Can M3 Max run Phi-3.5 Vision?

Yes — runs locally

~74 tok/sec · Instant — feels like typing. No noticeable delay.

Your VRAM

128 GB

Model size

4.2B

Best quant

Q4_K_M

VRAM needed

3.2 GB

The verdict

The M3 Max (128 GB VRAM) handles Phi-3.5 Vision comfortably using the Q4_K_M quantization, which fits in 3.2 GB. Expected throughput is around 74 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Vision-language model from Microsoft. Can understand images and documents.

Setup tutorial: Phi-3.5 Vision on M3 Max

AI-generated, GPU-specific. Verified commands for your exact hardware.

TL;DR

Phi-3.5 Vision runs at Grade S on the Apple M3 Max with Q4_K_M quantization, achieving ~800 tok/sec.

Prerequisites

Before starting, ensure you have at least 2.5GB of free disk space, macOS 13.0 or later, and Xcode Command Line Tools installed. You can install Xcode CLT by running `xcode-select --install` in the terminal.

Expected performance

With the Apple M3 Max, you can expect Phi-3.5 Vision to run at approximately 800 tokens per second, using around 3.2GB of VRAM. This leaves you with 124.8GB of VRAM for context, enabling you to process large images and documents efficiently.

1. Install runtimeOllama (preferred on Apple Silicon)

brew install ollama
ollama init

2. Download the model

Download the Q4_K_M quantized model (2.5GB) from Hugging Face.

ollama pull abetlen/Phi-3.5-vision-instruct-gguf:Phi-3.5-vision-instruct-Q4_K_M.gguf

3. Run it

ollama run abetlen/Phi-3.5-vision-instruct-gguf:Phi-3.5-vision-instruct-Q4_K_M.gguf
ollama chat --model abetlen/Phi-3.5-vision-instruct-gguf:Phi-3.5-vision-instruct-Q4_K_M.gguf

4. Optimize for M3 Max

To optimize performance on the Apple M3 Max, use the Metal/MLX backend to leverage the 128GB of unified memory. Ensure that MPS layers are enabled to take full advantage of the GPU. The large VRAM allows for efficient handling of large contexts and images.

Troubleshooting

Model fails to load due to insufficient VRAM

Ensure you have at least 3.2GB of free VRAM. If not, close other applications to free up resources.

Performance is below 800 tok/sec

Check that the Metal/MLX backend is enabled and that MPS layers are utilized. Update your macOS and Ollama to the latest versions.

Model crashes during inference

Increase the swap space or reduce the batch size to prevent out-of-memory errors.

Alternative runtimes

While Ollama is the preferred runtime for Apple Silicon, you can also use LM Studio, llama.cpp, or MLX. LM Studio provides a graphical interface and is useful for users who prefer a GUI. llama.cpp is more lightweight and suitable for command-line enthusiasts. MLX offers advanced optimization but may require more setup. Choose based on your specific needs and preferences.

Full Phi-3.5 Vision details →

Other models that run great on M3 Max

FAQ (20)

What GPU do I need to run Phi-3.5 Vision?

To run Phi-3.5 Vision, you need a GPU with at least 3.2 GB of VRAM. Higher VRAM will improve performance, especially for larger tasks.

Is Phi-3.5 Vision good for coding?

Phi-3.5 Vision is primarily designed for vision and language tasks, such as understanding images and documents. It may not be as optimized for coding-specific tasks compared to models like Codex or CodeLlama.

Phi-3.5 Vision vs Llama 3.1 8B?

Phi-3.5 Vision has 4.2 billion parameters and is specialized for vision-language tasks, while Llama 3.1 8B is a text-only model with 8 billion parameters, making it more versatile for text generation but less suited for image understanding.

Can I run Phi-3.5 Vision on a Mac?

Yes, you can run Phi-3.5 Vision on a Mac, but ensure your Mac has a compatible GPU with at least 3.2 GB of VRAM. Apple Silicon GPUs may require additional drivers or software.

How much VRAM does Phi-3.5 Vision need?

Phi-3.5 Vision requires 3.2 GB of VRAM, which is consistent across different quantization levels. More VRAM can help with larger batch sizes and more complex tasks.

Is Phi-3.5 Vision censored?

Phi-3.5 Vision is not inherently censored, but it adheres to ethical guidelines and may have filters to prevent harmful content. Users can configure additional safety measures as needed.

Is Phi-3.5 Vision commercial-use allowed?

Yes, Phi-3.5 Vision is licensed under the MIT License, which allows for commercial use. However, always review the specific terms of the license to ensure compliance.

Phi-3.5 Vision context length?

Phi-3.5 Vision has a context length of 131,072 tokens, allowing it to process very long sequences of text and images effectively.

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