The most rapid route to a local installation of this model is through Docker.

Follow the guidelines below to continue.

The installer automatically pulls the model (could be multiple GBs).

The installer will automatically analyze your hardware and select the optimal configuration for your system.

🔍 Hash-sum: 7e581bb28ae42428bef91dad14aced04 | 🕓 Last update: 2026-06-25 Verify CPU: multi-threading optimized for fast prompt processing RAM: required: 16 GB absolute minimum for small models Storage:100 GB free space for HuggingFace cache folder Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

The TRELLIS.2-4B model represents a significant advancement in open‑source language models, delivering state‑of‑the‑art performance while maintaining a manageable parameter count of 2.4 billion. Built on a transformer‑based architecture with enhanced attention mechanisms, it achieves superior comprehension of both textual and multimodal inputs. Trained on a diverse corpus spanning code, scientific literature, and conversational data, the model exhibits robust generalization across a wide range of downstream tasks. Its efficient design enables deployment on standard GPU clusters, making advanced AI capabilities accessible to developers and researchers worldwide. A dedicated

with key technical specifications is provided below for quick reference.

Specification	Value
Parameter Count	2.4 B
Context Length	8 K tokens
Training Data Types	Code, scientific, conversational
Primary Use Cases	Text generation, summarization, Q&A, multimodal tasks

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