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Yes. DeepSeek Coder V2 Lite 16B (MoE) fits in fast memory on RTX 4080 16GB at Q5_K_M (13 GB needed, 15.5 GB usable), about 117 tok/s (estimate).
Hardware: RTX 4080 16GB · Model: DeepSeek Coder V2 Lite 16B (MoE)
RTX 4080 16GB has 16 GB of VRAM and 717 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 15.5 GB. Partial offload may also use 60% of that system RAM. DeepSeek Coder V2 Lite 16B (MoE) (15.7B, 2.4B active, DeepSeek) at Q5_K_M is a 12 GB download and needs 13 GB with headroom for about 8k tokens.
| Best quant | Q5_K_M |
|---|---|
| Download size | 12 GB |
| Memory needed | 13 GB |
| Usable fast memory | 15.5 GB |
| Fit | fits in fast memory |
| Estimated speed | ~117 tok/s (estimate) |
| Command | ollama run deepseek-coder-v2:16b-lite-instruct-q5_K_M |
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