Ministral 3 8B needs ~10.9 GB VRAM. RTX 4070 Super 12GB has 12.0 GB. With Q4_K_M quantization, expect ~86 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
Tight fit
Decode
85.5 tok/s
TTFT
2265 ms
Safe context
24K
Memory
10.9 GB / 12.0 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 | S | Runs well | 85.5 tok/s | 1235 ms | 24K |
| Coding | A | Tight fit | 85.5 tok/s | 2265 ms | 24K |
| Agentic Coding | F | Too heavy | 53.5 tok/s | 5261 ms | 24K |
| Reasoning | A | Tight fit | 85.5 tok/s | 2676 ms | 24K |
| RAG | F | Too heavy | 53.5 tok/s | 6576 ms | 24K |
How Ministral 3 8B (8B params) fits at each quantization level on RTX 4070 Super 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | A80 |
Q3_K_S | 3 | 3.9 GB | Low | A81 |
NVFP4 | 4 | 4.5 GB | Medium | A82 |
Q4_K_M | 4 | 4.9 GB | Medium | A82 |
Q5_K_M | 5 | 5.8 GB | High | A83 |
Q6_K | 6 | 6.6 GB | High | A83 |
Q8_0Best for your GPU | 8 | 8.6 GB | Very High | A82 |
F16 | 16 | 16.4 GB | Maximum | F0 |
Copy-paste commands to run Ministral 3 8B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "mistralai/Ministral-3-8B-Instruct-2512" \
--hf-file "Ministral-3-8B-Instruct-2512-Q4_K_M.gguf" \
-c 4096 -ngl 99Yes, RTX 4070 Super 12GB can run Ministral 3 8B with a A grade (Tight fit). Expected decode speed: 85.5 tok/s.
Ministral 3 8B (8B parameters) requires approximately 10.9 GB of memory with Q4_K_M quantization.
The recommended quantization for Ministral 3 8B is Q4_K_M, which balances quality and memory efficiency.
On RTX 4070 Super 12GB, Ministral 3 8B achieves approximately 85.5 tokens per second decode speed with a time-to-first-token of 2265ms using Q4_K_M quantization.
For coding workloads, Ministral 3 8B on RTX 4070 Super 12GB receives a A grade with 85.5 tok/s and 24K context.
On RTX 4070 Super 12GB, Ministral 3 8B can safely use up to 24K tokens of context. The model's official context limit is 262K, 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/ministral-3-8b-on-rtx-4070-super-12gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: