diff --git a/docs/src/pages/docs/menlo-models/jan-nano.mdx b/docs/src/pages/docs/menlo-models/jan-nano.mdx index baa9312d9..bec95b38d 100644 --- a/docs/src/pages/docs/menlo-models/jan-nano.mdx +++ b/docs/src/pages/docs/menlo-models/jan-nano.mdx @@ -86,3 +86,40 @@ Here are some example queries to showcase Jan-Nano's web search capabilities: 8. **Cultural Events**: What major music festivals are happening in Europe this summer and who are the headliners? 9. **Health & Medicine**: What are the latest developments in mRNA vaccine technology and its applications beyond COVID-19? 10. **Space Exploration**: What are the current missions being conducted by NASA, ESA, and China's space program? + + +## FAQ + +- What are the recommended GGUF quantizations? + - Q8 GGUF is recommended for best performance + - iQ4_XS GGUF for very limited VRAM setups + - Avoid Q4_0 and Q4_K_M as they show significant performance degradation + +- Can I run this on a laptop with 8GB RAM? + - Yes, but use the recommended quantizations (iQ4_XS) + - Note that performance may be limited with Q4 quantizations + +- How much did the training cost? + - Training was done on internal A6000 clusters + - Estimated cost on RunPod would be under $100 using H200 + - Hardware used: + - 8xA6000 for training code + - 4xA6000 for vllm server (inferencing) + +- What frontend should I use? + - Jan Beta (recommended) - Minimalistic and polished interface + - Download link: https://jan.ai/docs/desktop/beta + +- Getting Jinja errors in LM Studio? + - Use Qwen3 template from other LM Studio compatible models + - Disable “thinking” and add the required system prompt + - Fix coming soon in future GGUF releases +- Having model loading issues in Jan? + - Use latest beta version: Jan-beta_0.5.18-rc6-beta + - Ensure proper CUDA support for your GPU + - Check VRAM requirements match your quantization choice + +## Resources + +- [Jan-Nano Model on Hugging Face](https://huggingface.co/Menlo/Jan-nano) +- [Jan-Nano GGUF on Hugging Face](https://huggingface.co/Menlo/Jan-nano-gguf)