HomeCan I run it?Qwen3-8BQwen3-8B on an RTX 3060 12GB
Yes, but it is tight. Qwen3-8B at Q8_0 needs about 11.0 GB, and the GeForce RTX 3060 12GB has 12.0 GB usable at a ~4k context.
Can I run Qwen3-8B on an RTX 3060 12GB?
Qwen3-8B at Q8_0 needs about 11.0 GB, and the GeForce RTX 3060 12GB has 12.0 GB usable. That figure is 12 GB of VRAM on the spec sheet, of which 12.0 GB is usable for weights and cache, at 360 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, short context only
- Memory needed
- 11.0 GB at Q8_0, ~4k context
- Usable VRAM
- 12.0 GB of 12 GB VRAM
- Est. tokens/sec
- 25–35 estimate
Memory at each quant
| Quant | Need vs 12.0 GB | Verdict |
|---|---|---|
| Q4_K_M | 6.7 GB | Q4Fits |
| Q8_0 | 11.0 GB | Q8Tight |
| FP16 | 19.8 GB | FP16Won’t fit |
Estimated tokens per second
Estimate: 25–35 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 8k tokens under our KV estimate. Longer chats need more memory for the cache. Figures assume an FP16 KV cache.
| Context | KV cache (FP16) | Total at Q8_0 | Verdict |
|---|---|---|---|
| 4k | 0.6 GB | 11.0 GB | Tight |
| 8k | 1.2 GB | 11.6 GB | Tight |
| 16k | 2.4 GB | 12.8 GB | Won’t fit |
| 32k | 4.8 GB | 15.2 GB | Won’t fit |
| 64k | 9.7 GB | 20.1 GB | Won’t fit |
| 128k | 19.3 GB | 29.7 GB | Won’t fit |
What to do instead
- Run Llama 3.1 8B instead (6.6 GB at Q4). It is a different model, not a drop-in, but it does fit this machine.
- Keep context short, close other GPU work, and avoid a higher quant. The VRAM calculator shows how the KV cache grows.
- See the best GPU for this model family and the Qwen3-8B model page.
Other hardware for Qwen3-8B
- 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
- Qwen3-8B on an RTX 5070 TiFits
Other models on an RTX 3060 12GB
- Qwen3-32B on an RTX 3060 12GBWon’t fit
- Qwen3-30B-A3B on an RTX 3060 12GBWon’t fit
- Qwen3.8-27B on an RTX 3060 12GBWon’t fit
- Gemma 3 27B on an RTX 3060 12GBWon’t fit
- Gemma 4 31B on an RTX 3060 12GBWon’t fit
- gpt-oss-20b on an RTX 3060 12GBWon’t fit
Quick answers
- Can I run Qwen3-8B on an RTX 3060 12GB?
- Yes, but it is tight. Qwen3-8B at Q8_0 needs about 11.0 GB, and the GeForce RTX 3060 12GB has 12.0 GB usable.
- How much VRAM does Qwen3-8B need?
- About 6.7 GB at Q4_K_M, 11.0 GB at Q8_0 and 19.8 GB at FP16, estimated for a ~4k context.
- How fast is Qwen3-8B on an RTX 3060 12GB?
- Our estimate is 25–35 tokens per second at Q8_0. It is not a measured benchmark.
- What context length can I use?
- At Q8_0, our KV estimate supports up to about 8k tokens before the cache pushes the total over usable memory.