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Yes. DeepSeek R1 0528 Qwen3 8B fits in fast memory on M2 Pro 32GB at Q8_0 (9.9 GB needed, 24.0 GB usable), about 18 tok/s (estimate).
Hardware: M2 Pro 32GB · Model: DeepSeek R1 0528 Qwen3 8B
M2 Pro 32GB has 32 GB of unified memory and 200 GB/s of memory bandwidth. M1 Pro 32GB has the same memory and bandwidth, so the fit numbers match; this page is M2 Pro 32GB. The checker leaves macOS a share of unified memory, so Ollama can use 24.0 GB. DeepSeek R1 0528 Qwen3 8B (8.19B, DeepSeek) at Q8_0 is a 8.9 GB download and needs 9.9 GB with headroom for about 8k tokens.
| Best quant | Q8_0 |
|---|---|
| Download size | 8.9 GB |
| Memory needed | 9.9 GB |
| Usable fast memory | 24.0 GB |
| Fit | fits in fast memory |
| Estimated speed | ~18 tok/s (estimate) |
| Command | ollama run deepseek-r1:8b-0528-qwen3-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.
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