Home / Can I run it? / Qwen3-8B / Qwen3-8B on an RTX 5070 Ti

Yes. Qwen3-8B at Q8_0 needs about 11.0 GB, and the GeForce RTX 5070 Ti has 16.0 GB usable at a ~4k context.

Can I run Qwen3-8B on an RTX 5070 Ti?

Qwen3-8B at Q8_0 needs about 11.0 GB, and the GeForce RTX 5070 Ti has 16.0 GB usable. That figure is 16 GB of VRAM on the spec sheet, of which 16.0 GB is usable for weights and cache, at 896 GB/s memory bandwidth. Alibaba’s 8B Qwen3. A strong small dense model, and a common upgrade from older 7B–8B weights. These are estimates from our formula, not measured benchmarks.

Quant that fits

Q8_0 Fits with headroom

Memory needed

11.0 GB at Q8_0, ~4k context

Usable VRAM

16.0 GB of 16 GB VRAM

Est. tokens/sec

62–88 estimate

Qwen3-8B · GeForce RTX 5070 Ti · Everything this machine runs · Q4 vs Q8 vs FP16

Memory at each quant

Estimated tokens per second

Estimate: 62–88 tokens/sec at Q8_0. This is a bandwidth-derived range, not a bench. Efficiency is a 60–85% GPU band from How we calculate.

Context headroom

At Q8_0, 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

• See the best GPU for this model family and the Qwen3-8B model page.

Other hardware for Qwen3-8B

• Qwen3-8B on an RTX 3060 12GBTight
• Qwen3-8B on an RTX 3070 TiFits
• Qwen3-8B on an RTX 3080Fits
• Qwen3-8B on an RTX 4060 Ti 16GBFits
• Qwen3-8B on an RTX 4070 Ti SuperFits
• Qwen3-8B on an RTX 4090Fits

Other models on an RTX 5070 Ti

• Qwen3-32B on an RTX 5070 TiWon’t fit
• Qwen3-30B-A3B on an RTX 5070 TiWon’t fit
• Qwen3.8-27B on an RTX 5070 TiWon’t fit
• Gemma 3 27B on an RTX 5070 TiWon’t fit
• Gemma 4 31B on an RTX 5070 TiWon’t fit
• gpt-oss-20b on an RTX 5070 TiTight