Liquid AI
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About
Liquid AI develops a new generation of foundation models designed for extreme efficiency and multi-platform deployment. Spun out of MIT CSAIL, the company focuses on creating Liquid Foundation Models (LFMs) that prioritize low latency, privacy, and security-critical performance. Unlike traditional large-scale models that require massive cloud-based GPU clusters, these models are architected to run locally on a variety of hardware, including standard CPUs and Neural Processing Units (NPUs), enabling high-intelligence applications directly on edge devices. The ecosystem centers around the LFM2 series, which includes diverse modalities such as text, vision, and audio, with parameter sizes ranging from 350M to several billion. A notable highlight is the LFM2.5-1.2B-Thinking model, which provides on-device reasoning while maintaining a memory footprint under 1GB. Developers manage these models through LEAP, a platform for building, specializing, and deploying AI workflows. For users wanting to test models quickly, the Apollo mobile app allows for local "vibe checking" of small language models, while a web-based playground provides immediate access to their chat capabilities. The platform is primarily built for developers and enterprises in industries where data privacy and real-time processing are paramount, such as automotive, financial services, and healthcare. It is particularly valuable for robotics engineers who need agentic vision-language models to run on embedded hardware without cloud bottlenecks. E-commerce platforms can leverage their sub-20ms commerce foundation models for real-time processing. Startups can also leverage a dedicated program to receive direct engineering guidance, provided they meet specific funding and maturity criteria. What sets Liquid AI apart is its first-principles approach to model architecture, which enables white-box explainability and significant compute savings. While many competitors focus on scaling models upward, Liquid focuses on optimization, allowing for high-performance reasoning on everyday devices like laptops and smartphones. Their partnership ecosystem with major silicon providers like AMD and Qualcomm ensures that their models are deeply integrated with modern hardware architectures, providing a more sustainable and cost-efficient alternative to purely cloud-reliant AI strategies.
Pros & Cons
Models like LFM2.5-1.2B provide reasoning capabilities while fitting under 1GB of memory.
Native optimization for NPUs and CPUs allows for low-latency performance on consumer hardware.
Supports end-to-end audio processing and vision-language tasks without cloud reliance.
Provides a private local-first approach for security-critical enterprise applications.
Founded by MIT CSAIL experts with a focus on first-principles AI architecture.
Free commercial use is restricted to companies making less than $10M in annual revenue.
Startup guidance program requires specific venture funding and registration thresholds.
Advanced enterprise solutions require manual demo requests rather than instant self-service.
Mobile app is currently focused on vibe checking rather than full production deployment.
Use Cases
Automotive engineers can deploy vision-language models for edge-native autonomous systems to reduce cloud latency and increase data security.
E-commerce developers use the platform to build sub-20ms foundation models for real-time product cataloging and commerce experiences.
Financial institutions implement private local AI for real-time fraud detection to process sensitive data without external cloud exposure.
Robotics developers can use LFM2-VL-3B for agentic autonomy in embedded devices to handle complex vision tasks locally.
Consumer electronics manufacturers can integrate small reasoning models into smartphones for offline translation and secure meeting summarization.
Platform
Task
Features
• white-box explainability
• mixture-of-experts architecture
• optimization for cpus, gpus, and npus
• on-device reasoning under 1gb
• multimodal support (text, audio, vision)
• apollo mobile app for on-device testing
• leap developer platform
• liquid foundation models (lfm)
FAQs
Can I use Liquid AI models for commercial purposes?
Free open-source commercial use of Liquid Foundation Models is available for enterprises earning less than $10 million in annual revenue. Organizations exceeding this revenue threshold must contact the sales team for commercial licensing.
What hardware is Liquid AI optimized for?
Liquid's models are purpose-built to run efficiently across CPUs, GPUs, and NPUs. They highlight specific performance optimizations for AMD Ryzen and Ryzen AI processors to enable high-speed intelligence on standard laptops.
What is the LEAP platform used for?
