Can RTX 3080 Ti run TRELLIS Image Large?
Yes — runs locally
~90 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 3080 Ti (12 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 RTX 3080 Ti
AI-generated, GPU-specific. Verified commands for your exact hardware.
TRELLIS Image Large runs on an NVIDIA GeForce RTX 3080 Ti with a Grade B performance at ~58 tok/sec using the FP16 quantization. It requires 12.0GB VRAM and outputs glTF files.
Prerequisites
Before starting, ensure you have at least 2.4GB of free disk space, a compatible operating system (Windows or Linux), the latest NVIDIA drivers (version 510.47.03 or later), and CUDA 11.4 or later installed.
Expected performance
With the FP16 quantization, you can expect a token generation rate of ~58 tok/sec and 12.0GB VRAM in use. The practical context window will be limited by the available VRAM, so it is advisable to keep the context length manageable to avoid out-of-memory errors.
1. Install runtimeOllama
pip install ollama
ollama init2. Download the model
Download the FP16 quantized version of TRELLIS Image Large, which is 2.4GB in size, from the Hugging Face repository.
ollama pull JeffreyXiang/TRELLIS-image-large3. Run it
ollama run TRELLIS-image-large --device cuda
ollama serve4. Optimize for RTX 3080 Ti
For optimal performance on the NVIDIA GeForce RTX 3080 Ti with 12GB VRAM, use the --n-gpu-layers flag to offload some layers to the CPU if necessary. Enable flash attention (--flash-attn) to reduce memory usage and improve speed. Given the 12.0GB VRAM requirement, there is no additional headroom for increasing the context length.
Troubleshooting
Out of memory error during inference
Reduce the batch size or context length, or use the --n-gpu-layers flag to offload some layers to the CPU.
Slow inference speed
Ensure that the latest NVIDIA drivers and CUDA are installed, and enable flash attention using the --flash-attn flag.
Model fails to load
Verify that the model file is correctly downloaded and not corrupted. Try re-downloading the model using the 'ollama pull' command.
Alternative runtimes
Alternative runtimes include LM Studio, llama.cpp, and Jan. LM Studio is suitable for a more user-friendly interface, while llama.cpp offers more fine-grained control over optimizations. Jan is a lightweight option for quick prototyping. Choose based on your specific needs for performance, ease of use, and customization.
Other models that run great on RTX 3080 Ti
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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