Can I run this LLM?
Can a NVIDIA RTX 4090 (24GB) run Gemma 2 2B?
Gemma · Gemma · estimated for a 24.0 GB machine at 4K context.
Yes — it runs great.
Runs greatBest fit: Gemma 2 2B at Q8_0 · 2.8 GB weights · 142–213 tok/s on a NVIDIA RTX 4090 (24GB).
Arena Text Overall · style-controlled
1,200Q8_0 untestedgemma-2-2b-it · published configuration reference · Q8_0 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 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
- 4.0 GB
- Weights + KV cache + runtime overhead
- Estimated generation
- 142–213 tok/s
- Estimated first token
- ~0.4s
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 | 1.7 GB | 2.9 GB | 178–267 tok/s | Runs great |
| Q5_K_M | 1.9 GB | 3.2 GB | 170–255 tok/s | Runs great |
| Q6_K | 2.2 GB | 3.4 GB | 161–242 tok/s | Runs great |
| Q8_0 | 2.8 GB | 4.0 GB | 142–213 tok/s | Runs great |
Ran Gemma 2 2B on a NVIDIA RTX 4090 (24GB)? Add your real numbers →