Can the NVIDIA RTX 4090 run Mixtral 8x7B?
Yes, with heavy quantization
QuantQ2_KHeavily degraded
Memory19.2 GBof 24 GB
Speed~125tokens/s
Only just. Mixtral 8x7B fits on the NVIDIA RTX 4090 at Q2_K, which costs noticeable quality. Expect about 125 tokens/second. A card with more memory is a better experience.
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Memory needed by quantization
At 8,192 tokens of context.
| Quant | Quality | Memory | Fits? | Speed |
|---|---|---|---|---|
| FP16 | Full quality | 95.1 GB | Too big | — |
| Q8_0 | Near-lossless | 51.3 GB | Too big | — |
| Q6_K | Excellent | 40 GB | Too big | — |
| Q5_K_M | Very good | 34.9 GB | Too big | — |
| Q4_K_M | Good, most popular | 30 GB | Too big | — |
| Q3_K_M | Noticeably degraded | 24.5 GB | Too big | — |
| Q2_K | Heavily degraded | 19.2 GB | Fits | ~125 tok/s |
How to run Mixtral 8x7B on the NVIDIA RTX 4090
Ollama's default mixtral:8x7b download is Q4_K_M, which needs about 30 GB, more than the 24 GB available. Download the Q2_K GGUF instead (LM Studio lists quants per model), or try a smaller context length.
GPUs that run Mixtral 8x7B comfortably
- NVIDIA RTX 5090 (32 GB)
- Apple M4 Pro (48GB)
- Apple M3 Max (64GB)
- Apple M4 Max (128GB)
- Apple M2 Ultra (192GB)