Can I run this LLM?
Can a NVIDIA RTX 3050 Laptop (4GB) run Gemma 2 2B?
Gemma · Gemma · estimated for a 4.0 GB machine at 4K context.
Yes — it runs great.
Runs greatBest fit: Gemma 2 2B at Q5_K_M · 1.9 GB weights · 52–78 tok/s on a NVIDIA RTX 3050 Laptop (4GB).
Arena Text Overall · style-controlled
1,200Q5_K_M untestedgemma-2-2b-it · published configuration reference · Q5_K_M not tested
Arena Text Overall (style-controlled), exact published entry gemma-2-2b-it, 2026-10-08: reference rating 1,200.1. Published confidence bounds 1,196–1,204.2. 46,616 votes. Published gemma-2-2b-it 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
- 3.2 GB
- Weights + KV cache + runtime overhead
- Estimated generation
- 52–78 tok/s
- Estimated first token
- ~6.0s
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 | 1.7 GB | 2.9 GB | 56–84 tok/s | Runs great |
| Q5_K_M | 1.9 GB | 3.2 GB | 52–78 tok/s | Runs great |
| Q6_K | 2.2 GB | 3.4 GB | 48–72 tok/s | Tight / slow |
| Q8_0 | 2.8 GB | 4.0 GB | — not resident | Won't fit |
Ran Gemma 2 2B on a NVIDIA RTX 3050 Laptop (4GB)? Add your real numbers →