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--- |
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license: apache-2.0 |
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language: |
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- en |
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base_model: |
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- Menlo/Jan-nano |
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pipeline_tag: text-generation |
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library_name: transformers |
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--- |
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# Jan-Nano-128k: Empowering deeper research through extended context understanding. |
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<sub>*Note: Jan-Nano is a non-thinking model.*</sub> |
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[](https://github.com/menloresearch/deep-research) |
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[](https://opensource.org/licenses/Apache-2.0) |
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<div align="center"> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/65713d70f56f9538679e5a56/NP7CvcjOtLX8mST0t7eAM.png" width="300" alt="Jan-Nano-128k"> |
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</div> |
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**Authors:** [Alan Dao](https://scholar.google.com/citations?user=eGWws2UAAAAJ&hl=en), [Bach Vu Dinh](https://scholar.google.com/citations?user=7Lr6hdoAAAAJ&hl=vi) |
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## Overview |
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Jan-Nano-128k represents a significant advancement in compact language models for research applications. Building upon the success of [Jan-Nano](https://huggingface.co/Menlo/Jan-nano), this enhanced version features a **native 128k context window** that enables deeper, more comprehensive research capabilities without the performance degradation typically associated with context extension methods. |
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**Key Improvements:** |
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- **🔍 Research Deeper**: Extended context allows for processing entire research papers, lengthy documents, and complex multi-turn conversations |
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- **⚡ Native 128k Window**: Built from the ground up to handle long contexts efficiently, maintaining performance across the full context range |
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- **📈 Enhanced Performance**: Unlike traditional context extension methods, Jan-Nano-128k shows improved performance with longer contexts |
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This model maintains full compatibility with Model Context Protocol (MCP) servers while dramatically expanding the scope of research tasks it can handle in a single session. |
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## Evaluation |
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Jan-Nano-128k has been rigorously evaluated on the SimpleQA benchmark using our MCP-based methodology, demonstrating superior performance compared to its predecessor: |
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## Why Jan-Nano-128k? |
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Traditional approaches to extending context length, such as YaRN (Yet another RoPE extensioN), often result in performance degradation as context length increases. Jan-Nano-128k breaks this paradigm: |
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This fundamental difference makes Jan-Nano-128k ideal for research applications requiring deep document analysis, multi-document synthesis, and complex reasoning over large information sets. |
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## 🖥️ How to Run Locally |
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Jan desktop will eventually support this model (WIP). Otherwise you can check the deployment options below that we have tested. |
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For additional tutorials and community guidance, visit our [Discussion Forums](https://huggingface.co/Menlo/Jan-nano-128k/discussions). |
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### Deployment |
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Deploy using VLLM: |
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```bash |
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vllm serve Menlo/Jan-nano-128k \ |
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--host 0.0.0.0 \ |
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--port 1234 \ |
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--enable-auto-tool-choice \ |
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--tool-call-parser hermes \ |
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--rope-scaling '{"rope_type":"yarn","factor":3.2,"original_max_position_embeddings":40960}' --max-model-len 131072 |
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``` |
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Or `llama-server` from `llama.cpp`: |
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```bash |
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llama-server ... --rope-scaling yarn --rope-scale 3.2 --yarn-orig-ctx 40960 |
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``` |
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**Note:** The chat template is included in the tokenizer. For troubleshooting, download the [Non-think chat template](https://qwen.readthedocs.io/en/latest/_downloads/c101120b5bebcc2f12ec504fc93a965e/qwen3_nonthinking.jinja). |
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### Recommended Sampling Parameters |
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```yaml |
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Temperature: 0.7 |
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Top-p: 0.8 |
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Top-k: 20 |
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Min-p: 0.0 |
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``` |
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## FAQ: |
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- I have Jinja template issue with LMStudio, how can i fix? [Here](https://huggingface.co/Menlo/Jan-nano-128k-gguf/discussions/1#6862fe2375cb85f79b28d69c) |
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## 🤝 Community & Support |
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- **Discussions**: [HuggingFace Community](https://huggingface.co/Menlo/Jan-nano-128k/discussions) |
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- **Issues**: [GitHub Repository](https://github.com/menloresearch/jan/issues) |
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- **Documentation**: [Official Docs](https://menloresearch.github.io/deep-research/) |
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## 📄 Citation |
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```bibtex |
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@misc{dao2025jannanotechnicalreport, |
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title={Jan-nano Technical Report}, |
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author={Alan Dao and Dinh Bach Vu}, |
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year={2025}, |
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eprint={2506.22760}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL}, |
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url={https://arxiv.org/abs/2506.22760}, |
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} |
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``` |
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--- |
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*Jan-Nano-128k: Empowering deeper research through extended context understanding.* |
