HomeCan I run it?Mixtral 8x22BMixtral 8x22B on an RTX 5090
No. Mixtral 8x22B at Q4_K_M needs about 99.0 GB, and the GeForce RTX 5090 has 32.0 GB usable at a ~4k context.
Can I run Mixtral 8x22B on an RTX 5090?
Mixtral 8x22B at Q4_K_M needs about 99.0 GB, and the GeForce RTX 5090 has 32.0 GB usable. That figure is 32 GB of VRAM on the spec sheet, of which 32.0 GB is usable for weights and cache, at 1792 GB/s memory bandwidth. Mixtral 8x22B, a large Mixture-of-Experts. Total weights need a high-memory box; only a fraction is active per token. These are estimates from our formula, not measured benchmarks.
- Quant that fits
- None of Q4, Q8 or FP16 needs 99.0 GB
- Memory needed
- 99.0 GB at Q4_K_M, ~4k context
- Usable VRAM
- 32.0 GB of 32 GB VRAM
- Est. tokens/sec
- n/a does not fit
Memory at each quant
| Quant | Need vs 32.0 GB | Verdict |
|---|---|---|
| Q4_K_M | 99.0 GB | Q4Won’t fit |
| Q8_0 | 172.8 GB | Q8Won’t fit |
| FP16 | 324.4 GB | FP16Won’t fit |
Estimated tokens per second
No speed estimate: Mixtral 8x22B does not fit in the 32.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.
Context headroom
Even at a short ~4k context, the weights do not fit. Extending context would only increase the gap.
| Context | KV cache (FP16) | Total at Q4_K_M | Verdict |
|---|---|---|---|
| 4k | 0.9 GB | 99.0 GB | Won’t fit |
| 8k | 1.9 GB | 100.0 GB | Won’t fit |
| 16k | 3.8 GB | 101.9 GB | Won’t fit |
| 32k | 7.5 GB | 105.6 GB | Won’t fit |
| 64k | 15.0 GB | 113.1 GB | Won’t fit |
| 128k | 30.1 GB | 128.2 GB | Won’t fit |
What to do instead
- Run R1 Distill 32B instead (23.8 GB at Q4). It is a different model, not a drop-in, but it does fit this machine.
- To hold Mixtral 8x22B at Q4, you need about 99.0 GB. The Mac Studio M5 Ultra 256GB has 192.0 GB usable ($9499 Apple list price, M5 Ultra 30C CPU/64C GPU, 256GB/1TB).
- CPU offload can load the weights anyway, but it is slow. We do not publish an offload tokens/sec figure.
- Full hardware list: Mixtral-8x22B-Instruct-v0.1. Specs for this machine: GeForce RTX 5090.
Other hardware for Mixtral 8x22B
- Mixtral 8x22B on an RTX 4090Won’t fit
- Mixtral 8x22B on dual RTX 3090sWon’t fit
- Mixtral 8x22B on a Mac Studio 256GBTight
- Mixtral 8x22B on a Mac mini 64GBWon’t fit
Other models on an RTX 5090
- Qwen3-32B on an RTX 5090Fits
- Qwen3-30B-A3B on an RTX 5090Fits
- Qwen3.8-27B on an RTX 5090Fits
- Gemma 3 27B on an RTX 5090Fits
- Gemma 4 31B on an RTX 5090Fits
- gpt-oss-20b on an RTX 5090Fits
Quick answers
- Can I run Mixtral 8x22B on an RTX 5090?
- No. Mixtral 8x22B at Q4_K_M needs about 99.0 GB, and the GeForce RTX 5090 has 32.0 GB usable.
- How much VRAM does Mixtral 8x22B need?
- About 99.0 GB at Q4_K_M, 172.8 GB at Q8_0 and 324.4 GB at FP16, estimated for a ~4k context.
- How fast is Mixtral 8x22B on an RTX 5090?
- We do not estimate tokens/sec when the model does not fit. CPU offload is possible but slow.
- What context length can I use?
- The weights already do not fit, so longer context is not the limiting factor.