Pixtral 12B needs ~13.4 GB VRAM. RTX A5000 24GB has 24.0 GB. With Q4_K_M quantization, expect ~79 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
79.0 tok/s
TTFT
2452 ms
Safe context
86K
Memory
13.4 GB / 24.0 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 | A | Runs well | 79.0 tok/s | 1338 ms | 86K |
| Coding | A | Runs well | 79.0 tok/s | 2452 ms | 86K |
| Agentic Coding | A | Runs well | 79.0 tok/s | 3567 ms | 86K |
| Reasoning | A | Runs well | 79.0 tok/s | 2898 ms | 86K |
| RAG | A | Runs well | 79.0 tok/s | 4458 ms | 86K |
How Pixtral 12B (12B params) fits at each quantization level on RTX A5000 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.7 GB | Low | B69 |
Q3_K_S | 3 | 5.9 GB | Low | B70 |
NVFP4 | 4 | 6.7 GB | Medium | A70 |
Q4_K_M | 4 | 7.3 GB | Medium | A70 |
Q5_K_M | 5 | 8.6 GB | High | A71 |
Q6_K | 6 | 9.8 GB | High | A72 |
Q8_0Best for your GPU | 8 | 12.8 GB | Very High | A74 |
F16 | 16 | 24.6 GB | Maximum | F0 |
Copy-paste commands to run Pixtral 12B on your machine.
Run
ollama run pixtralYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen3-Coder 30B A3B Instruct | 30.5B | S | 81.3 tok/s | |
| Qwen 3.5 27B | 27B | S | 35.3 tok/s | |
| Qwen 3.6 27B | 27B | S | 35.4 tok/s | |
| Qwen3-VL 30B A3B Instruct | 30B | S | 84.1 tok/s | |
| Qwen 3.5 35B A3B | 35B | A | 45.5 tok/s |
Yes, RTX A5000 24GB can run Pixtral 12B with a A grade (Runs well). Expected decode speed: 79.0 tok/s.
Pixtral 12B (12B parameters) requires approximately 13.4 GB of memory with Q4_K_M quantization.
The recommended quantization for Pixtral 12B is Q4_K_M, which balances quality and memory efficiency.
On RTX A5000 24GB, Pixtral 12B achieves approximately 79.0 tokens per second decode speed with a time-to-first-token of 2452ms using Q4_K_M quantization.
For coding workloads, Pixtral 12B on RTX A5000 24GB receives a A grade with 79.0 tok/s and 86K context.
On RTX A5000 24GB, Pixtral 12B can safely use up to 86K 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/pixtral-12b-on-a5000-24gb" 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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