Can Mistral Small 3.2 24B run on RTX PRO 4500 Blackwell 32GB?
YES — Runs Great
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
Choose the run profile you care about
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
Memory breakdown
See how fast it feels
What limits this setup
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.
Best improvement path
Performance by 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 |
Inference speed
Mistral Small 3.2 24B inference speed — tokens per second by GPU & Mac
Estimated decode speed (tokens/sec) for Mistral Small 3.2 24B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~88 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
| 32 GB | Q4_K_M | 88.2 | Fits | |
| 24 GB | Q4_K_M | 56.3 | Tight | |
RX 7900 XTX 24GB | 24 GB | Q4_K_M | 50.8 | Tight |
| 24 GB | Q4_K_M | 48.1 | Tight | |
Mac Studio M3 Ultra 256GB | 256 GB | Q4_K_M | 40.9 | Fits |
MacBook Pro M4 Max 128GB | 128 GB | Q4_K_M | 36.8 | Fits |
MacBook Pro M4 Max 64GB | 64 GB | Q4_K_M | 36.8 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q4_K_M | 34.1 | Fits |
Mac Studio M1 Ultra 128GB | 128 GB | Q4_K_M | 32.3 | Fits |
MacBook Pro M4 Pro 48GB | 48 GB | Q4_K_M | 23.2 | Fits |
| 16 GB | Q4_K_M | 21.3 | Too big | |
MacBook Pro M3 Max 64GB | 64 GB | Q4_K_M | 17.6 | Fits |
MacBook Pro M1 Max 64GB | 64 GB | Q4_K_M | 16.2 | Fits |
| 12 GB | Q4_K_M | 7.5 | Too big | |
| 12 GB | Q4_K_M | 4.7 | Too big | |
| 8 GB | Q4_K_M | 2.2 | Too big |
Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
Quantization options
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 |
Get started
Copy-paste commands to run Mistral Small 3.2 24B on your machine.
Run
ollama run mistral-small3.2Your hardware
More models your RTX PRO 4500 Blackwell 32GB can run
| 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 |
Frequently asked questions
Can RTX PRO 4500 Blackwell 32GB run Mistral Small 3.2 24B?
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.
How much VRAM does Mistral Small 3.2 24B need?
Mistral Small 3.2 24B (24B parameters) requires approximately 21.5 GB of memory with Q4_K_M quantization.
What is the best quantization for Mistral Small 3.2 24B?
The recommended quantization for Mistral Small 3.2 24B is Q4_K_M, which balances quality and memory efficiency.
What speed will Mistral Small 3.2 24B run at on RTX PRO 4500 Blackwell 32GB?
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.
Can RTX PRO 4500 Blackwell 32GB run Mistral Small 3.2 24B for coding?
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.
What context window can Mistral Small 3.2 24B use on RTX PRO 4500 Blackwell 32GB?
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.
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