HomeCan I run it?Qwen3-14BQwen3-14B on an RTX 4070 Ti Super
Yes. Qwen3-14B at Q4_K_M needs about 11.3 GB, and the GeForce RTX 4070 Ti Super has 16.0 GB usable at a ~4k context.
Can I run Qwen3-14B on an RTX 4070 Ti Super?
Qwen3-14B at Q4_K_M needs about 11.3 GB, and the GeForce RTX 4070 Ti Super 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 672 GB/s memory bandwidth. Alibaba’s 14B Qwen3. It sits in the sweet spot for 12–16 GB cards that want more quality than an 8B. These are estimates from our formula, not measured benchmarks.
- Quant that fits
- Q4_K_M Fits with headroom
- Memory needed
- 11.3 GB at Q4_K_M, ~4k context
- Usable VRAM
- 16.0 GB of 16 GB VRAM
- Est. tokens/sec
- 45–64 estimate
Memory at each quant
| Quant | Need vs 16.0 GB | Verdict |
|---|---|---|
| Q4_K_M | 11.3 GB | Q4Fits |
| Q8_0 | 19.0 GB | Q8Won’t fit |
| FP16 | 35.0 GB | FP16Won’t fit |
Estimated tokens per second
Estimate: 45–64 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
At Q4_K_M, 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.
| Context | KV cache (FP16) | Total at Q4_K_M | Verdict |
|---|---|---|---|
| 4k | 0.7 GB | 11.3 GB | Fits |
| 8k | 1.3 GB | 12.0 GB | Fits |
| 16k | 2.7 GB | 13.3 GB | Fits |
| 32k | 5.4 GB | 16.0 GB | Tight |
| 64k | 10.7 GB | 21.4 GB | Won’t fit |
| 128k | 21.5 GB | 32.1 GB | Won’t fit |
What to do instead
- Q8_0 needs 19.0 GB and does not fit here. The Radeon RX 7900 XT has 20.0 GB usable, enough for Q8.
- See the best GPU for this model family and the Qwen3-14B model page.
Other hardware for Qwen3-14B
- Qwen3-14B on an RTX 3060 12GBTight
- Qwen3-14B on an RTX 3070 TiWon’t fit
- Qwen3-14B on an RTX 3080Won’t fit
- Qwen3-14B on an RTX 4060 Ti 16GBFits
- Qwen3-14B on an RTX 4090Fits
- Qwen3-14B on an RTX 5070 TiFits
Other models on an RTX 4070 Ti Super
- Qwen3-32B on an RTX 4070 Ti SuperWon’t fit
- Qwen3-30B-A3B on an RTX 4070 Ti SuperWon’t fit
- Qwen3.8-27B on an RTX 4070 Ti SuperWon’t fit
- Gemma 3 27B on an RTX 4070 Ti SuperWon’t fit
- Gemma 4 31B on an RTX 4070 Ti SuperWon’t fit
- gpt-oss-20b on an RTX 4070 Ti SuperTight
Quick answers
- Can I run Qwen3-14B on an RTX 4070 Ti Super?
- Yes. Qwen3-14B at Q4_K_M needs about 11.3 GB, and the GeForce RTX 4070 Ti Super has 16.0 GB usable.
- How much VRAM does Qwen3-14B need?
- About 11.3 GB at Q4_K_M, 19.0 GB at Q8_0 and 35.0 GB at FP16, estimated for a ~4k context.
- How fast is Qwen3-14B on an RTX 4070 Ti Super?
- Our estimate is 45–64 tokens per second at Q4_K_M. It is not a measured benchmark.
- What context length can I use?
- At Q4_K_M, our KV estimate supports up to about 32k tokens before the cache pushes the total over usable memory.