Best Local AI Models for an M4 Pro Mac With 48GB Memory
Calculated local AI model fits for an Apple M4 Pro Mac with 48GB unified memory.
Yes. A computer with 48GB RAM can run small local AI models. A safe first choice from the current MamiLens list is Mistral Small 3.2 24B. 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 40GB.
Best models to start with
Mistral Small 3.2 24B
Strong single-GPU multimodal instruction model with robust tool calling.
- Calculated weights
- 15 GB
- Estimated total RAM
- 29 GB
- RAM left
- 19 GB
- Expected path
- Unified memory
- Speed
- 6 to 12 tokens/s estimate
- Evidence
- Calculated estimate
ollama run mistral-small3.2Open evidence-labelled model profile →Devstral Small 24B
Code-agent model for repository exploration and multi-file software-engineering work.
- Calculated weights
- 15 GB
- Estimated total RAM
- 28 GB
- RAM left
- 20 GB
- Expected path
- Unified memory
- Speed
- 6 to 12 tokens/s estimate
- Evidence
- Calculated estimate
ollama run devstral:24bOpen evidence-labelled model profile →Gemma 4 26B-A4B
Gemma 4 26B-A4B is a curated mixture-of-experts profile for general, writing, reasoning workloads.
- Calculated weights
- 18 GB
- Estimated total RAM
- 33 GB
- RAM left
- 15 GB
- Expected path
- Unified memory
- Speed
- 5 to 10 tokens/s estimate
- Evidence
- Calculated estimate
ollama run gemma4:26bOpen evidence-labelled model profile →GPT-OSS 20B
GPT-OSS 20B is a curated mixture-of-experts profile for reasoning, coding, tools workloads.
- Calculated weights
- 14 GB
- Estimated total RAM
- 26 GB
- RAM left
- 22 GB
- Expected path
- Unified memory
- Speed
- 6 to 13 tokens/s estimate
- Evidence
- Calculated estimate
ollama run gpt-oss:20bOpen evidence-labelled model profile →Qwen 3.6 27B Q4
Qwen 3.6 27B Q4 is a curated dense profile for general, coding, reasoning workloads.
- Calculated weights
- 17 GB
- Estimated total RAM
- 32 GB
- RAM left
- 16 GB
- Expected path
- Unified memory
- Speed
- 5 to 11 tokens/s estimate
- Evidence
- Calculated estimate
ollama run qwen3.6:27bOpen 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.