Zai Org Glm 4 7 speed on RTX 4080 Super and quantization-level VRAM fit.
RTX 4080 Super does not meet the minimum VRAM requirement for Q4 inference of Zai Org Glm 4 7. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 4080 Super lacks sufficient VRAM for comfortable Zai Org Glm 4 7 operation with Q4 quantization.
Your 16GB GPU is 164GB short of the 180GB 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 | 180GB | 16GB | 15.20 tok/s | ❌ Not recommended |
| Q8 | 359GB | 16GB | 10.64 tok/s | ❌ Not recommended |
| FP16 | 717GB | 16GB | 5.78 tok/s | ❌ Not recommended |
Check current pricing links for RTX 4080 Super and similar cards.
Open RTX 4080 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 Zai Org Glm 4 7 on cloud GPU instantly.
RTX 4080 Super is not a comfortable Q4 fit for Zai Org Glm 4 7 (about 180GB needed).
Q4 inference is estimated to need about 180GB VRAM on this page, while RTX 4080 Super has 16GB available.
Try lower-bit quantization, choose a smaller model, or move to a higher-VRAM GPU from the alternatives list.