Can I run this LLM?
Can a NVIDIA A100 (80GB) run GLM-4 9B?
GLM · MIT · estimated for a 80.0 GB machine at 4K context.
Yes — it runs great.
Runs greatBest fit: GLM-4 9B at FP16 · 18.8 GB weights · 65–98 tok/s on a NVIDIA A100 (80GB).
Arena Text Overall · style-controlled
UnratedNo exact matchNo reviewed exact Arena match
No reviewed exact model/configuration match in the Arena Text Overall style-controlled snapshot. No family or editorial score is substituted. Local quantization quality is unmeasured.
Snapshot published 2026-10-08 · snapshot imported 2026-10-11 UTC · validated last-good data · manual refresh
Arena leaderboard dataset · Arena / lmarena-ai, Arena Leaderboard Dataset (CC BY 4.0). Selected Text Overall style-controlled rows; field names adapted, ratings unchanged. · dataset CC BY 4.0 · revision e16f90232986
- Total memory at 4K context
- 19.8 GB
- Weights + KV cache + runtime overhead
- Estimated generation
- 65–98 tok/s
- Estimated first token
- ~0.8s
Every quantization on this machine
On small screens, each quant lists every metric below its name. On wider screens, scroll sideways for total memory, speed and fit. Keyboard: focus the table, then use the arrow keys. Quant names stay visible.
| Quant | Weights | Total memory | Speed | Fit |
|---|---|---|---|---|
| Q2_K | 4.0 GB | 5.0 GB | 182–273 tok/s | Runs great |
| Q3_K_M | 5.0 GB | 5.9 GB | 163–244 tok/s | Runs great |
| Q4_K_M | 6.2 GB | 7.1 GB | 144–216 tok/s | Runs great |
| Q5_K_M | 7.1 GB | 8.0 GB | 133–199 tok/s | Runs great |
| Q6_K | 8.3 GB | 9.2 GB | 120–180 tok/s | Runs great |
| Q8_0 | 10.0 GB | 11.0 GB | 106–158 tok/s | Runs great |
| FP16 | 18.8 GB | 19.8 GB | 65–98 tok/s | Runs great |
Ran GLM-4 9B on a NVIDIA A100 (80GB)? Add your real numbers →