Ministral 8B needs ~9.5 GB VRAM. RTX 3500 Ada Laptop 12GB has 12.0 GB. With Q4_K_M quantization, expect ~54 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
54.0 tok/s
TTFT
3583 ms
Safe context
34K
Memory
9.5 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 | B | Runs well | 54.0 tok/s | 1954 ms | 34K |
| Coding | B | Runs well | 54.0 tok/s | 3583 ms | 34K |
| Agentic Coding | B | Runs with offload | 54.0 tok/s | 5212 ms | 34K |
| Reasoning | B | Runs well | 54.0 tok/s | 4235 ms | 34K |
| RAG | B | Runs with offload | 54.0 tok/s | 6515 ms | 34K |
How Ministral 8B (8B params) fits at each quantization level on RTX 3500 Ada Laptop 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | B59 |
Q3_K_S | 3 | 3.9 GB | Low | B60 |
NVFP4 | 4 | 4.5 GB | Medium | B61 |
Q4_K_M | 4 | 4.9 GB | Medium | B61 |
Q5_K_M | 5 | 5.8 GB | High | B62 |
Q6_K | 6 | 6.6 GB | High | B62 |
Q8_0Best for your GPU | 8 | 8.6 GB | Very High | B61 |
F16 | 16 | 16.4 GB | Maximum | F0 |
Copy-paste commands to run Ministral 8B on your machine.
Run
ollama run ministralYes, RTX 3500 Ada Laptop 12GB can run Ministral 8B with a B grade (Runs well). Expected decode speed: 54.0 tok/s.
Ministral 8B (8B parameters) requires approximately 9.5 GB of memory with Q4_K_M quantization.
The recommended quantization for Ministral 8B is Q4_K_M, which balances quality and memory efficiency.
On RTX 3500 Ada Laptop 12GB, Ministral 8B achieves approximately 54.0 tokens per second decode speed with a time-to-first-token of 3583ms using Q4_K_M quantization.
For coding workloads, Ministral 8B on RTX 3500 Ada Laptop 12GB receives a B grade with 54.0 tok/s and 34K context.
On RTX 3500 Ada Laptop 12GB, Ministral 8B can safely use up to 34K 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/ministral-8b-on-rtx-3500-ada-laptop-12gb" 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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