Can RTX 5080 run TRELLIS Image Large?
Yes — runs locally
~156 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 5080 (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 5080
AI-generated, GPU-specific. Verified commands for your exact hardware.
TRELLIS Image Large runs snappily on the NVIDIA GeForce RTX 5080 with FP16 quantization, achieving ~77 tok/sec and using 12.0GB VRAM.
Prerequisites
Before starting, ensure you have at least 3GB of free disk space, a compatible operating system (Windows or Linux), the latest NVIDIA drivers (version 525.60 or later), and CUDA 11.8 installed.
Expected performance
With the FP16 quantization, you can expect the model to run at ~77 tok/sec, utilizing 12.0GB of VRAM. This leaves 4.0GB of VRAM for context, allowing for a practical context window of several hundred tokens depending on the complexity of the input images.
1. Install runtimeOllama
pip install ollama
ollama config set runtime cuda2. 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 interact TRELLIS-image-large4. Optimize for RTX 5080
For optimal performance on the NVIDIA GeForce RTX 5080 with 16GB VRAM, use the --n-gpu-layers flag to offload layers to the GPU. Enable flash attention (--flash-attn) to reduce memory usage and improve speed. With 12.0GB VRAM in use, you have 4.0GB of headroom for larger context windows. Consider using tensor parallelism (--tensor-parallel-size 2) if you need to further optimize performance.
Troubleshooting
Out of memory errors during inference
Reduce the number of layers offloaded to the GPU using --n-gpu-layers <num_layers> or enable flash attention with --flash-attn.
Slow inference times
Ensure CUDA is properly configured and try enabling tensor parallelism with --tensor-parallel-size 2.
Model fails to load
Verify that the model files are correctly downloaded and 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 need more control over the execution environment or specific features. LM Studio is ideal for a GUI-based workflow, llama.cpp offers low-level customization, and Jan is suitable for distributed training scenarios. However, Ollama provides a streamlined and easy-to-use interface for most users on the NVIDIA GeForce RTX 5080.
Other models that run great on RTX 5080
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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