Can I run this LLM?
Can a NVIDIA H100 SXM (80GB) run Llama 3.2 3B?
Llama · Llama 3.2 Community · estimated for a 80.0 GB machine at 4K context.
Yes — it runs great.
Runs greatBest fit: Llama 3.2 3B at FP16 · 6.4 GB weights · 181–272 tok/s on a NVIDIA H100 SXM (80GB).
Arena Text Overall · style-controlled
1,167FP16 untestedllama-3.2-3b-instruct · published configuration reference · FP16 not tested
Arena Text Overall (style-controlled), exact published entry llama-3.2-3b-instruct, 2026-10-08: reference rating 1,166.8. Published confidence bounds 1,159.1–1,174.5. 7,936 votes. Published llama-3.2-3b-instruct configuration reference. Reasoning mode is not disclosed by the Arena dataset. Tested precision, runtime and sampling settings are not disclosed in this dataset. Selected FP16 has not been measured by this Arena entry. No quantization quality adjustment is applied.
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
- 7.7 GB
- Weights + KV cache + runtime overhead
- Estimated generation
- 181–272 tok/s
- Estimated first token
- ~0.2s
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 |
|---|---|---|---|---|
| Q4_K_M | 2.0 GB | 3.3 GB | 268–402 tok/s | Runs great |
| Q5_K_M | 2.3 GB | 3.6 GB | 260–389 tok/s | Runs great |
| Q6_K | 2.6 GB | 3.9 GB | 251–377 tok/s | Runs great |
| Q8_0 | 3.4 GB | 4.7 GB | 233–349 tok/s | Runs great |
| FP16 | 6.4 GB | 7.7 GB | 181–272 tok/s | Runs great |
Ran Llama 3.2 3B on a NVIDIA H100 SXM (80GB)? Add your real numbers →