Can RTX 4090 run TRELLIS Image Large?
Yes — runs locally
~192 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 4090 (24 GB VRAM) handles TRELLIS Image Large comfortably using the FP16 quantization, which fits in 12.0 GB. Expected throughput is around 192 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 4090
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run TRELLIS Image Large on an NVIDIA GeForce RTX 4090 with FP16 quantization for Grade S performance at ~116 tok/sec.
Prerequisites
Before starting, ensure you have at least 2.4GB of free disk space, a compatible operating system (Windows or Linux), and the latest NVIDIA drivers (version 525.60.13 or later) with CUDA 11.8 installed.
Expected performance
With the FP16 quantization, you can expect the model to run at approximately 116 tokens per second, using around 12.0GB of VRAM. The remaining 12.0GB of VRAM provides ample headroom for handling larger context windows, enabling the processing of higher-resolution images or more detailed 3D models.
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 --quantization fp16
ollama interactive --model TRELLIS-image-large --quantization fp164. Optimize for RTX 4090
For optimal performance on the NVIDIA GeForce RTX 4090 with 24GB VRAM, set --n-gpu-layers to 32 to fully utilize the GPU memory. Enable flash attention (--flash-attn) to speed up inference and reduce VRAM usage. Given the 24GB VRAM, you can allocate up to 12GB for the model and still have 12GB for context, allowing for larger input images or more complex 3D models.
Troubleshooting
Out of memory errors during inference
Reduce the number of layers allocated to the GPU using --n-gpu-layers <num_layers> or decrease the batch size.
Slow inference times
Ensure flash attention is enabled with --flash-attn and check that your CUDA installation is up to date.
Model fails to load
Verify that the model files are correctly downloaded and not corrupted. Try re-downloading the model with 'ollama pull JeffreyXiang/TRELLIS-image-large'.
Alternative runtimes
Alternative runtimes like LM Studio, llama.cpp, and Jan can be used if you need more control over the inference process or if you encounter issues with Ollama. LM Studio is ideal for a user-friendly interface, while llama.cpp offers fine-grained control over optimizations. Jan is a lightweight option for quick prototyping. Choose based on your specific needs and the level of customization required.
Other models that run great on RTX 4090
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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