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Yes. Gemma 3n E2B (on-device) fits in fast memory on RTX 5090 32GB at Q8_0 (7.8 GB needed, 31.5 GB usable), about 156 tok/s (estimate).
Hardware: RTX 5090 32GB · Model: Gemma 3n E2B (on-device)
RTX 5090 32GB has 32 GB of VRAM and 1792 GB/s of memory bandwidth. The checker holds back 0.5 GB of VRAM for the driver and assumes 16 GB of system RAM, so fast memory usable by Ollama is 31.5 GB. Partial offload may also use 60% of that system RAM. Gemma 3n E2B (on-device) (5.4B, Google) at Q8_0 is a 6.9 GB download and needs 7.8 GB with headroom for about 8k tokens.
| Best quant | Q8_0 |
|---|---|
| Download size | 6.9 GB |
| Memory needed | 7.8 GB |
| Usable fast memory | 31.5 GB |
| Fit | fits in fast memory |
| Estimated speed | ~156 tok/s (estimate) |
| Command | ollama run gemma3n:e2b-it-q8_0 |
Estimates, not benchmarks. Model sizes are ollama.com download sizes; memory needed adds headroom for ~8k tokens of context; speeds are rough figures from memory bandwidth. Data updated 2026-10-23.
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