license: apache-2.0
language:
- en
base_model:
- Qwen/Qwen3-4B-Thinking-2507
pipeline_tag: text-generation
Jan-v1: Advanced Agentic Language Model
Overview
Introducing Jan-v1, the first release in the Jan Family – specifically designed for advanced agentic reasoning and complex problem-solving within the Jan App. Building on the innovative agentic capabilities of our earlier Lucy model, Jan-v1 represents a significant leap forward through strategic model scaling.
Jan-v1 leverages the newly released Qwen3-4B-thinking model to deliver significantly enhanced reasoning capabilities and effective tool utilizatio. This architectural evolution is designed to deliver superior performance on complex agentic tasks, setting a new benchmark for accessible, high-performance AI.
Evaluation
Question Answering (SimpleQA)
For question-answering, Jan-v1 shows a significant performance gain from model scaling, achieving 91.2% accuracy.
Model | SimpleQA Accuracy |
---|---|
Jan-v1 (Ours) | 91.1% |
Qwen3-4B-thinking-2507 | 86.5% |
Jan-nano-128k-MCP (YaRN 130k) | 83.2% |
Jan-nano-MCP | 80.7% |
Jan-nano-MCP (YaRN 130k) | 79.7% |
Lucy (YaRN 130k) | 78.3% |
DeepSeek-V3-MCP | 78.2% |
ChatGPT-4.5 | 62.5% |
Baseline-MCP | 59.2% |
Gemini-2.5-Pro | 52.9% |
Claude-3.7-Sonnet | 50% |
o3 | 49.4% |
Grok-3 | 44.6% |
o1 | 42.6% |
The 91.2% SimpleQA accuracy represents a significant milestone in factual question answering for models of this scale, demonstrating the effectiveness of our scaling and fine-tuning approach.
Report Generation & Factuality
Evaluated on a benchmark testing factual report generation from web sources, using an LLM-as-judge. The benchmark includes our proprietary Jan Exam - Longform
and the DeepResearchBench
.
Model | Average Overall Score |
---|---|
o4-mini | 7.30 |
Jan-v1-4B (Ours) | 7.17 |
gpt-4.1 | 6.90 |
Qwen3-4B-Thinking-2507 | 6.84 |
4o-mini | 6.60 |
Jan-nano-128k | 5.63 |
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 Menlo/Jan-v1 \
--host 0.0.0.0 \
--port 1234 \
--enable-auto-tool-choice \
--tool-call-parser hermes
Using llama.cpp:
llama-server --model jan-v1.gguf \
--host 0.0.0.0 \
--port 1234
Recommended Parameters
temperature: 0.7
top_p: 0.9
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
📄 Citation
Updated Soon