Ministral 3 8B needs ~10.3 GB but Radeon RX 7700S 8GB only has 8.0 GB. Try a smaller quantization or lighter model.
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
2.3 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
13.3 tok/s
TTFT
14606 ms
Safe context
4K
Memory
10.3 GB / 8.0 GB
Offload
20%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 10.3 GB, but this setup only exposes 8.0 GB of usable VRAM.
Add more VRAM headroom
The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | F | Too heavy | 16.8 tok/s | 6279 ms | 4K |
| Coding | F | Too heavy | 13.3 tok/s | 14606 ms | 4K |
| Agentic Coding | F | Too heavy | 8.8 tok/s | 31943 ms | 4K |
| Reasoning | F | Too heavy | 13.3 tok/s | 17261 ms | 4K |
| RAG | F | Too heavy | 8.8 tok/s | 39929 ms | 4K |
How Ministral 3 8B (8B params) fits at each quantization level on Radeon RX 7700S 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | A84 |
Q3_K_S | 3 | 3.9 GB | Low | A84 |
NVFP4 | 4 |
Upgrade options
Makes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
~$329 MSRP
Makes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
~$349 MSRP
Makes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
~$449 MSRP
No, Ministral 3 8B requires more memory than Radeon RX 7700S 8GB provides.
Ministral 3 8B (8B parameters) requires approximately 10.3 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 Radeon RX 7700S 8GB, Ministral 3 8B achieves approximately 13.3 tokens per second decode speed with a time-to-first-token of 14606ms using Q4_K_M quantization.
For coding workloads, Ministral 3 8B on Radeon RX 7700S 8GB receives a F grade with 13.3 tok/s and 4K context.
On Radeon RX 7700S 8GB, Ministral 3 8B can safely use up to 4K 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-rx-7700s-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| Medium |
| A84 |
Q4_K_MBest for your GPU | 4 | 4.9 GB | Medium | A83 |
Q5_K_M | 5 | 5.8 GB | High | F0 |
Q6_K | 6 | 6.6 GB | High | F0 |
Q8_0 | 8 | 8.6 GB | Very High | F0 |
F16 | 16 | 16.4 GB | Maximum | F0 |
Add more VRAM headroom. The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
