HomeCan I run it?Qwen3-235BQwen3-235B on an RTX 4090
No. Qwen3-235B at Q4_K_M needs about 164.9 GB, and the GeForce RTX 4090 has 24.0 GB usable at a ~4k context.
Can I run Qwen3-235B on an RTX 4090?
Qwen3-235B at Q4_K_M needs about 164.9 GB, and the GeForce RTX 4090 has 24.0 GB usable. That figure is 24 GB of VRAM on the spec sheet, of which 24.0 GB is usable for weights and cache, at 1008 GB/s memory bandwidth. Qwen3’s large Mixture-of-Experts (235B total, about 22B active). It needs a high-memory unified machine at Q4, not a single consumer GPU. These are estimates from our formula, not measured benchmarks.
- Quant that fits
- None of Q4, Q8 or FP16 needs 164.9 GB
- Memory needed
- 164.9 GB at Q4_K_M, ~4k context
- Usable VRAM
- 24.0 GB of 24 GB VRAM
- Est. tokens/sec
- n/a does not fit
Memory at each quant
| Quant | Need vs 24.0 GB | Verdict |
|---|---|---|
| Q4_K_M | 164.9 GB | Q4Won’t fit |
| Q8_0 | 288.3 GB | Q8Won’t fit |
| FP16 | 541.7 GB | FP16Won’t fit |
Estimated tokens per second
No speed estimate: Qwen3-235B does not fit in the 24.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.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 | 0.8 GB | 164.9 GB | Won’t fit |
| 8k | 1.6 GB | 165.7 GB | Won’t fit |
| 16k | 3.2 GB | 167.3 GB | Won’t fit |
| 32k | 6.3 GB | 170.4 GB | Won’t fit |
| 64k | 12.6 GB | 176.7 GB | Won’t fit |
| 128k | 25.2 GB | 189.3 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 Qwen3-235B at Q4, you need about 164.9 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 We do not publish an offload tokens/sec figure.
- See the best GPU for this model family and the Qwen3-235B-A22B model page.
Other hardware for Qwen3-235B
- Qwen3-235B on a Mac Studio 256GBFits
- Qwen3-235B on a Mac Studio 512GBFits
- Qwen3-235B on dual RTX 3090sWon’t fit
- Qwen3-235B on an RTX 5090Won’t fit
- Qwen3-235B on a Mac mini 64GBWon’t fit
Other models on an RTX 4090
- Qwen3-32B on an RTX 4090Tight
- Qwen3-30B-A3B on an RTX 4090Tight
- Qwen3.8-27B on an RTX 4090Fits
- Gemma 3 27B on an RTX 4090Fits
- Gemma 4 31B on an RTX 4090Tight
- gpt-oss-20b on an RTX 4090Fits
Quick answers
- Can I run Qwen3-235B on an RTX 4090?
- No. Qwen3-235B at Q4_K_M needs about 164.9 GB, and the GeForce RTX 4090 has 24.0 GB usable.
- How much VRAM does Qwen3-235B need?
- About 164.9 GB at Q4_K_M, 288.3 GB at Q8_0 and 541.7 GB at FP16, estimated for a ~4k context.
- How fast is Qwen3-235B on an RTX 4090?
- 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.