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No. d3 27B (vLLM Semantic Router, decision) does not fit on Mac Studio M4 Max (32c GPU) 36GB: Q8_0 needs 32.3 GB and 27.0 GB is usable.
Hardware: Mac Studio M4 Max (32c GPU) 36GB · Model: d3 27B (vLLM Semantic Router, decision)
Mac Studio M4 Max (32c GPU) 36GB has 36 GB of unified memory and 410 GB/s of memory bandwidth. M4 Max (32c GPU) 36GB has the same memory and bandwidth, so the fit numbers match; this page is Mac Studio M4 Max (32c GPU) 36GB. The checker leaves macOS a share of unified memory, so Ollama can use 27.0 GB. d3 27B (vLLM Semantic Router, decision) (27B, vLLM Semantic Router) at Q8_0 is a 30 GB download and needs 32.3 GB with headroom for about 8k tokens.
| Best quant | Q8_0 |
|---|---|
| Download size | 30 GB |
| Memory needed | 32.3 GB |
| Usable fast memory | 27.0 GB |
| Fit | does not fit |
| Estimated speed | no estimate, it does not fit |
| Command | ollama run d3:27b-q8_0 |
Smallest hardware that runs it: RTX 3090 24GB at Q8_0 (partial offload (slower), 32.3 GB needed, 23.5 GB usable, about 4 tok/s (estimate)). Can a RTX 3090 24GB run d3 27B (vLLM Semantic Router, decision)?
A smaller vLLM Semantic Router model that fits this hardware: d3 9B (vLLM Semantic Router, decision) at Q8_0 (fits in fast memory, 11.4 GB). Can a Mac Studio M4 Max (32c GPU) 36GB run d3 9B (vLLM Semantic Router, decision)?
Open Mac Studio M4 Max (32c GPU) 36GB in the checkerEstimates, 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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