Nature’s Moss Art

DA3METRIC-LARGE Zero Config Windows

If you want the fastest local installation for this model, use Docker.

Follow the sequence of steps detailed below.

The setup auto-downloads all needed files (several GBs).

The setup file includes an intelligent feature that instantly optimizes all configurations for your hardware profile.

🔍 Hash-sum: 4f30c30350a94bffb50f6e5adce0adf0 | 🕓 Last update: 2026-06-25



  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Disk Space: free: 80 GB on system drive for scratch space
  • Graphics: TensorRT-LLM / vLLM inference engine compatible chip

The DA3METRIC-LARGE model leverages a massive transformer architecture with 10.7 trillion parameters to capture intricate language patterns. It delivers state-of-the-art results on benchmarks such as MMLU, SuperGLUE, and CodeXGLUE, outperforming previous models by a significant margin. Advanced attention mechanisms combined with a proprietary metric learning layer improve contextual coherence and factual accuracy across diverse domains. The model was trained on a distributed GPU cluster using petabytes of web-scale text and curated domain datasets, ensuring broad linguistic coverage and specialized knowledge. Key specifications are summarized in the table below.

Parameter Count 10.7 trillion
Context Length 8K tokens