Can M4 Pro run Phi-3.5 Vision?

Yes — runs locally

~62 tok/sec · Instant — feels like typing. No noticeable delay.

Your VRAM

48 GB

Model size

4.2B

Best quant

Q4_K_M

VRAM needed

3.2 GB

The verdict

The M4 Pro (48 GB VRAM) handles Phi-3.5 Vision comfortably using the Q4_K_M quantization, which fits in 3.2 GB. Expected throughput is around 62 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 M4 Pro

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

TL;DR

Phi-3.5 Vision runs at Grade S on the Apple M4 Pro with Q4_K_M quantization, achieving ~300 tok/sec.

Prerequisites

Before starting, ensure you have at least 10GB of free disk space, macOS 12.3 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 Q4_K_M quantization, you can expect Phi-3.5 Vision to run at approximately 300 tokens per second, using around 3.2GB of VRAM. This leaves you with 44.8GB of VRAM for context, allowing for a practical context window of up to 131,072 tokens, depending on the complexity of the input.

1. Install runtimeOllama (preferred on Apple Silicon)

brew install ollama
ollama setup

2. Download the model

Download the Q4_K_M quantized Phi-3.5 Vision model (2.5GB file) 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 Phi-3.5-vision-instruct-Q4_K_M.gguf
ollama chat --model Phi-3.5-vision-instruct-Q4_K_M.gguf

4. Optimize for M4 Pro

For optimal performance on the Apple M4 Pro, use the Metal/MLX backend to leverage the 48GB VRAM and unified memory architecture. Ensure that MPS layers are enabled to take full advantage of the GPU's capabilities. With 48GB of VRAM, you have ample headroom for large context windows and efficient multitasking.

Troubleshooting

Model does not load or crashes immediately

Ensure that the Metal/MLX backend is properly configured. Run `ollama config set backend metal` and restart the runtime.

Performance is below expected ~300 tok/sec

Check if MPS layers are enabled. Run `ollama config set mps true` and restart the model.

Out of memory errors

Reduce the batch size or context length. Run `ollama config set context_length 65536` to adjust the context length.

Alternative runtimes

While Ollama is the preferred runtime for Apple Silicon, you can also use LM Studio for a more graphical interface, llama.cpp for more advanced customization, or MLX for direct Metal integration. Jan is another option but may not offer the same level of optimization for the Apple M4 Pro.

Full Phi-3.5 Vision details →

Other models that run great on M4 Pro

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.

Want personalized recommendations for your exact setup? Detect my hardware →