple Silicon Macs
- Apple M1 (8GB) No
- Apple M2 (16GB) No
- Apple M4 (16GB) No
- Apple M5 (16GB) No
- Apple M3 Pro (18GB) No
- Apple M4 (24GB) No
- Apple M4 Pro (24GB) No
- Apple M5 (32GB) No
- Apple M4 Pro (48GB) No
- Apple M5 Pro (48GB) No
- Apple M4 Max (64GB) No
- Apple M4 Max (128GB) No
- Apple M5 Max (128GB) No
- Apple M3 Ultra (256GB) No
RAM-only laptops
iPhone & iPad
Android
NVIDIA GPUs
Same job, different size
Pick by what fits your memory: step down to free up VRAM, or step up if you have headroom.
Similar models
Head-to-head
FAQ
How much VRAM or RAM does Kimi K2.7 Code need?
At Q4_K_M, Kimi K2.7 Code needs about 592.1 GB (weights ~583.71 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~1070.9 GB.
What is the Q4_K_M GGUF file size of Kimi K2.7 Code?
The Q4_K_M GGUF file is about 583.71 GB to download, and the Q8_0 GGUF is about 1062.5 GB. That is the weights file on disk; to run it you also need room for the KV cache and overhead, so budget ~592.1 GB of memory at Q4_K_M.
Can Kimi K2.7 Code run on a laptop?
Kimi K2.7 Code is large; you need a high-memory Mac or multi-GPU setup at Q4_K_M.
Is Kimi K2.7 Code cheaper to run because it is a MoE model?
It is faster, not lighter. Kimi K2.7 Code activates only 32B of 1000B params per token (so it runs quickly), but all experts must stay in memory, so it still needs memory for the full 1000B.
Can I use Kimi K2.7 Code commercially?
Conditionally. Modified MIT; commercial use allowed below a large-user threshold, attribution above it.
Understand the numbers
Short guides to the ideas behind Kimi K2.7 Code's memory and quant figures.
Moonshot's coding variant of the 1T K2 line: 32B active, vision-capable, 256K context. Q4 figure is unsloth's UD-Q4_K_XL (583.71GB); the 1-bit UD-IQ1_M floor is still 304GB. Cloud-only on Ollama; no single consumer machine runs it.
Sources
Last validated 2026-08-03. Memory figures are estimates. See methodology.