Can M4 Pro run TRELLIS Image Large?
Yes — runs locally
~90 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The M4 Pro (48 GB VRAM) handles TRELLIS Image Large comfortably using the FP16 quantization, which fits in 12.0 GB. Expected throughput is around 90 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Image-to-3D model that produces textured meshes. Runs in ~12 GB VRAM and outputs glTF.
Setup tutorial: TRELLIS Image Large on M4 Pro
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run TRELLIS Image Large on an Apple M4 Pro with Ollama using the FP16 quantization. Expect Grade S performance at ~99 tok/sec.
Prerequisites
Before starting, ensure you have at least 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 your terminal.
Expected performance
With the FP16 quantization, expect the model to run at ~99 tok/sec, utilizing 12.0GB of VRAM. Given the 48GB VRAM on the M4 Pro, you have 36.0GB of headroom for context, allowing for a practical context window that can handle large images and complex 3D models.
1. Install runtimeOllama (preferred on Apple Silicon)
brew install ollama
ollama setup2. Download the model
Download the FP16 quantized version of TRELLIS Image Large (2.4GB) from Hugging Face.
ollama pull JeffreyXiang/TRELLIS-image-large3. Run it
ollama run TRELLIS-image-large
ollama interactive TRELLIS-image-large4. Optimize for M4 Pro
To optimize performance on the Apple M4 Pro, leverage the Metal/MLX backend and unified memory. The M4 Pro has 48GB of VRAM, which allows the model to run efficiently with 12.0GB VRAM usage, leaving 36.0GB for context and other tasks. Ensure you enable MPS layers for better utilization of the GPU.
Troubleshooting
Low performance or high latency
Ensure you have the latest macOS updates and that the Metal/MLX backend is enabled. Run `ollama tune --backend=metal` to optimize the runtime.
Out of memory errors
Reduce the batch size or context length. You can adjust these settings using `ollama config --batch-size=16 --context-length=512`.
Model not found
Verify that the model was successfully downloaded by running `ollama list`. If not, try pulling the model again with `ollama pull JeffreyXiang/TRELLIS-image-large`.
Alternative runtimes
While Ollama is the preferred runtime for Apple Silicon, you can also use alternatives like LM Studio, llama.cpp, or MLX. LM Studio is ideal for GUI-based workflows, llama.cpp offers more control over quantization, and MLX is suitable for custom integrations. Choose based on your specific use case and preferences.
Other models that run great on M4 Pro
FAQ (20)
What GPU do I need to run TRELLIS Image Large?
To run TRELLIS Image Large, you need a GPU with at least 12 GB of VRAM. NVIDIA RTX 3060 or higher is recommended.
Is TRELLIS Image Large good for coding?
TRELLIS Image Large is primarily designed for generating 3D models from images, not for coding tasks. It is not suitable for code generation or programming assistance.
TRELLIS Image Large vs Llama 3.1 8B?
TRELLIS Image Large has 1.2 billion parameters and specializes in image-to-3D conversion, while Llama 3.1 8B is a text-based model with 8 billion parameters, making it better suited for language tasks.
Can I run TRELLIS Image Large on a Mac?
Yes, you can run TRELLIS Image Large on a Mac with a compatible GPU that has at least 12 GB of VRAM, such as an AMD Radeon Pro W5700X or higher.
How much VRAM does TRELLIS Image Large need?
TRELLIS Image Large requires 12 GB of VRAM to run effectively, regardless of quantization.
Is TRELLIS Image Large censored?
TRELLIS Image Large is not inherently censored, but its outputs may be influenced by the training data and any filters applied by the user or platform.
Is TRELLIS Image Large commercial-use allowed?
Yes, TRELLIS Image Large is licensed under the MIT License, which allows for commercial use without additional restrictions.
TRELLIS Image Large context length?
The context length for TRELLIS Image Large is unknown, as it primarily focuses on image-to-3D conversion rather than text processing.
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