How Liquid AI Uses ExecuTorch to Power Efficient, Flexible On-Device Intelligence | Liquid AI

When we needed to deploy our hybrid LFM models on-device, we faced a critical challenge: existing inference engines couldn’t handle the unique combination of attention and recurrent layers our architecture required. By adopting PyTorch ExecuTorch in late 2024, we achieved seamless deployment with 2× faster inference and significantly lower latency, proving that the right infrastructure choice can unlock entirely new possibilities for edge AI.