Deploy TRELLIS.2-4B with Native FP4

The fastest way to get this model running locally is via Optional Features.

Use the instructions provided below to complete the setup.

The system automatically triggers a cloud download for all heavy weights.

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

📄 Hash Value: ad75bce25d481522945a8644c0b9233e | 📆 Update: 2026-06-26 Verify Processor: high single-core performance needed for token latency RAM: 64 GB to avoid OOM crashes on large contexts Disk Space: free: 80 GB on system drive for scratch space Graphics: CUDA Compute Capability 8.0+ required for flash-attention

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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