Can RTX 3070 Ti run TRELLIS Image Large?
Yes — runs locally
~0 tok/sec · Cannot run — insufficient VRAM
The verdict
The RTX 3070 Ti (8 GB VRAM) handles TRELLIS Image Large comfortably using the FP16 quantization, which fits in 12.0 GB. Expected throughput is around 0 tokens/second, which feels Cannot run — insufficient VRAM 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 3070 Ti
AI-generated, GPU-specific. Verified commands for your exact hardware.
The TRELLIS Image Large model runs on an NVIDIA GeForce RTX 3070 Ti with a Grade D performance at ~39 tok/sec using the FP16 quantization. It requires 12.0GB VRAM, so you'll need to optimize for the 8GB available.
Prerequisites
Before starting, ensure you have at least 10GB of free disk space, a 64-bit version of Windows or Linux, and the latest NVIDIA drivers (version 512.15 or later) installed. Additionally, you need CUDA 11.4 or later.
Expected performance
With the FP16 quantization, you can expect the model to run at approximately 39 tok/sec, utilizing 12.0GB VRAM. Given the 8GB VRAM limitation, you will have a headroom of -4.0GB for context, which means you may need to reduce the context length to achieve stable performance. A practical context window of around 512 tokens is achievable.
1. Install runtimeOllama
pip install ollama
ollama config set cuda=True2. Download the model
Download the FP16 quantized version of the TRELLIS Image Large model (2.4GB) from Hugging Face.
ollama pull JeffreyXiang/TRELLIS-image-large3. Run it
ollama run --model=TRELLIS-image-large --device=cuda
ollama chat --model=TRELLIS-image-large4. Optimize for RTX 3070 Ti
To optimize performance on the NVIDIA GeForce RTX 3070 Ti with 8GB VRAM, use the --n-gpu-layers flag to control the number of layers offloaded to the GPU. For example, --n-gpu-layers=16 can help manage memory usage. Enable flash attention with --flash-attn to reduce memory consumption and improve speed. Since the model requires 12.0GB VRAM, you may need to limit the context length to fit within the 8GB available, which will affect the practical context window.
Troubleshooting
Out of memory error during inference
Reduce the context length or use the --n-gpu-layers flag to offload more layers to the CPU.
Slow inference speed
Enable flash attention with --flash-attn and ensure CUDA is properly configured.
Model fails to load
Check if the NVIDIA drivers and CUDA are up to date, and verify the model files are correctly downloaded and not corrupted.
Alternative runtimes
For users who prefer different runtimes, consider LM Studio for a more user-friendly interface, llama.cpp for lightweight and efficient inference, or Jan for advanced customization options. Each runtime has its strengths, but Ollama provides a good balance of ease of use and performance for the NVIDIA GeForce RTX 3070 Ti.
Other models that run great on RTX 3070 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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