Powerful AI, Pocket-Sized

Deploy state-of-the-art language models on mobile and edge devices with advanced distillation, quantization, and optimization techniques.

Explore Toolkit

Core Capabilities

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Model Distillation

Compress large language models into tiny, efficient versions while preserving accuracy. Train student models from teacher networks with minimal quality loss.

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Quantization

Reduce model size by 75%+ through INT8/INT4 quantization. Achieve 4x faster inference with negligible accuracy degradation on edge hardware.

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LoRA Fine-tuning

Adapt pre-trained models to your specific tasks using Low-Rank Adaptation. Fine-tune with minimal compute and memory requirements.

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Offline Inference

Run models entirely on-device without internet connectivity. Ensure data privacy and ultra-low latency for real-time applications.

Performance Impact

75%+

Model Size Reduction

4x

Faster Inference

95%+

Accuracy Retained

<50MB

Typical Model Size

Real-World Applications

๐Ÿ“ฑ Mobile Apps

Integrate intelligent text generation, translation, and summarization directly into iOS and Android applications.

๐ŸŒ IoT Devices

Deploy language understanding to smart home devices, wearables, and embedded systems with limited resources.

๐Ÿ”’ Privacy-First Apps

Build applications that process sensitive data entirely on-device, ensuring complete user privacy and GDPR compliance.

โšก Edge Computing

Enable real-time AI inference at the network edge, reducing latency and bandwidth costs for distributed systems.

Ready to Get Started?

Deploy tiny language models on any device in minutes.