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Yes. GLM-OCR 0.9B fits in fast memory on M2 Ultra 64GB at BF16 (3.7 GB needed, 48.0 GB usable), about 237 tok/s (estimate).
Hardware: M2 Ultra 64GB · Model: GLM-OCR 0.9B
M2 Ultra 64GB has 64 GB of unified memory and 800 GB/s of memory bandwidth. The checker leaves macOS a share of unified memory, so Ollama can use 48.0 GB. GLM-OCR 0.9B (1.33B, Z.ai) at BF16 is a 2.7 GB download and needs 3.7 GB with headroom for about 8k tokens.
| Best quant | BF16 |
|---|---|
| Download size | 2.7 GB |
| Memory needed | 3.7 GB |
| Usable fast memory | 48.0 GB |
| Fit | fits in fast memory |
| Estimated speed | ~237 tok/s (estimate) |
| Command | ollama run glm-ocr:latest |
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