Mixtral 8x7B needs ~32.7 GB but RX 6700 XT 12GB only has 12.0 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
20.7 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
2.2 tok/s
TTFT
89860 ms
Safe context
4K
Memory
32.7 GB / 12.0 GB
Offload
60%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 32.7 GB, but this setup only exposes 12.0 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 | 2.2 tok/s | 49015 ms | 4K |
| Coding | F | Too heavy | 2.0 tok/s | 96600 ms | 4K |
| Agentic Coding | F | Too heavy | 2.2 tok/s | 130706 ms | 4K |
| Reasoning | F | Too heavy | 2.2 tok/s | 106198 ms | 4K |
| RAG | F | Too heavy | 2.2 tok/s | 163382 ms | 4K |
How Mixtral 8x7B (47B params) fits at each quantization level on RX 6700 XT 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 18.3 GB | Low | F0 |
Q3_K_S | 3 | 23.0 GB | Low | F0 |
NVFP4 | 4 | 26.3 GB | Medium | F0 |
Q4_K_M | 4 | 28.7 GB | Medium | F0 |
Q5_K_M | 5 | 33.8 GB | High | F0 |
Q6_K | 6 | 38.5 GB | High | F0 |
Q8_0 | 8 | 50.3 GB | Very High | F0 |
F16 | 16 | 96.4 GB | Maximum | F0 |
アップグレードオプション
Makes the model fit on the accelerator instead of staying completely out of reach.
Raises estimated decode speed by about 700%.
〜$1,899 MSRP
Makes the model fit on the accelerator instead of staying completely out of reach.
Raises estimated decode speed by about 491%.
〜$2,249 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.
〜$3,999 MSRP
No, Mixtral 8x7B requires more memory than RX 6700 XT 12GB provides.
Mixtral 8x7B (47B parameters) requires approximately 32.7 GB of memory with Q4_K_M quantization.
The recommended quantization for Mixtral 8x7B is Q4_K_M, which balances quality and memory efficiency.
On RX 6700 XT 12GB, Mixtral 8x7B achieves approximately 2.0 tokens per second decode speed with a time-to-first-token of 96600ms using Q4_K_M quantization.
For coding workloads, Mixtral 8x7B on RX 6700 XT 12GB receives a F grade with 2.0 tok/s and 4K context.
On RX 6700 XT 12GB, Mixtral 8x7B can safely use up to 4K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.
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.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/mixtral-8x7b-on-rx-6700-xt-12gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
