Home › Models › Kimi K2.7 Code
Kimi K2.7 Code: VRAM needs and speed by GPU
At UD-Q4_K_XL, Kimi K2.7 Code needs about 586.7 GB of VRAM. We have 1 measured speed results for it.
Ranked #20 among open-weight models by the Artificial Analysis Intelligence Index, checked 2026-10-22T16:10:10Z. All leading open models.
1026.41B parameters (mixture-of-experts, ~32.8B active) · license: other · 262,144-token context · GGUF published 2026-06-12T18:03:48.000Z · GGUF files on Hugging Face
Measured speeds
| Chip | Generation tok/s | Prompt tok/s | Quant | Backend | Test | Source |
|---|---|---|---|---|---|---|
| Apple M3 Ultra (80-core GPU) | 24.6 | 145 | UD-Q2_K_XL | Metal | tg300 (llama-bench -n 300) | AI KIZAI: Mac Studio M3 Ultra 512 GB measured benchmarks details |
Memory needed per quantization
| Quant | File size | Needs (estimate) | Smallest card it fits |
|---|---|---|---|
| UD-IQ1_M | 303.9 GB | 306.9 GB | multi-GPU / large unified memory |
| UD-IQ2_XXS | 317.8 GB | 320.8 GB | multi-GPU / large unified memory |
| UD-IQ2_M | 318.0 GB | 321.0 GB | multi-GPU / large unified memory |
| UD-Q2_K_XL | 339.5 GB | 342.5 GB | multi-GPU / large unified memory |
| UD-IQ3_S | 418.8 GB | 421.8 GB | multi-GPU / large unified memory |
| UD-Q3_K_M | 463.6 GB | 466.6 GB | multi-GPU / large unified memory |
| UD-Q3_K_XL | 463.9 GB | 466.9 GB | multi-GPU / large unified memory |
| UD-IQ4_XS | 495.1 GB | 498.1 GB | multi-GPU / large unified memory |
| UD-Q4_K_XL | 583.7 GB | 586.7 GB | multi-GPU / large unified memory |
| UD-Q8_K_XL | 594.5 GB | 597.5 GB | multi-GPU / large unified memory |
Expected speed on popular hardware
| Hardware | Best quant that fits | Expected tok/s |
|---|---|---|
| NVIDIA RTX 3060 | Does not fit | |
| NVIDIA RTX 4060 Ti | Does not fit | |
| NVIDIA RTX 3090 | Does not fit | |
| NVIDIA RTX 4090 | Does not fit | |
| NVIDIA RTX 5090 | Does not fit | |
| AMD Radeon RX 7900 XTX | Does not fit | |
| Apple M4 Pro (20-core GPU) | Does not fit | |
| Apple M3 Max (40-core GPU) | Does not fit | |
| AMD Ryzen AI Max+ 395 (Radeon 8060S) | Does not fit | |
Too big for your card?
Run Kimi K2.7 Code on a rented 24-80 GB GPU by the hour.
Rent a bigger GPU on RunPodAffiliate link: if you sign up, RigBench may earn a referral credit. It never affects rankings or numbers.