Pixtral 12B needs ~11.9 GB VRAM. RTX 3080 Ti 12GB has 12.0 GB. With Q4_K_M quantization, expect ~92 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 with offload
Decode
97.1 tok/s
TTFT
1993 ms
Safe context
17K
Memory
11.9 GB / 12.0 GB
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Tight fit | 97.1 tok/s | 1087 ms | 17K |
| Coding | A | Runs with offload | 92.2 tok/s | 2100 ms | 17K |
| Agentic Coding | B | Very compromised (needs ~1.2 GB host RAM) | 50.3 tok/s | 5594 ms | 17K |
| Reasoning | A | Runs with offload | 97.1 tok/s | 2356 ms | 17K |
| RAG | B | Very compromised (needs ~1.2 GB host RAM) | 50.3 tok/s | 6992 ms |
How Pixtral 12B (12B params) fits at each quantization level on RTX 3080 Ti 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.7 GB | Low | A75 |
Q3_K_S | 3 | 5.9 GB | Low | A76 |
NVFP4 | 4 |
Copy-paste commands to run Pixtral 12B on your machine.
Run
ollama run pixtralYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3 14B | 14B | A | 52.3 tok/s | |
 Phi-4-reasoning-plus 14B | 14.7B | A | 41.5 tok/s |
Yes, RTX 3080 Ti 12GB can run Pixtral 12B with a A grade (Runs with offload). Expected decode speed: 92.2 tok/s.
Pixtral 12B (12B parameters) requires approximately 11.9 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 3080 Ti 12GB, Pixtral 12B achieves approximately 92.2 tokens per second decode speed with a time-to-first-token of 2100ms using Q4_K_M quantization.
For coding workloads, Pixtral 12B on RTX 3080 Ti 12GB receives a A grade with 92.2 tok/s and 17K context.
On RTX 3080 Ti 12GB, Pixtral 12B can safely use up to 17K 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-rtx-3080-ti-12gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 17K |
6.7 GB |
| Medium |
| A76 |
Q4_K_M | 4 | 7.3 GB | Medium | A75 |
Q5_K_MBest for your GPU | 5 | 8.6 GB | High | A75 |
Q6_K | 6 | 9.8 GB | High | F0 |
Q8_0 | 8 | 12.8 GB | Very High | F0 |
F16 | 16 | 24.6 GB | Maximum | F0 |
 Ministral 3 14B | 14B | A | 52.1 tok/s |
| Phi-4 14B | 14B | A | 47.3 tok/s |
| Qwen 2.5 14B | 14B | A | 48.4 tok/s |
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.