Apollo: Private, local AI now powered by Liquid AI

Tonight at #CES, Liquid’s CEO Ramin Hasani @ramin_m_h announced to the world the LFM 2.5 model library. Watch Ramin’s full announcement alongside Lisa Su, CEO of AMD, and learn how we are making intelligence accessible everywhere. Read the full release: liquid.ai/blog/introduci… LEAP: leap.liquid.ai/models HF: huggingface.co/collections/Li…

Today, we release LFM2.5, our most capable family of tiny on-device foundation models. It’s built to power reliable on-device agentic applications: higher quality, lower latency, and broader modality support in the ~1B parameter class. > LFM2.5 builds on our LFM2 device-optimized hybrid architecture > Pretraining scaled from 10T → 28T tokens > Expanded reinforcement learning post-training > Higher ceilings for instruction following 🧵

Today we introduce Liquid Labs, our advanced research unit, with the goal of understanding and building efficient and adaptive intelligence systems. Liquid Labs consolidates our existing research efforts at Liquid across architecture of foundation models, multimodality, training, data, and inference. The lab also will be home to new frontier research work across the broad range of foundation model build-up stack. Read the full announcement: liquid.ai/blog/introduci… We are hiring: jobs.ashbyhq.com/liquid-ai Also find us at NeurIPS 2025 exhibition hall! 🚀

What a weekend! We just wrapped an incredible two-day hackathon where 20 teams joined us in our SF office to build real-world applications using Liquid Foundation Models running on @AMD NUCs. The range of ideas and level of innovation were inspiring — creative builds, sharp conversations, and big ideas pushing the edge forward. Thank you to our partners at @AIatAMD and everyone who joined us and made this weekend such a blast! Stay tuned to see what they built 👀

Today, we’re announcing our partnership with @Shopify to bring Liquid Foundation Models (LFMs) to core commerce experiences. Shopify will license LFMs to enhance search and recommendations, improving relevance, conversions, and customer experience at scale. The first production deployment is a sub‑20ms LFM that enhances search. Shopify and Liquid have also co-developed a generative recommender model with a novel HSTU architecture. In controlled tests, the model beat the previous stack, leading to higher conversion rates from recommendations. 👇

Bonus for devs + builders! Across operating systems, Apollo and LEAP (by @liquidai) have come together to create a connected workflow to test and deploy on the edge, making it faster and easier to deploy locally. Vibe check and play with models on Apollo ➡️ download and deploy on LEAP. Get started on LEAP today: leap.liquid.ai

3 easy steps: Download the app → select your local model, or, connect your own → instantly access secure, fast AI on the go. Download for Android: play.google.com/store/apps/det… Download for iOS: apps.apple.com/us/app/apollo-…

🔉🤖 The announcement you’ve been waiting for is here: Apollo is available on Android! Now you can easily access all the local, secure AI technology you’ve loved on iOS from whichever phone is in your pocket. Apollo’s low-latency, cloud-free platform and library of small models lets you instantly access fast, effective AI - without sacrificing privacy or security. Get started in 🧵

Introducing Liquid Nanos ⚛️ — a new family of extremely tiny task-specific models that deliver GPT-4o-class performance while running directly on phones, laptops, cars, embedded devices, and GPUs with the lowest latency and fastest generation speed. > model size: 350M to 2.6B > built on LFM2, our v2 efficient model architecture > perform competitively with models up to hundreds of times larger > enable core agentic tasks: precise data extraction, multilingual translation, tool call, math, and RAG. 1/n

Today, we release LEAP, our new developer platform for building with on-device AI — and Apollo, a lightweight iOS application for vibe checking small language models directly on your phone. With LEAP and Apollo, AI isn’t tied to the cloud anymore. Run it locally when you want, for speed, privacy, and reliability, using LEAP’s end-to-end toolkit for on-device AI. 1/

Excited to share that Apollo has been acquired by Liquid AI. Expect more models, improvements, and powerful features you've never seen before with on-device models.

LFM2 are now available on Apollo. Thanks to the @liquidai team for driving forward months of app and user improvements, we are now a part of the Liquid AI ecosystem. With that comes stronger features, faster models, and a robust roadmap. More to come soon.

@levelsio @apolloaiapp by @localghost

@levelsio @apolloaiapp

@levelsio Apollo

@levelsio It’s Apollo and it’s not even close @localghost

I’ve been using Quasar Alpha on @openrouter on the @apolloaiapp So far I’ve been enjoying it. I would say as of right now it’s my new favorite model for doing web searches. Its outputs are very informative and has the information structured very well.

@ai_for_success My favorite way to use all the last models is through @openrouter and @apolloaiapp

TL;DR: we are excited to release a powerful new open-weight language model with reasoning in the coming months, and we want to talk to devs about how to make it maximally useful: openai.com/open-model-fee… we are excited to make this a very, very good model! __ we are planning to release our first open-weigh language model since GPT-2. we’ve been thinking about this for a long time but other priorities took precedence. now it feels important to do. before release, we will evaluate this model according out our preparedness framework, like we would for any other model. and we will do extra work given that we know this model will be modified post-release. we still have some decisions to make, so we are hosting developer events to gather feedback and later play with early prototypes. we’ll start in SF in a couple of weeks followed by sessions in europe and APAC. if you are interested in joining, please sign up at the link above. we’re excited to see what developers build and how large companies and governments use it where they prefer to run a model themselves.

Now that the @apolloaiapp has included shortcut outputs, it's making me think about workflows for offline and online AI. Give it a read and let me know what you think. I'd love to hear from you open.substack.com/pub/creatortra…