phi4-mini-npu-mobile

Phi-4-mini

Run Phi-4-mini optimized for Qualcomm NPUs with nexaSDK.

Model Description

Phi-4-mini is a ~3.8B-parameter instruction-tuned model from Microsoft’s Phi-4 family. Trained on a blend of synthetic “textbook-style” data, filtered public web content, curated books/Q&A, and high-quality supervised chat data, it emphasizes reasoning-dense capabilities while maintaining a compact footprint. This NPU Turbo build uses Nexa’s Qualcomm backend (QNN/Hexagon) to deliver lower latency and higher throughput on-device, with support for 128K context and efficient long-context memory handling.

Features

• Lightweight yet capable: strong reasoning (math/logic) in a compact 3.8B model.
• Instruction-following: enhanced SFT + DPO alignment for reliable chat.
• Content generation: drafting, completion, summarization, code comments, and more.
• Conversational AI: context-aware assistants/agents with long-context support (128K).
• NPU-Turbo path: INT8/INT4 quantization, op fusion, and KV-cache residency for Snapdragon® NPUs via nexaSDK.
• Customizable: fine-tune/adapt for domain-specific or enterprise use.

Use Cases

• Personal & enterprise chatbots
• On-device/offline assistants (latency-bound scenarios)
• Document/report/email summarization
• Education, tutoring, and STEM reasoning tools
• Vertical applications (e.g., healthcare, finance, legal) with appropriate safeguards

Inputs and Outputs

Input:

• Text prompts or conversation history (chat-format, tokenized sequences).

Output:

• Generated text: responses, explanations, or creative content.
• Optionally: raw logits/probabilities for advanced downstream tasks.

License

This model is released under the Creative Commons Attribution–NonCommercial 4.0 (CC BY-NC 4.0) license.
Non-commercial use, modification, and redistribution are permitted with attribution.
For commercial licensing, please contact dev@nexa.ai.

References

📰 Phi-4-mini Microsoft Blog <br> 📖 Phi-4-mini Technical Report <br> 👩‍🍳 Phi Cookbook <br> 🚀 Model paper