DA3METRIC-LARGE Windows 11 Easy Build

DA3METRIC-LARGE Windows 11 Easy Build

Deploying this model locally is quickest when done via Docker.

Use the instructions provided below to complete the setup.

In case you want to set things up without relying on virtual infrastructure, just follow the text below.

🧩 Hash sum → b398a29d11a05becad456fc42e11bca9 — Update date: 2026-06-25



  • CPU: multi-threading optimized for fast prompt processing
  • RAM: minimum 16 GB for stable 8B model loading
  • 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
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