How to Run TRELLIS.2-4B Step-by-Step

How to Run TRELLIS.2-4B Step-by-Step

To install this model locally in the shortest time, opt for Docker.

Simply follow the directions outlined below.

There is no manual tuning required; the builder will automatically deploy the best matching configuration.

🧾 Hash-sum — 9a8aa71611cbfd0a918a3a113e6319a5 • 🗓 Updated on: 2026-06-27



  • Processor: 6-core 3.5 GHz minimum required
  • RAM: minimum 16 GB for stable 8B model loading
  • Disk: 150+ GB for high-context vector database storage
  • Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading

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.

SpecificationValue
Parameter Count2.4 B
Context Length8 K tokens
Training Data TypesCode, scientific, conversational
Primary Use CasesText generation, summarization, Q&A, multimodal tasks
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