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No. Qwen3-VL 32B does not fit on M1 16GB: Q4_K_M needs 23.6 GB and 10.7 GB is usable.
Hardware: M1 16GB · Model: Qwen3-VL 32B
M1 16GB has 16 GB of unified memory and 68 GB/s of memory bandwidth. The checker leaves macOS a share of unified memory, so Ollama can use 10.7 GB. Qwen3-VL 32B (33.4B, Alibaba) at Q4_K_M is a 21 GB download and needs 23.6 GB with headroom for about 8k tokens.
| Best quant | Q4_K_M |
|---|---|
| Download size | 21 GB |
| Memory needed | 23.6 GB |
| Usable fast memory | 10.7 GB |
| Fit | does not fit |
| Estimated speed | no estimate, it does not fit |
| Command | ollama run qwen3-vl:32b |
Smallest hardware that runs it: RTX 4060 Ti 16GB at Q4_K_M (partial offload (slower), 23.6 GB needed, 15.5 GB usable, about 4 tok/s (estimate)). Can a RTX 4060 Ti 16GB run Qwen3-VL 32B?
A smaller Alibaba model that fits this hardware: Qwen 2.5 14B at Q4_K_M (fits in fast memory, 10.3 GB). Can a M1 16GB run Qwen 2.5 14B?
Open M1 16GB 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.
A project by OnDevice Labs · llms.txt