Ministral 8B needs ~10.7 GB VRAM. RTX 4500 Ada 24GB has 24.0 GB. With Q4_K_M quantization, expect ~75 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
75.2 tok/s
TTFT
2575 ms
Safe context
113K
Memory
10.7 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 | B | Runs well | 75.2 tok/s | 1405 ms | 113K |
| Coding | B | Runs well | 75.2 tok/s | 2575 ms | 113K |
| Agentic Coding | B | Runs well | 75.2 tok/s | 3746 ms | 113K |
| Reasoning | B | Runs well | 75.2 tok/s | 3043 ms | 113K |
| RAG | B | Runs well | 75.2 tok/s | 4682 ms | 113K |
How Ministral 8B (8B params) fits at each quantization level on RTX 4500 Ada 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C54 |
Q3_K_S | 3 | 3.9 GB | Low | C54 |
NVFP4 | 4 | 4.5 GB | Medium | C55 |
Q4_K_M | 4 | 4.9 GB | Medium | C55 |
Q5_K_M | 5 | 5.8 GB | High | B55 |
Q6_K | 6 | 6.6 GB | High | B56 |
Q8_0 | 8 | 8.6 GB | Very High | B57 |
F16Best for your GPU | 16 | 16.4 GB | Maximum | B59 |
Copy-paste commands to run Ministral 8B on your machine.
Run
ollama run ministralYes, RTX 4500 Ada 24GB can run Ministral 8B with a B grade (Runs well). Expected decode speed: 75.2 tok/s.
Ministral 8B (8B parameters) requires approximately 10.7 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 4500 Ada 24GB, Ministral 8B achieves approximately 75.2 tokens per second decode speed with a time-to-first-token of 2575ms using Q4_K_M quantization.
For coding workloads, Ministral 8B on RTX 4500 Ada 24GB receives a B grade with 75.2 tok/s and 113K context.
On RTX 4500 Ada 24GB, Ministral 8B can safely use up to 113K 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-4500-ada-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: