volosati/Jan-v1-4B
Jan-v1 is a 4 billion parameter agentic language model developed by volosati, part of the Jan Family, designed for advanced reasoning and problem-solving. Based on the Lucy model and utilizing Qwen3-4B-thinking, it achieves enhanced performance on complex agentic tasks. This model demonstrates 91.1% accuracy on SimpleQA, indicating strong factual question-answering capabilities for its scale. It is optimized for direct integration and use within the Jan App.
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Jan-v1: Advanced Agentic Language Model
Jan-v1 is the inaugural release in the Jan Family of models, developed by volosati and specifically engineered for agentic reasoning and problem-solving. This 4 billion parameter model is built upon the existing Lucy model and integrates the Qwen3-4B-thinking architecture to deliver improved performance on complex agentic tasks.
Key Capabilities & Performance
- Enhanced Agentic Reasoning: Designed to excel in scenarios requiring advanced reasoning and tool utilization.
- Strong Question Answering: Achieves 91.1% accuracy on SimpleQA, demonstrating significant gains in factual question answering through model scaling and fine-tuning.
- Conversational & Instructional: Evaluated with chat benchmarks to ensure robust conversational and instructional capabilities.
Integration & Deployment
Jan-v1 is primarily optimized for seamless integration with the Jan App, allowing users to access its full capabilities directly. For developers, it supports local deployment via vLLM and llama.cpp, with recommended parameters for optimal performance. The model includes a default system prompt in its chat template to maintain benchmark performance, with an option for a vanilla chat template.