Home / Can I run it? / Gemma 4 31B / Gemma 4 31B on an RTX 5090

Yes. Gemma 4 31B at Q4_K_M needs about 22.8 GB, and the GeForce RTX 5090 has 32.0 GB usable at a ~4k context.

Can I run Gemma 4 31B on an RTX 5090?

Gemma 4 31B at Q4_K_M needs about 22.8 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. Google’s dense Gemma 4 31B. Close in memory to Qwen3-32B, with a different training mix. These are estimates from our formula, not measured benchmarks.

Quant that fits

Q4_K_M Fits with headroom

Memory needed

22.8 GB at Q4_K_M, ~4k context

Usable VRAM

32.0 GB of 32 GB VRAM

Est. tokens/sec

57–80 estimate

Gemma 4 31B · GeForce RTX 5090 · Everything this machine runs · Q4 vs Q8 vs FP16

Memory at each quant

Estimated tokens per second

Estimate: 57–80 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

We do not have a published KV config for this model, so the memory need is the ~4k-context estimate only. Use the VRAM calculator to explore longer chats.

What to do instead

• Q8_0 needs 39.2 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 Gemma 4 31B model page.

Other hardware for Gemma 4 31B

• Gemma 4 31B on an RTX 3060 12GBWon’t fit
• Gemma 4 31B on an RTX 3070 TiWon’t fit
• Gemma 4 31B on an RTX 3080Won’t fit
• Gemma 4 31B on an RTX 3090Tight
• Gemma 4 31B on an RTX 4060 Ti 16GBWon’t fit
• Gemma 4 31B on an RTX 4070 Ti SuperWon’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
• gpt-oss-20b on an RTX 5090Fits
• Mistral Small 24B on an RTX 5090Tight