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Can a M4 16GB run d3 9B (vLLM Semantic Router, decision)?

No. d3 9B (vLLM Semantic Router, decision) does not fit on M4 16GB: Q8_0 needs 11.4 GB and 10.7 GB is usable.

Hardware: M4 16GB · Model: d3 9B (vLLM Semantic Router, decision)

M4 16GB has 16 GB of unified memory and 120 GB/s of memory bandwidth. The checker leaves macOS a share of unified memory, so Ollama can use 10.7 GB. d3 9B (vLLM Semantic Router, decision) (9B, vLLM Semantic Router) at Q8_0 is a 10 GB download and needs 11.4 GB with headroom for about 8k tokens.

Best quantQ8_0
Download size10 GB
Memory needed11.4 GB
Usable fast memory10.7 GB
Fitdoes not fit
Estimated speedno estimate, it does not fit
Commandollama run d3:9b-q8_0

Smallest hardware that runs it: RTX 3060 8GB at Q8_0 (partial offload (slower), 11.4 GB needed, 7.5 GB usable, about 8 tok/s (estimate)). Can a RTX 3060 8GB run d3 9B (vLLM Semantic Router, decision)?

A smaller vLLM Semantic Router model that fits this hardware: d3 4B (vLLM Semantic Router, decision) at Q8_0 (fits in fast memory, 6.9 GB). Can a M4 16GB run d3 4B (vLLM Semantic Router, decision)?

Open M4 16GB in the checker

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