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Yes. Qwen3-VL 30B-A3B (MoE) fits in fast memory on M4 Max (40c GPU) 128GB at Q8_0 (35.7 GB needed, 96.0 GB usable), about 67 tok/s (estimate).
Hardware: M4 Max (40c GPU) 128GB · Model: Qwen3-VL 30B-A3B (MoE)
M4 Max (40c GPU) 128GB has 128 GB of unified memory and 546 GB/s of memory bandwidth. Mac Studio M4 Max (40c GPU) 128GB has the same memory and bandwidth, so the fit numbers match; this page is M4 Max (40c GPU) 128GB. The checker leaves macOS a share of unified memory, so Ollama can use 96.0 GB. Qwen3-VL 30B-A3B (MoE) (31.1B, 3B active, Alibaba) at Q8_0 is a 34 GB download and needs 35.7 GB with headroom for about 8k tokens.
| Best quant | Q8_0 |
|---|---|
| Download size | 34 GB |
| Memory needed | 35.7 GB |
| Usable fast memory | 96.0 GB |
| Fit | fits in fast memory |
| Estimated speed | ~67 tok/s (estimate) |
| Command | ollama run qwen3-vl:30b-a3b-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