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Yes, with partial offload (slower). Gemma 3n E2B (on-device) on RTX 3060 Ti 8GB at Q8_0 uses system RAM (7.8 GB needed, 7.5 GB usable), about 32 tok/s (estimate).
Hardware: RTX 3060 Ti 8GB · Model: Gemma 3n E2B (on-device)
RTX 3060 Ti 8GB has 8 GB of VRAM and 448 GB/s of memory bandwidth. RTX 3070 8GB has the same memory and bandwidth, so the fit numbers match; this page is RTX 3060 Ti 8GB. 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 7.5 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 | 7.5 GB |
| Fit | partial offload (slower) |
| Estimated speed | ~32 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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