Can RTX 4080 SUPER run TRELLIS Image Large?
Yes — runs locally
~156 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 4080 SUPER (16 GB VRAM) handles TRELLIS Image Large comfortably using the FP16 quantization, which fits in 12.0 GB. Expected throughput is around 156 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 RTX 4080 SUPER
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run TRELLIS Image Large on an NVIDIA GeForce RTX 4080 SUPER with FP16 quantization for Grade A performance at ~77 tok/sec.
Prerequisites
Before starting, ensure you have at least 2.4GB of free disk space, a 64-bit version of Windows or Linux, and the latest NVIDIA drivers (version 525.60.12 or later) with CUDA 11.8 installed.
Expected performance
With the FP16 quantization, you can expect the model to run at approximately 77 tokens per second, using around 12.0GB of VRAM. The remaining 4.0GB of VRAM provides headroom for handling larger context windows, enabling the processing of more complex images without running out of memory.
1. Install runtimeOllama
pip install ollama
ollama init2. 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 --model=TRELLIS-image-large --device=cuda --quant=fp16
ollama interactive4. Optimize for RTX 4080 SUPER
For optimal performance on the NVIDIA GeForce RTX 4080 SUPER with 16GB VRAM, use the --n-gpu-layers flag to specify the number of layers to offload to the GPU. Set --n-gpu-layers to 12 to balance memory usage and speed. Enable flash attention with --flash-attn to reduce memory usage and improve performance. With 12GB VRAM used by the model, you will have 4GB of VRAM headroom for context, allowing for larger input images.
Troubleshooting
Out of memory error during inference
Reduce the batch size or decrease the --n-gpu-layers value to free up more VRAM.
Slow inference speed
Ensure that the latest NVIDIA drivers and CUDA are installed, and enable flash attention with --flash-attn.
Model fails to load
Verify that the model file has been downloaded correctly and is not corrupted. Re-run the download command if necessary.
Alternative runtimes
Alternative runtimes like LM Studio, llama.cpp, and Jan can be used if you prefer different features or need better support for specific use cases. LM Studio offers a more user-friendly interface, while llama.cpp provides more fine-grained control over optimizations. Jan is a lightweight alternative that may be suitable for simpler tasks or environments with limited resources.
Other models that run great on RTX 4080 SUPER
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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