Can I run this LLM?
Can a NVIDIA RTX 3050 Laptop (4GB) run Llama 3.2 1B?
Llama · Llama 3.2 Community · estimated for a 4.0 GB machine at 4K context.
Yes — it runs great.
Runs greatBest fit: Llama 3.2 1B at Q8_0 · 1.3 GB weights · 77–116 tok/s on a NVIDIA RTX 3050 Laptop (4GB).
Arena Text Overall · style-controlled
1,111Q8_0 untestedllama-3.2-1b-instruct · published configuration reference · Q8_0 not tested
Arena Text Overall (style-controlled), exact published entry llama-3.2-1b-instruct, 2026-10-08: reference rating 1,111.1. Published confidence bounds 1,103.2–1,119. 8,045 votes. Published llama-3.2-1b-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 Q8_0 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
- 2.3 GB
- Weights + KV cache + runtime overhead
- Estimated generation
- 77–116 tok/s
- Estimated first token
- ~2.9s
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 | 0.8 GB | 1.7 GB | 107–160 tok/s | Runs great |
| Q5_K_M | 0.9 GB | 1.8 GB | 99–149 tok/s | Runs great |
| Q6_K | 1.0 GB | 2.0 GB | 92–138 tok/s | Runs great |
| Q8_0 | 1.3 GB | 2.3 GB | 77–116 tok/s | Runs great |
| FP16 | 2.5 GB | 3.4 GB | 47–71 tok/s | Tight / slow |
Ran Llama 3.2 1B on a NVIDIA RTX 3050 Laptop (4GB)? Add your real numbers →