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Yes. Gemma 3 27B fits in fast memory on RTX 4090 24GB at Q4_K_M (19.3 GB needed, 23.5 GB usable), about 36 tok/s (estimate).
Hardware: RTX 4090 24GB · Model: Gemma 3 27B
RTX 4090 24GB has 24 GB of VRAM and 1008 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 23.5 GB. Partial offload may also use 60% of that system RAM. Gemma 3 27B (27.4B, Google) at Q4_K_M is a 17 GB download and needs 19.3 GB with headroom for about 8k tokens.
| Best quant | Q4_K_M |
|---|---|
| Download size | 17 GB |
| Memory needed | 19.3 GB |
| Usable fast memory | 23.5 GB |
| Fit | fits in fast memory |
| Estimated speed | ~36 tok/s (estimate) |
| Command | ollama run gemma3:27b |
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.
A project by OnDevice Labs · llms.txt