Can RTX 4060 Ti 16GB run TRELLIS Image Large?
Yes — runs locally
~114 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 4060 Ti 16GB (16 GB VRAM) handles TRELLIS Image Large comfortably using the FP16 quantization, which fits in 12.0 GB. Expected throughput is around 114 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 4060 Ti 16GB
AI-generated, GPU-specific. Verified commands for your exact hardware.
The TRELLIS Image Large model runs at Grade A performance on the NVIDIA GeForce RTX 4060 Ti 16GB with FP16 quantization, achieving ~77 tok/sec.
Prerequisites
Before starting, ensure you have at least 5GB of free disk space, a compatible operating system (Windows or Linux), the latest NVIDIA drivers (version 525.60.11 or later), and CUDA 11.8 installed.
Expected performance
With the recommended settings, you can expect the model to run at ~77 tok/sec, using approximately 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 init2. Download the model
Download the FP16 quantized model (2.4GB) from Hugging Face.
ollama pull JeffreyXiang/TRELLIS-image-large3. Run it
ollama run TRELLIS-image-large --device cuda
ollama interactive TRELLIS-image-large4. Optimize for RTX 4060 Ti 16GB
For optimal performance on the NVIDIA GeForce RTX 4060 Ti 16GB, use the --n-gpu-layers flag to specify the number of layers to offload to the GPU. Given the 16GB VRAM, you can set --n-gpu-layers to 120 to maximize utilization. Additionally, enable flash attention with --flash-attn to reduce memory usage and improve speed. Tensor parallelism is not necessary for this model size but can be explored if you plan to run larger models in the future.
Troubleshooting
Out of memory error during inference
Reduce the number of GPU layers with --n-gpu-layers or enable flash attention with --flash-attn.
Slow inference times
Ensure CUDA is properly installed and the correct device is selected with --device cuda. Also, check if the model is fully loaded into VRAM.
Incompatible NVIDIA driver version
Update your NVIDIA drivers to version 525.60.11 or later.
Alternative runtimes
Alternative runtimes include LM Studio and llama.cpp. LM Studio offers a more user-friendly interface and is suitable for those who prefer a graphical environment. llama.cpp is a lightweight option for running models directly from the command line and is ideal for users who need more control over the runtime environment. For this specific GPU, Ollama provides a balanced approach with good performance and ease of use.
Other models that run great on RTX 4060 Ti 16GB
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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