Written by Jakub Rusinowski · Last updated September 6, 2026
Yes
Yes — Magistral Small 24B at Q8_0 needs about 28 GB of the 32 GB usable on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM) (~4 GB spare), at ~45.8 tok/s (estimated), with room for about 16,384 tokens of context.
Confidence: medium · Recommended quantization: Q8_0 · Estimated speed: ~45.8 tok/s
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| Usable memory for models | 32 GB |
| Memory bandwidth | 1792 GB/s |
| Form factor | Desktop |
| Operating system | Windows or Linux |
| Memory upgradeable | Yes |
| Quant | Memory needed | Fits 32 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 50.5 GB | ✗ No | — | — | 48 GB |
| Q8_0 | 28 GB | ✓ Yes | 16K | ~45.8 tok/s | 25.5 GB |
| Q6_K | 22.2 GB | ✓ Yes | 32K | ~57.1 tok/s | 19.7 GB |
| Q5_K_M | 19.5 GB | ✓ Yes | 64K | ~64.4 tok/s | 17 GB |
| Q4_K_M | 17 GB | ✓ Yes | 64K | ~73.3 tok/s | 14.5 GB |
| Q3_K_M | 12.7 GB | ✓ Yes | 64K | ~95.4 tok/s | 10.2 GB |
| Q2_K | 10.4 GB | ✓ Yes | 64K | ~114.4 tok/s | 7.9 GB |
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Yes — Magistral Small 24B at Q8_0 needs about 28 GB of the 32 GB usable on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM) (~4 GB spare), at ~45.8 tok/s (estimated), with room for about 16,384 tokens of context.
Q8_0 — it needs about 28 GB of the 32 GB available, downloads as roughly 25.5 GB, and runs at an estimated 45.8 tokens/sec with up to 16K 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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