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Yes. Llama 3.3 70B fits in fast memory on Mac Studio M3 Ultra (80c GPU) 256GB at Q8_0 (79.1 GB needed, 192.0 GB usable), about 9 tok/s (estimate).
Hardware: Mac Studio M3 Ultra (80c GPU) 256GB · Model: Llama 3.3 70B
Mac Studio M3 Ultra (80c GPU) 256GB has 256 GB of unified memory and 819 GB/s of memory bandwidth. Mac Studio M3 Ultra (60c GPU) 256GB has the same memory and bandwidth, so the fit numbers match; this page is Mac Studio M3 Ultra (80c GPU) 256GB. The checker leaves macOS a share of unified memory, so Ollama can use 192.0 GB. Llama 3.3 70B (70.6B, Meta) at Q8_0 is a 75 GB download and needs 79.1 GB with headroom for about 8k tokens.
| Best quant | Q8_0 |
|---|---|
| Download size | 75 GB |
| Memory needed | 79.1 GB |
| Usable fast memory | 192.0 GB |
| Fit | fits in fast memory |
| Estimated speed | ~9 tok/s (estimate) |
| Command | ollama run llama3.3:70b-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