Can M4 Max run Phi-3.5 Vision?
Yes — runs locally
~74 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The M4 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 M4 Max
AI-generated, GPU-specific. Verified commands for your exact hardware.
Phi-3.5 Vision runs at Grade S on the Apple M4 Max with Q4_K_M quantization, achieving ~800 tok/sec and using 3.2GB VRAM.
Prerequisites
Before starting, ensure you have at least 2.5GB 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 ~800 tok/sec performance and 3.2GB VRAM usage. Given the 128GB VRAM, you have a headroom of 124.8GB, allowing for a large practical context window of up to 131072 tokens, depending on the complexity of the input.
1. Install runtimeOllama (preferred on Apple Silicon)
brew install ollama
ollama init2. Download the model
Download the Q4_K_M quantized version of Phi-3.5 Vision, which is a 2.5GB file.
ollama pull abetlen/Phi-3.5-vision-instruct-gguf:Q4_K_M3. Run it
ollama run Phi-3.5-vision-instruct-Q4_K_M
ollama chat --model Phi-3.5-vision-instruct-Q4_K_M4. Optimize for M4 Max
To optimize performance on the Apple M4 Max, ensure you are using the Metal/MLX backend. The unified memory architecture allows efficient use of the 128GB VRAM, with 3.2GB dedicated to the model, leaving 124.8GB available for context and other tasks. Enable MPS layers for further acceleration.
Troubleshooting
Model fails to load due to insufficient VRAM.
Ensure you have at least 128GB of VRAM available. If not, close other applications and try again.
Performance is below expected ~800 tok/sec.
Check that the Metal/MLX backend is enabled and that MPS layers are utilized. Update Ollama to the latest version using `brew upgrade ollama`.
Model crashes or hangs during inference.
Restart the Ollama runtime with `ollama stop` followed by `ollama start`. Ensure your macOS is up to date.
Alternative runtimes
For users preferring different runtimes, consider LM Studio for a more graphical interface, llama.cpp for low-level control, or MLX for direct Metal integration. Jan is another option but may not offer the same level of optimization for Apple Silicon as Ollama.
Other models that run great on M4 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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