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Yes. DeepSeek Coder V2 Lite 16B (MoE) fits in fast memory on RTX 3090 24GB at Q8_0 (18 GB needed, 23.5 GB usable), about 108 tok/s (estimate).
Hardware: RTX 3090 24GB · Model: DeepSeek Coder V2 Lite 16B (MoE)
RTX 3090 24GB has 24 GB of VRAM and 936 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. DeepSeek Coder V2 Lite 16B (MoE) (15.7B, 2.4B active, DeepSeek) at Q8_0 is a 17 GB download and needs 18 GB with headroom for about 8k tokens.
| Best quant | Q8_0 |
|---|---|
| Download size | 17 GB |
| Memory needed | 18 GB |
| Usable fast memory | 23.5 GB |
| Fit | fits in fast memory |
| Estimated speed | ~108 tok/s (estimate) |
| Command | ollama run deepseek-coder-v2:16b-lite-instruct-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.
A project by OnDevice Labs · llms.txt