LEAP is a developer platform designed for building, specializing, and deploying on-device AI. It allows developers to customize and deploy Liquid Foundation Models on-device in a single, unified workflow.
Does Liquid AI offer models for modalities other than text?
Yes, the LFM2 family includes multimodal capabilities such as vision-language models (LFM2-VL) and end-to-end audio foundation models. These are designed to be ultra-efficient for edge devices like cameras and sensors.
What are the requirements for the Startup program?
Startups must be privately held, founded in the last 5 years, and have at least $500K in venture-backed funding. They must also be in the seed through series C stage and be fully registered with a public presence.
Pricing Plans
Everyone
Unknown Price• Download and customize LFMs via Hugging Face
• Access to LEAP developer platform
• On-device deployment in a single workflow
• Access to tutorials and documentation
• Web-based model playground
• Free on-device intelligence via Apollo app
Startups
Unknown Price• Everything in Open Source access
• Direct access to full tech stack
• Guidance from engineering and product teams
• Customized deployment support
• Feedback and design partnership
Enterprises
Unknown Price• Everything in Open Source access
• Full-scale custom AI solutions
• White glove support for design and building
• Tailored hardware and data integration
• End-to-end intelligence solutions
Job Opportunities
Finance Manager
Build and deploy ultra-efficient multimodal foundation models on-device or in the cloud for privacy-critical applications in robotics, automotive, and more.
Benefits:
Equity in a unicorn-stage company
100% medical, dental, and vision premiums
401(k) matching plan up to 4%
Unlimited Time Off policy
Catered lunches
Experience Requirements:
6+ years of experience in Finance
Specific emphasis on Sales Finance, Strategic Finance, or FP&A
High-growth startup experience
Sales Exposure and understanding of enterprise contracts
Experience standing up or managing CRMs
Other Requirements:
Operational intuition for sales operations
Ability to architect sources of truth
Relentless automation mindset
Ability to thrive in ambiguity
Responsibilities:
Build the GTM Finance Engine
Partner with the sales team on quotas and commissions
Aid in capital allocation and headcount planning
Design workflows connecting revenue engine to general ledger
Automate invoicing and collections
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Member of Technical Staff - Frontend Engineer
Build and deploy ultra-efficient multimodal foundation models on-device or in the cloud for privacy-critical applications in robotics, automotive, and more.
Benefits:
Equity in a unicorn-stage company
100% medical, dental, and vision premiums
401(k) matching up to 4%
Unlimited PTO
Company-wide Refill Days
Experience Requirements:
Strong proficiency in React and Next.js with TypeScript
Experience with TailwindCSS and component libraries like ShadCN
Comfort working with APIs and making light backend modifications
Track record of shipping in fast-paced environments
Other Requirements:
Ability to thrive in ambiguity
Proactive decision-making skills
Product ownership mindset
Balance of speed and quality
Responsibilities:
Build frontend systems for AI model customization platform
Create intuitive interfaces for complex ML workflows
Collaborate with ML researchers and backend engineers
Polish demos and prototypes for enterprise customers
Contribute to mobile app development
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Member of Technical Staff - Product Designer
Build and deploy ultra-efficient multimodal foundation models on-device or in the cloud for privacy-critical applications in robotics, automotive, and more.
Benefits:
Equity in a unicorn-stage company
100% medical, dental, and vision premiums
401(k) matching up to 4%
Unlimited PTO
Company-wide Refill Days
Experience Requirements:
4+ years designing complex tools or platforms
Portfolio demonstrating systems thinking and interaction design
Experience translating technical complexity into usable products
Experience iterating based on prototyping and feedback
Other Requirements:
Ability to own problems and analyze user feedback
Fast-paced prototype building
Systemic thinking regarding permissions and states
Collaboration skills with engineering teams
Responsibilities:
Design intuitive flows for LEAP Workbench
Translate complex ML workflows into simple experiences
Improve UI/UX of Apollo mobile application
Analyze usage data to prioritize design improvements
Maintain and evolve design system and component library
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