Can I Run Mistral Family on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM)?
Written by Jakub Rusinowski · Last updated January 28, 2025
Yes, but it is tight
Yes, but it is tight — Mistral Small 3 (24B) at Q6_K needs about 22.4 GB of the 24 GB usable on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM), leaving only ~1.6 GB before the runtime starts swapping. Expect ~33.9 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: medium · Recommended quantization: Q6_K · Estimated speed: ~33.9 tok/s
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RTX 4090 Desktop (24 GB VRAM, 64 GB RAM) — what it gives a model
| Usable memory for models | 24 GB |
| Memory bandwidth | 1008 GB/s |
| Form factor | Desktop |
| Operating system | Windows or Linux |
| Memory upgradeable | Yes |
Mistral Family on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM): memory by quantization
| Quant | Memory needed | Fits 24 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 50.7 GB | ✗ No | — | — | 48 GB |
| Q8_0 | 28.2 GB | ✗ No | — | — | 25.5 GB |
| Q6_K | 22.4 GB | ✓ Yes | 8K | ~33.9 tok/s | 19.7 GB |
| Q5_K_M | 19.7 GB | ✓ Yes | 16K | ~38.5 tok/s | 17 GB |
| Q4_K_M | 17.2 GB | ✓ Yes | 32K | ~44.1 tok/s | 14.5 GB |
| Q3_K_M | 12.9 GB | ✓ Yes | 32K | ~58.8 tok/s | 10.2 GB |
| Q2_K | 10.6 GB | ✓ Yes | 32K | ~71.8 tok/s | 7.9 GB |
Which Mistral Family sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| Mistral Small 3 (24B) | 17.2 GB | ✓ Fits | ~44.1 tok/s |
| Mistral NeMo 12B | 9.4 GB | ✓ Fits | ~78.6 tok/s |
RTX 4090 desktop limitations
- 24 GB is the sweet spot for 27–32B models at Q4; 70B needs offload or a second card.
Recommended setup
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
How these numbers are calculated
- Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
- 24 GB of VRAM on the NVIDIA GeForce RTX 4090 at 1008 GB/s.
- 64 GB of system RAM available for CPU offload when a model exceeds VRAM.
- Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
- KV cache is computed from this model's published attention configuration.
FAQ
Can I run Mistral Family on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM)?
Yes, but it is tight — Mistral Small 3 (24B) at Q6_K needs about 22.4 GB of the 24 GB usable on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM), leaving only ~1.6 GB before the runtime starts swapping. Expect ~33.9 tok/s (estimated), with room for about 8,192 tokens of context.
Which quantization of Mistral Family should I use on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM)?
Q6_K — it needs about 22.4 GB of the 24 GB available, downloads as roughly 19.7 GB, and runs at an estimated 33.9 tokens/sec with up to 8K of context.
What limits Mistral Family on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM)?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Other Computers
Other Models on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM)
- Mistral Small 3.1 on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM)
- Mistral Small 3.2 on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM)
- Nemotron 3 Nano Omni on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM)
- Nemotron Cascade 2 on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM)
- Nex-N2 on RTX 4090 Desktop (24 GB VRAM, 64 GB RAM)
Mistral Family on GPUs
- Mistral Family on NVIDIA GeForce RTX 5090
- Mistral Family on NVIDIA GeForce RTX 5080
- Mistral Family on NVIDIA GeForce RTX 5070 Ti
- Mistral Family on NVIDIA GeForce RTX 5070
What This Model Is Good At
Model & Tools
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