Jan-v1: Advanced Agentic Language Model

Overview

Update: Jan-v1-2509

We have released a small weight update, jan-v1-2509, which refines the original v1.

• No architectural changes.
• Slightly lower performance on SimpleQA compared to jan-v1.
• Slightly mproved results on other chat benchmarks and overall more reliable

Jan-v1 is the first release in the Jan Family, designed for agentic reasoning and problem-solving within the Jan App. Based on our Lucy model, Jan-v1 achieves improved performance through model scaling.

Jan-v1 uses the Qwen3-4B-thinking model to provide enhanced reasoning capabilities and tool utilization. This architecture delivers better performance on complex agentic tasks.

Performance

Question Answering (SimpleQA)

For question-answering, Jan-v1 shows a significant performance gain from model scaling, achieving 91.1% accuracy.

The 91.1% SimpleQA accuracy with Jan-v1 remains a highlight, though Jan-v1-2509 focuses on balancing factual QA with improved reliability across chat-based reasoning tasks.

Chat Benchmarks

These benchmarks evaluate the model's conversational and instructional capabilities.

Quick Start

Integration with Jan App

Jan-v1 is optimized for direct integration with the Jan App. Simply select the model from the Jan App interface for immediate access to its full capabilities.

Local Deployment

Using vLLM:

vllm serve janhq/Jan-v1-2509 \
    --host 0.0.0.0 \
    --port 1234 \
    --enable-auto-tool-choice \
    --tool-call-parser hermes
    

Using llama.cpp:

llama-server --model Jan-v1-2509-Q4_K_M.gguf \
    --host 0.0.0.0 \
    --port 1234 \
    --jinja \
    --no-context-shift

Recommended Parameters

temperature: 0.6
top_p: 0.95
top_k: 20
min_p: 0.0
max_tokens: 2048

🤝 Community & Support

• Discussions: HuggingFace Community
• Jan App: Learn more about the Jan App at jan.ai

(*) Note

By default we have system prompt in chat template, this is to make sure the model having the same performance with the benchmark result. You can also use the vanilla chat template without system prompt in the file chat_template_raw.jinja.

📄 Citation

Updated Soon

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