On-device LLM

Run high-performance language models locally on mobile, desktop, and edge hardware without an internet connection.

On-device LLMs eliminate latency and privacy risks by moving inference from the cloud to local silicon. Using frameworks like MLC LLM or Apple’s Core ML, developers deploy quantized models (4-bit or 8-bit) that leverage NPU and GPU acceleration on chips like the M3 or Snapdragon 8 Gen 3. This architecture ensures data sovereignty for enterprise applications and enables offline functionality for tools like local coding assistants or private medical transcription. By bypassing API costs and token limits, teams gain predictable performance and total control over the model lifecycle.

https://mlc.ai/mlc-llm/