Best Local AI Models for an M3 Max Mac With 64GB Memory
Calculated local AI model fits for an Apple M3 Max Mac with 64GB unified memory.
Yes. A computer with 64GB RAM can run small local AI models. A safe first choice from the current MamiLens list is Qwen 2.5 32B. This is a memory-fit estimate, not a speed promise.
The device we checked
MamiLens keeps 8GB for the operating system and background work. That leaves a working model budget of about 56GB.
Best models to start with
Qwen 2.5 32B
Qwen 2.5 32B is a curated dense profile for general, writing, coding workloads.
- Calculated weights
- 20 GB
- Estimated total RAM
- 34 GB
- RAM left
- 30 GB
- Expected path
- Unified memory
- Speed
- 7 to 13 tokens/s estimate
- Evidence
- Calculated estimate
ollama run qwen2.5:32bOpen evidence-labelled model profile →Qwen 3 32B
Qwen 3 32B is a curated dense profile for general, coding, reasoning workloads.
- Calculated weights
- 20 GB
- Estimated total RAM
- 33 GB
- RAM left
- 31 GB
- Expected path
- Unified memory
- Speed
- 7 to 13 tokens/s estimate
- Evidence
- Calculated estimate
ollama run qwen3:32bOpen evidence-labelled model profile →DeepSeek R1 32B
DeepSeek R1 32B is a curated dense profile for reasoning, math, coding workloads.
- Calculated weights
- 20 GB
- Estimated total RAM
- 34 GB
- RAM left
- 30 GB
- Expected path
- Unified memory
- Speed
- 7 to 13 tokens/s estimate
- Evidence
- Calculated estimate
ollama run deepseek-r1:32bOpen evidence-labelled model profile →Gemma 4 31B
Gemma 4 31B is a curated dense profile for general, writing, reasoning workloads.
- Calculated weights
- 20 GB
- Estimated total RAM
- 36 GB
- RAM left
- 28 GB
- Expected path
- Unified memory
- Speed
- 7 to 13 tokens/s estimate
- Evidence
- Calculated estimate
ollama run gemma4:31bOpen evidence-labelled model profile →Qwen 3 30B-A3B
Qwen 3 30B-A3B is a curated mixture-of-experts profile for general, coding, reasoning workloads.
- Calculated weights
- 19 GB
- Estimated total RAM
- 32 GB
- RAM left
- 32 GB
- Expected path
- Unified memory
- Speed
- 7 to 14 tokens/s estimate
- Evidence
- Calculated estimate
ollama run qwen3:30bOpen evidence-labelled model profile →Recommended inference engine
LM Studio or MLX LM
Both can use Apple unified memory. LM Studio is easier; MLX LM gives Apple-native control.
Unified memory helps model access, but chip generation still changes speed.How accurate is this result?
This page uses the same calculator rules as the live MamiLens tool. It includes model weights, runtime overhead, operating-system reserve, context reserve and simultaneous-user cache when selected. A displayed speed range is calculated from published memory bandwidth. It is not a benchmark from this exact computer.
Start with the first model. Test a normal task, record response speed and watch memory use before using it for important work.