Can Mistral Small 3.2 24B run on RTX A5000 24GB?
YES — Tight Fit
Mistral Small 3.2 24B needs ~20.7 GB VRAM. RTX A5000 24GB has 24.0 GB. With Q4_K_M quantization, expect ~40 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
Tight fit
Decode
39.5 tok/s
TTFT
4904 ms
Safe context
38K
Memory
20.7 GB / 24.0 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 | 39.5 tok/s | 2675 ms | 38K |
| Coding | S | Tight fit | 39.5 tok/s | 4904 ms | 38K |
| Agentic Coding | S | Runs with offload | 39.5 tok/s | 7134 ms | 38K |
| Reasoning | S | Tight fit | 39.5 tok/s | 5796 ms | 38K |
| RAG | S | Runs with offload | 39.5 tok/s | 8917 ms | 38K |
Quantization options
How Mistral Small 3.2 24B (24B params) fits at each quantization level on RTX A5000 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | A83 |
Q3_K_S | 3 | 11.8 GB | Low | A84 |
NVFP4 | 4 | 13.4 GB | Medium | A84 |
Q4_K_M | 4 | 14.6 GB | Medium | A84 |
Q5_K_MBest for your GPU | 5 | 17.3 GB | High | A83 |
Q6_K | 6 | 19.7 GB | High | F0 |
Q8_0 | 8 | 25.7 GB | Very High | F0 |
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
