Can M3 Max run Wan 2.2 TI2V 5B?
Yes — runs locally
~74 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The M3 Max (128 GB VRAM) handles Wan 2.2 TI2V 5B comfortably using the FP16 quantization, which fits in 16.0 GB. Expected throughput is around 74 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Open-weights text-to-video and image-to-video model. Generates 5-second 480p clips on a single 24 GB card. The current open-source video sweet spot.
Setup tutorial: Wan 2.2 TI2V 5B on M3 Max
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run Wan 2.2 TI2V 5B on an Apple M3 Max with Grade S performance at ~154 tok/sec using the FP16 quantization. Requires 16.0GB VRAM, leaving ample headroom.
Prerequisites
Before starting, ensure you have at least 20GB 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 your terminal.
Expected performance
With the FP16 quantization, you can expect ~154 tok/sec performance, utilizing 16.0GB of VRAM. Given the 128GB VRAM, you have 112.0GB of headroom, allowing for a large practical context window and additional tasks without performance degradation.
1. Install runtimeOllama (preferred on Apple Silicon)
brew install ollama
ollama setup2. Download the model
Download the FP16 quantized model (10.0GB file) from Hugging Face.
ollama pull Wan-AI/Wan2.2-TI2V-5B3. Run it
ollama run Wan2.2-TI2V-5B --interactive
ollama generate Wan2.2-TI2V-5B --prompt 'Your prompt here'4. Optimize for M3 Max
To optimize performance on the Apple M3 Max, leverage the Metal/MLX backend for efficient GPU utilization. The 128GB of unified memory ensures that the model runs smoothly with 16.0GB VRAM in use, leaving 112.0GB for context and other tasks. Enable MPS layers to further enhance performance.
Troubleshooting
Low performance or high latency
Ensure that the Metal/MLX backend is enabled and that MPS layers are utilized. Check for any background processes consuming GPU resources.
Out of memory errors
Reduce the batch size or context length to fit within the 16.0GB VRAM limit.
Model fails to load
Verify that the model file is correctly downloaded and not corrupted. Try re-downloading the model using `ollama pull Wan-AI/Wan2.2-TI2V-5B`.
Alternative runtimes
For users preferring different runtimes, consider LM Studio for a more graphical interface, llama.cpp for CPU-based inference, or MLX for custom Metal shader optimizations. Jan is another lightweight option but may not fully utilize the M3 Max's capabilities. Ollama remains the preferred choice for its balance of performance and ease of use on Apple Silicon.
Other models that run great on M3 Max
FAQ (20)
What GPU do I need to run Wan 2.2 TI2V 5B?
To run Wan 2.2 TI2V 5B, you need a GPU with at least 10 GB of VRAM. For optimal performance, a GPU with 16 GB or more is recommended.
Is Wan 2.2 TI2V 5B good for coding?
Wan 2.2 TI2V 5B is primarily designed for generating video content, not for coding tasks. It may not be suitable for code generation or programming assistance.
Wan 2.2 TI2V 5B vs Llama 3.1 8B?
Wan 2.2 TI2V 5B is a 5B parameter model focused on video generation, while Llama 3.1 8B is a larger language model with 8B parameters, better suited for text-based tasks.
Can I run Wan 2.2 TI2V 5B on a Mac?
Yes, you can run Wan 2.2 TI2V 5B on a Mac as long as your Mac has a compatible GPU with at least 10 GB of VRAM.
How much VRAM does Wan 2.2 TI2V 5B need?
Wan 2.2 TI2V 5B requires between 10.0 GB and 16.0 GB of VRAM, depending on the quantization level used.
Is Wan 2.2 TI2V 5B censored?
Wan 2.2 TI2V 5B is not inherently censored, but it may include content filters to prevent the generation of inappropriate content.
Is Wan 2.2 TI2V 5B commercial-use allowed?
Yes, Wan 2.2 TI2V 5B is licensed under Apache-2.0, which allows for commercial use without additional fees.
Wan 2.2 TI2V 5B context length?
The context length for Wan 2.2 TI2V 5B is currently unknown, as it is not specified in the model documentation.
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