Mistral Small 3.2 24B needs ~23.1 GB VRAM. Quadro RTX 8000 48GB has 48.0 GB. With Q4_K_M quantization, expect ~34 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
34.0 tok/s
TTFT
5686 ms
Safe context
131K
Memory
23.1 GB / 48.0 GB
This setup is broadly balanced for this model.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 34.0 tok/s | 3102 ms | 131K |
| Coding | A | Runs well | 34.0 tok/s | 5686 ms | 131K |
| Agentic Coding | A | Runs well | 34.0 tok/s | 8271 ms | 131K |
| Reasoning | A | Runs well | 34.0 tok/s | 6720 ms | 131K |
| RAG | A | Runs well | 34.0 tok/s | 10338 ms | 131K |
How Mistral Small 3.2 24B (24B params) fits at each quantization level on Quadro RTX 8000 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | A77 |
Q3_K_S | 3 | 11.8 GB | Low | A77 |
NVFP4 | 4 | 13.4 GB | Medium | A78 |
Q4_K_M | 4 | 14.6 GB | Medium | A78 |
Q5_K_M | 5 | 17.3 GB | High | A79 |
Q6_K | 6 | 19.7 GB | High | A80 |
Q8_0Best for your GPU | 8 | 25.7 GB | Very High | A82 |
F16 | 16 | 49.2 GB | Maximum | F0 |
Copy-paste commands to run Mistral Small 3.2 24B on your machine.
Run
ollama run mistral-small3.2Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 30.5B | S | 70.1 tok/s | ||
| 27B | S | 30.4 tok/s | ||
| 27B | S | 30.5 tok/s | ||
| 35B | S | 58.9 tok/s | ||
| 30B | S | 72.5 tok/s |
Yes, Quadro RTX 8000 48GB can run Mistral Small 3.2 24B with a A grade (Runs well). Expected decode speed: 34.0 tok/s.
Mistral Small 3.2 24B (24B parameters) requires approximately 23.1 GB of memory with Q4_K_M quantization.
The recommended quantization for Mistral Small 3.2 24B is Q4_K_M, which balances quality and memory efficiency.
On Quadro RTX 8000 48GB, Mistral Small 3.2 24B achieves approximately 34.0 tokens per second decode speed with a time-to-first-token of 5686ms using Q4_K_M quantization.
For coding workloads, Mistral Small 3.2 24B on Quadro RTX 8000 48GB receives a A grade with 34.0 tok/s and 131K context.
On Quadro RTX 8000 48GB, Mistral Small 3.2 24B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/mistral-small-3.2-24b-on-quadro-rtx-8000-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: