Can I Run Mistral Small 3.2 on NVIDIA GeForce RTX 4090?
Written by Jakub Rusinowski · Last updated September 29, 2026
Yes, comfortably — Mistral Small 3.2 24B at Q4_K_M needs 16.4 GB at 8K context (14.2 GB weights + 2.2 GB KV cache/overhead), leaving ~7.6 GB of the NVIDIA GeForce RTX 4090's 24 GB, at ~55 tok/s (est.), with room for up to 32K context.
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NVIDIA GeForce RTX 4090 Specs
| VRAM | 24 GB |
| Memory Bandwidth | 1008 GB/s |
Mistral Small 3.2 24B on the NVIDIA GeForce RTX 4090: VRAM by quantization
| Quant | VRAM needed | Fits 24 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 49.3 GB | ✗ No | — | — |
| Q8_0 | 27.2 GB | ✗ No | — | — |
| Q6_K | 21.5 GB | ✓ Yes | 16K | — |
| Q5_K_M | 18.9 GB | ✓ Yes | 32K | — |
| Q4_K_M | 16.4 GB | ✓ Yes | 32K | — |
| Q3_K_M | 12.2 GB | ✓ Yes | 64K | — |
| Q2_K | 9.9 GB | ✓ Yes | 64K | — |
Assumes an 8K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 24 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At Q4_K_M on the NVIDIA GeForce RTX 4090: 8K 16.4 GB · 32K 20.4 GB · 128K 36.5 GB ✗. Past 128K it no longer fits 24 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? Mistral Small 3.2 24B on 16 GB of system RAM, CPU only: runs, but it is tight.
Mistral Small 3.2 Sizes That Fit the NVIDIA GeForce RTX 4090 (at 8K context)
| Mistral Small 3.2 24B | Q4_K_M · 16.4 GB at 8K context · ~55 tok/s (est.) |
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FAQ
Will Mistral Small 3.2 run on the NVIDIA GeForce RTX 4090?
Yes, comfortably — Mistral Small 3.2 24B at Q4_K_M needs 16.4 GB at 8K context (14.2 GB weights + 2.2 GB KV cache/overhead), leaving ~7.6 GB of the NVIDIA GeForce RTX 4090's 24 GB, at ~55 tok/s (est.), with room for up to 32K context.
Which Mistral Small 3.2 variant fits best on the NVIDIA GeForce RTX 4090?
Mistral Small 3.2 24B at Q4_K_M quantization needs 16.4 GB at 8K context (14.2 GB weights + 2.2 GB KV cache/overhead), estimated ~55 tokens/sec, up to 32K context.
Mistral Small 3.2 on Other GPUs
- Mistral Small 3.2 on NVIDIA GeForce RTX 3090
- Mistral Small 3.2 on AMD Radeon RX 7900 XTX
- Mistral Small 3.2 on Apple M4 Pro
- Mistral Small 3.2 on Apple M3
- Mistral Small 3.2 on Apple M2
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