Can I run this LLM?
Can a NVIDIA RTX 3080 (10GB) run Llama 3.2 3B?
Llama · Llama 3.2 Community · estimated for a 10.0 GB machine at 4K context.
Yes — it runs great.
Runs greatBest fit: Llama 3.2 3B at FP16 · 6.4 GB weights · 67–100 tok/s on a NVIDIA RTX 3080 (10GB).
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
- 67–100 tok/s
- Estimated first token
- ~1.4s
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 | 140–209 tok/s | Runs great |
| Q5_K_M | 2.3 GB | 3.6 GB | 130–195 tok/s | Runs great |
| Q6_K | 2.6 GB | 3.9 GB | 121–181 tok/s | Runs great |
| Q8_0 | 3.4 GB | 4.7 GB | 104–155 tok/s | Runs great |
| FP16 | 6.4 GB | 7.7 GB | 67–100 tok/s | Runs great |
Ran Llama 3.2 3B on a NVIDIA RTX 3080 (10GB)? Add your real numbers →