New developer platform and consumer app showcase the power of reliable and efficient generative AI models deployed on local edge devices, enabling fast, private, and always-on AI experiences
Liquid AI, the foundation model company setting new standards for performance and efficiency, today announced the launch of their early-stage developer platform called Liquid Edge-AI Platform (LEAP) v0 for building and deploying AI on devices such as smartphones, laptops, wearables, drones, cars, and other local hardware – without cloud infrastructure. The company also introduced Apollo, an updated, lightweight, iOS-native application powered by LEAP that offers an interactive interface for experiencing private AI with Liquid’s latest breakthrough models.
“Our research shows developers are frustrated by the complexity, feasibility, and privacy trade-offs of current edge AI solutions,” said Ramin Hasani, co-founder and CEO of Liquid AI. “LEAP is our answer—a deployment platform designed from the ground up to make powerful, efficient, and private edge AI easy and accessible. We’re also excited to give users the ability to test our new groundbreaking models through the iOS-native app Apollo.”
LEAP v0 represents a breakthrough for edge AI, pairing a small language model (SLM) library with a developer-first interface and platform-agnostic toolchain. LEAP allows developers to deploy foundation models directly in their Android and iOS applications in 10 lines of code. Liquid AI’s goal with the new platform is to make it easy for AI novices and full-stack app developers, not just inference engineers or AI experts, to deploy local models.
To provide the true experience of private and on-device AI, Liquid has acquired Apollo designed by Aaron Ng, and has substantially evolved it into an interactive interface to utilize, vibe-check, and pair small foundation models for private use-cases of AI. Apollo provides private, secure, low-latency AI interactions fully on-device, demonstrating what’s possible when enterprises and developers aren’t constrained by internet access, cloud requirements, or bulky models.
Among other open-source SLMs, both LEAP and Apollo now include access to Liquid AI’s next-generation Liquid Foundation Models (LFM2), open-source small foundation models announced just last week that set new records in speed, energy efficiency, and instruction-following performance in the edge model class. The integration makes these high-performance models immediately available for developers to test and build edge-native AI applications.
LFM2 is designed based on Liquid AI’s first-principles approach to model design. Unlike traditional transformer-based models, LFM2 is composed of structured, adaptive operators that allow for more efficient training, faster inference, and better generalization, especially in long-context or resource-constrained scenarios.
LEAP is available starting today at leap.liquid.ai and Apollo can be downloaded from the iOS App Store here with Android coming in the next few weeks.
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