Home / Can I run it? / Qwen3.8-27B / Qwen3.8-27B on an RTX 3090

Yes. Qwen3.8-27B at Q4_K_M needs about 20.4 GB, and the GeForce RTX 3090 has 24.0 GB usable at a ~4k context.

Can I run Qwen3.8-27B on an RTX 3090?

Qwen3.8-27B at Q4_K_M needs about 20.4 GB, and the GeForce RTX 3090 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 936 GB/s memory bandwidth. Alibaba’s denser Qwen3.8 27B, a newer mid-size chat model in the same memory class as Gemma 3 27B. These are estimates from our formula, not measured benchmarks.

Quant that fits

Q4_K_M Fits with headroom

Memory needed

20.4 GB at Q4_K_M, ~4k context

Usable VRAM

24.0 GB of 24 GB VRAM

Est. tokens/sec

33–47 estimate

Qwen3.8-27B · GeForce RTX 3090 · Everything this machine runs · Q4 vs Q8 vs FP16

Memory at each quant

Estimated tokens per second

Estimate: 33–47 tokens/sec at Q4_K_M. This is a bandwidth-derived range, not a bench. Efficiency is a 60–85% GPU band from How we calculate.

Context headroom

At Q4_K_M, this machine has headroom out to about 32k tokens under our KV estimate. Longer chats need more memory for the cache. Figures assume an FP16 KV cache.

From the model’s config. Try other sizes in the VRAM calculator or see the context length guide.

What to do instead

• Q8_0 needs 34.9 GB and does not fit here. The Mac mini M5 Pro 64GB has 48.0 GB usable, enough for Q8.
• See the best GPU for this model family and the Qwen3.8-27B model page.

Other hardware for Qwen3.8-27B

• Qwen3.8-27B on an RTX 3060 12GBWon’t fit
• Qwen3.8-27B on an RTX 3070 TiWon’t fit
• Qwen3.8-27B on an RTX 3080Won’t fit
• Qwen3.8-27B on an RTX 4060 Ti 16GBWon’t fit
• Qwen3.8-27B on an RTX 4070 Ti SuperWon’t fit
• Qwen3.8-27B on an RTX 4090Fits

Other models on an RTX 3090

• Qwen3-32B on an RTX 3090Tight
• Qwen3-30B-A3B on an RTX 3090Tight
• Gemma 3 27B on an RTX 3090Fits
• Gemma 4 31B on an RTX 3090Tight
• gpt-oss-20b on an RTX 3090Fits
• Mistral Small 24B on an RTX 3090Fits