Mistral Small 3.2 24B needs ~21.5 GB VRAM. RTX PRO 4500 Blackwell 32GB has 32.0 GB. With Q4_K_M quantization, expect ~55 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
55.3 tok/s
TTFT
3503 ms
Safe context
85K
Memory
21.5 GB / 32.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs well | 55.3 tok/s | 1911 ms | 85K |
| Coding | S | Runs well | 55.3 tok/s | 3503 ms | 85K |
| Agentic Coding | S | Runs well | 55.3 tok/s | 5095 ms | 85K |
| Reasoning | S | Runs well | 55.3 tok/s | 4140 ms | 85K |
| RAG | S | Runs well | 55.3 tok/s | 6369 ms | 85K |
How Mistral Small 3.2 24B (24B params) fits at each quantization level on RTX PRO 4500 Blackwell 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | A80 |
Q3_K_S | 3 | 11.8 GB | Low | A81 |
NVFP4 | 4 | 13.4 GB | Medium | A82 |
Q4_K_M | 4 | 14.6 GB | Medium | A82 |
Q5_K_M | 5 | 17.3 GB | High | A83 |
Q6_K | 6 | 19.7 GB | High | A83 |
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 | 113.8 tok/s | ||
| 27B | S | 49.4 tok/s | ||
| 27B | S | 49.5 tok/s | ||
| 35B | S | 95.6 tok/s | ||
| 30B | S | 117.7 tok/s |
Yes, RTX PRO 4500 Blackwell 32GB can run Mistral Small 3.2 24B with a S grade (Runs well). Expected decode speed: 55.3 tok/s.
Mistral Small 3.2 24B (24B parameters) requires approximately 21.5 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 RTX PRO 4500 Blackwell 32GB, Mistral Small 3.2 24B achieves approximately 55.3 tokens per second decode speed with a time-to-first-token of 3503ms using Q4_K_M quantization.
For coding workloads, Mistral Small 3.2 24B on RTX PRO 4500 Blackwell 32GB receives a S grade with 55.3 tok/s and 85K context.
On RTX PRO 4500 Blackwell 32GB, Mistral Small 3.2 24B can safely use up to 85K 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-rtx-pro-4500-blackwell-32gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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