Can I run this LLM?
Can a NVIDIA RTX 3050 Laptop (4GB) run Llama 3.2 3B?
Llama · Llama 3.2 Community · estimated for a 4.0 GB machine at 4K context.
Yes, but it's tight.
Tight / slowBest fit: Llama 3.2 3B at Q5_K_M · 2.3 GB weights · 45–67 tok/s on a NVIDIA RTX 3050 Laptop (4GB).
Arena Text Overall · style-controlled
1,167Q5_K_M untestedllama-3.2-3b-instruct · published configuration reference · Q5_K_M 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 Q5_K_M 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
- 3.6 GB
- Weights + KV cache + runtime overhead
- Estimated generation
- 45–67 tok/s
- Estimated first token
- ~7.5s
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 | 49–74 tok/s | Tight / slow |
| Q5_K_M | 2.3 GB | 3.6 GB | 45–67 tok/s | Tight / slow |
| Q6_K | 2.6 GB | 3.9 GB | — not resident | Won't fit |
| Q8_0 | 3.4 GB | 4.7 GB | — not resident | Won't fit |
| FP16 | 6.4 GB | 7.7 GB | — not resident | Won't fit |
Ran Llama 3.2 3B on a NVIDIA RTX 3050 Laptop (4GB)? Add your real numbers →