SupraLabs has released Supra-Router-51M, a compact language model designed for efficient prompt routing within multi-model AI ecosystems. With only 51.7 million parameters, this model can determine whether a user's request should be handled by a local edge model or sent to a more powerful cloud-based system. It was fine-tuned on the SupraLabs/Prompt-Routing-Dataset and utilizes multi-task sequence generation to analyze prompt properties before routing. AI
IMPACT Enables more efficient routing of requests in multi-model AI systems, potentially reducing latency and costs.
RANK_REASON Model release from a non-frontier lab with detailed technical instructions.
- SupraLabs
- Supra-Router-51M
- Docker
- Google Colab
- Hugging Face
- Kaggle
- SGLang
- SupraLabs/Prompt-Routing-Dataset
- SupraLabs/Supra-Router-51M
- vLLM
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