HomeCan I run it?Qwen3-30B-A3BQwen3-30B-A3B on an RTX 5070 Ti
No. Qwen3-30B-A3B at Q4_K_M needs about 22.3 GB, and the GeForce RTX 5070 Ti has 16.0 GB usable at a ~4k context.
Can I run Qwen3-30B-A3B on an RTX 5070 Ti?
Qwen3-30B-A3B at Q4_K_M needs about 22.3 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. A Qwen3 Mixture-of-Experts with 30B total weights and about 3B active per token, so it needs 30B-class memory but can decode closer to a small dense model. These are estimates from our formula, not measured benchmarks.
- Quant that fits
- None of Q4, Q8 or FP16 needs 22.3 GB
- Memory needed
- 22.3 GB at Q4_K_M, ~4k context
- Usable VRAM
- 16.0 GB of 16 GB VRAM
- Est. tokens/sec
- n/a does not fit
Memory at each quant
| Quant | Need vs 16.0 GB | Verdict |
|---|---|---|
| Q4_K_M | 22.3 GB | Q4Won’t fit |
| Q8_0 | 38.3 GB | Q8Won’t fit |
| FP16 | 71.2 GB | FP16Won’t fit |
Estimated tokens per second
No speed estimate: Qwen3-30B-A3B does not fit in the 16.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.
Context headroom
Even at a short ~4k context, the weights do not fit. Extending context would only increase the gap.
| Context | KV cache (FP16) | Total at Q4_K_M | Verdict |
|---|---|---|---|
| 4k | 0.4 GB | 22.3 GB | Won’t fit |
| 8k | 0.8 GB | 22.7 GB | Won’t fit |
| 16k | 1.6 GB | 23.5 GB | Won’t fit |
| 32k | 3.2 GB | 25.1 GB | Won’t fit |
| 64k | 6.4 GB | 28.3 GB | Won’t fit |
| 128k | 12.9 GB | 34.8 GB | Won’t fit |
What to do instead
- Run gpt-oss-20b instead (15.6 GB at Q4). It is a different model, not a drop-in, but it does fit this machine.
- To hold Qwen3-30B-A3B at Q4, you need about 22.3 GB. The GeForce RTX 3090 has 24.0 GB usable ($1499 list price).
- CPU offload can load the weights anyway, but it is slow. We do not publish an offload tokens/sec figure.
- See the best GPU for this model family and the Qwen3-30B-A3B model page.
Other hardware for Qwen3-30B-A3B
- Qwen3-30B-A3B on an RTX 3060 12GBWon’t fit
- Qwen3-30B-A3B on an RTX 3070 TiWon’t fit
- Qwen3-30B-A3B on an RTX 3080Won’t fit
- Qwen3-30B-A3B on an RTX 3090Tight
- Qwen3-30B-A3B on an RTX 4060 Ti 16GBWon’t fit
- Qwen3-30B-A3B on an RTX 4070 Ti SuperWon’t fit
Other models on an RTX 5070 Ti
- Qwen3-32B 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
- Mistral Small 24B on an RTX 5070 TiWon’t fit
Quick answers
- Can I run Qwen3-30B-A3B on an RTX 5070 Ti?
- No. Qwen3-30B-A3B at Q4_K_M needs about 22.3 GB, and the GeForce RTX 5070 Ti has 16.0 GB usable.
- How much VRAM does Qwen3-30B-A3B need?
- About 22.3 GB at Q4_K_M, 38.3 GB at Q8_0 and 71.2 GB at FP16, estimated for a ~4k context.
- How fast is Qwen3-30B-A3B on an RTX 5070 Ti?
- We do not estimate tokens/sec when the model does not fit. CPU offload is possible but slow.
- What context length can I use?
- The weights already do not fit, so longer context is not the limiting factor.