Autor: Jakub Rusinowski · Ostatnia aktualizacja: 4 kwietnia 2024
Yes, but it is tight
Yes, but it is tight — Command R (35B) at Q2_K needs about 23 GB of the 24 GB usable on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM), leaving only ~1 GB before the runtime starts swapping. Expect ~40.7 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: medium · Recommended quantization: Q2_K · Estimated speed: ~40.7 tok/s
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| Usable memory for models | 24 GB |
| Memory bandwidth | 1008 GB/s |
| Form factor | Desktop |
| Operating system | Windows or Linux |
| Memory upgradeable | Yes |
| Quant | Memory needed | Fits 24 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 81.5 GB | ✗ No | — | — | 70 GB |
| Q8_0 | 48.7 GB | ✗ No | — | — | 37.2 GB |
| Q6_K | 40.2 GB | ✗ No | — | — | 28.7 GB |
| Q5_K_M | 36.3 GB | ✗ No | — | — | 24.8 GB |
| Q4_K_M | 32.7 GB | ✗ No | — | — | 21.1 GB |
| Q3_K_M | 26.5 GB | ✗ No | — | — | 14.9 GB |
| Q2_K | 23 GB | ✓ Yes | 8K | ~40.7 tok/s | 11.5 GB |
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| Command R+ (104B) | 65.7 GB | ✗ Too large | — |
| Command R (35B) | 32.7 GB | ✗ Too large | — |
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Yes, but it is tight — Command R (35B) at Q2_K needs about 23 GB of the 24 GB usable on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM), leaving only ~1 GB before the runtime starts swapping. Expect ~40.7 tok/s (estimated), with room for about 8,192 tokens of context.
Q2_K — it needs about 23 GB of the 24 GB available, downloads as roughly 11.5 GB, and runs at an estimated 40.7 tokens/sec with up to 8K of context.
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
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