Home / Can I run it? / R1 Distill 7B / R1 Distill 7B on an RTX 4090

Yes. R1 Distill 7B at FP16 needs about 18.5 GB, and the GeForce RTX 4090 has 24.0 GB usable at a ~4k context.

Can I run R1 Distill 7B on an RTX 4090?

R1 Distill 7B at FP16 needs about 18.5 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. A 7B DeepSeek-R1 distill on Qwen. It is a reasoning-tuned small model, not the full 671B R1. These are estimates from our formula, not measured benchmarks.

Quant that fits

FP16 Fits with headroom

Memory needed

18.5 GB at FP16, ~4k context

Usable VRAM

24.0 GB of 24 GB VRAM

Est. tokens/sec

40–56 estimate

DeepSeek-R1-Distill-Qwen-7B · GeForce RTX 4090 · Everything this machine runs · Q4 vs Q8 vs FP16

Memory at each quant

Estimated tokens per second

Estimate: 40–56 tokens/sec at FP16. This is a bandwidth-derived range, not a bench. Efficiency is a 60–85% GPU band from How we calculate.

Context headroom

At FP16, this machine has headroom out to about 64k 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

• See the best GPU for this model family and the DeepSeek-R1-Distill-Qwen-7B model page.

Other hardware for R1 Distill 7B

• R1 Distill 7B on an RTX 3060 12GBFits
• R1 Distill 7B on an RTX 3070 TiFits
• R1 Distill 7B on an Arc B580Fits
• R1 Distill 7B on a Mac mini 16GBFits

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