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No. Llama 3.3 70B does not fit on M4 Max (32c GPU) 36GB: Q4_K_M needs 47.1 GB and 27.0 GB is usable.
Hardware: M4 Max (32c GPU) 36GB · Model: Llama 3.3 70B
M4 Max (32c GPU) 36GB has 36 GB of unified memory and 410 GB/s of memory bandwidth. Mac Studio M4 Max (32c GPU) 36GB has the same memory and bandwidth, so the fit numbers match; this page is M4 Max (32c GPU) 36GB. The checker leaves macOS a share of unified memory, so Ollama can use 27.0 GB. Llama 3.3 70B (70.6B, Meta) at Q4_K_M is a 43 GB download and needs 47.1 GB with headroom for about 8k tokens.
| Best quant | Q4_K_M |
|---|---|
| Download size | 43 GB |
| Memory needed | 47.1 GB |
| Usable fast memory | 27.0 GB |
| Fit | does not fit |
| Estimated speed | no estimate, it does not fit |
| Command | ollama run llama3.3:70b |
Smallest hardware that runs it: M1 Max (32c GPU) 64GB at Q4_K_M (fits in fast memory, 47.1 GB needed, 48.0 GB usable, about 7 tok/s (estimate)). Can a M1 Max (32c GPU) 64GB run Llama 3.3 70B?
A smaller Meta model that fits this hardware: Llama 3.2 Vision 11B at Q8_0 (fits in fast memory, 13.5 GB). Can a M4 Max (32c GPU) 36GB run Llama 3.2 Vision 11B?
Open M4 Max (32c GPU) 36GB 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