Pixtral 12B needs ~12.6 GB VRAM. NVIDIA A2 16GB has 16.0 GB. With Q4_K_M quantization, expect ~23 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
22.9 tok/s
TTFT
8451 ms
Safe context
39K
Memory
12.6 GB / 16.0 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 | 22.9 tok/s | 4609 ms | 39K |
| Coding | A | Runs well | 22.9 tok/s | 8451 ms | 39K |
| Agentic Coding | A | Tight fit | 22.9 tok/s | 12292 ms | 39K |
| Reasoning | A | Runs well | 22.9 tok/s | 9987 ms | 39K |
| RAG | A | Tight fit | 22.9 tok/s | 15365 ms | 39K |
How Pixtral 12B (12B params) fits at each quantization level on NVIDIA A2 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.7 GB | Low | A72 |
Q3_K_S | 3 | 5.9 GB | Low | A73 |
NVFP4 | 4 | 6.7 GB | Medium | A74 |
Q4_K_M | 4 | 7.3 GB | Medium | A75 |
Q5_K_M | 5 | 8.6 GB | High | A75 |
Q6_KBest for your GPU | 6 | 9.8 GB | High | A75 |
Q8_0 | 8 | 12.8 GB | Very High | F0 |
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 |
|---|---|---|---|---|
 Qwen 3 14B | 14B | S | 19.7 tok/s | |
 Phi-4-reasoning-plus 14B | 14.7B | S | 18.7 tok/s | |
 GPT-OSS 20B | 21B | A | 17.4 tok/s | |
 Ministral 3 14B | 14B | A | 19.6 tok/s | |
| Codestral 2 25.08 | 22B | B | 6.8 tok/s |
Yes, NVIDIA A2 16GB can run Pixtral 12B with a A grade (Runs well). Expected decode speed: 22.9 tok/s.
Pixtral 12B (12B parameters) requires approximately 12.6 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 NVIDIA A2 16GB, Pixtral 12B achieves approximately 22.9 tokens per second decode speed with a time-to-first-token of 8451ms using Q4_K_M quantization.
For coding workloads, Pixtral 12B on NVIDIA A2 16GB receives a A grade with 22.9 tok/s and 39K context.
On NVIDIA A2 16GB, Pixtral 12B can safely use up to 39K 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-a2-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: