Qwen Qwen2 5 32B Instruct speed on RTX 4070 Ti Super and quantization-level VRAM fit.
RTX 4070 Ti Super does not meet the minimum VRAM requirement for Q4 inference of Qwen Qwen2 5 32B Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 4070 Ti Super lacks sufficient VRAM for comfortable Qwen Qwen2 5 32B Instruct operation with Q4 quantization.
Your 16GB GPU is 1GB short of the 17GB minimum.
Options: (1) Try Q2 or Q3 quantization for lower VRAM requirements, (2) Consider cloud GPU rental, (3) Upgrade to a GPU with at least 16GB VRAM.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 17GB | 16GB | 39.62 tok/s | ❌ Not recommended |
| Q8 | 33GB | 16GB | 27.73 tok/s | ❌ Not recommended |
| FP16 | 66GB | 16GB | 15.06 tok/s | ❌ Not recommended |
Check current pricing links for RTX 4070 Ti Super and similar cards.
Open RTX 4070 Ti Super buy links →Use workload-focused recommendations before committing to a purchase.
Browse best GPU guides →Compare complete systems if you want ready-to-run hardware.
Compare prebuilt systems →Your GPU doesn't meet the VRAM requirements. Run Qwen Qwen2 5 32B Instruct on cloud GPU instantly.
RTX 4070 Ti Super is not a comfortable Q4 fit for Qwen Qwen2 5 32B Instruct (about 17GB needed).
Q4 inference is estimated to need about 17GB VRAM on this page, while RTX 4070 Ti Super has 16GB available.
Try lower-bit quantization, choose a smaller model, or move to a higher-VRAM GPU from the alternatives list.