Build Anything with LFM 2.5! Here's how 🤯

LFM 2. 5 just dropped and it's insane. This AI runs on your phone. No cloud needed. It's fast, it's powerful, and it's totally free. I'm going to show you how to build with it right now. Hey, if we haven't met already, I'm the digital avatar of Julian Goldie, CEO of SEO agency Goldie Agency. Whilst he's helping clients get more leads and customers, I'm here to help you get the latest AI updates. Julian Goldie reads every comment, so make sure you comment below. Okay, so LFM 2. 5. This is huge and most people have no idea this even exists yet. So, let me break this down super simple. LFM 2. 5 is Liquid AI's newest model. It runs completely on your device, your laptop, your phone, even IoT devices. No internet required. No cloud costs, nothing. And here's why that matters. Most AI tools right now need the cloud. That means you're paying per request. You're sending data to someone else's servers and if the internet goes down, you're done. LFM 2. 5 changes all of that. It's a 1. 2 billion parameter model that fits on edge devices and it's fast. Like really fast. We're talking hundreds of tokens per second on a phone. That's wild. Now, let

me explain what makes this different. First, the architecture. LFM 2. 5 uses something called a hybrid stack. It combines convolutional blocks with grouped query attention. I know that sounds technical, but here's what it means. is designed to run fast on regular CPUs and mobile processors, not just expensive GPUs. Most AI models are built for cloud servers, big machines, lots of power. LFM 2. 5 is built for the device in your pocket. That's the game changer. Second thing, the training data. They scaled this thing from 10 trillion tokens to 28 trillion tokens. That's almost 3x more knowledge baked into the model. More reasoning, better instruction following, more capabilities overall. Third, they added reinforcement learning, a lot of it. This means the model is better at following instructions, better at using tools, better at multi-step tasks. It acts more like an agent now. It can plan, it can execute, it can adapt. And here's what most people miss. This isn't just a text model. LFM 2. 5 comes in multiple versions. There's text models, vision language models, audio language models, all in the same family, all optimized for edge devices. You can literally build a multimodal AI assistant that runs entirely on a phone. No servers, no API costs, just pure local AI. Now, let me show you what you can actually build with this because that's what matters. Real use cases, real applications, stuff you can deploy today. Use case one

offline AI assistance. Imagine you're building a business automation tool for the AI profit boardroom. You want members to have an AI assistant that helps them write content, analyze data, and manage tasks. But you don't want to pay cloud API fees for thousands of users. With LFM 2. 5, you build it once. Users download it. It runs locally. No recurring costs. Complete privacy. Their data never leaves their device. That's powerful for businesses that handle sensitive information. Use case two, mobile apps with AI features. Let's say you're building a lead generation app for the AI profit boardroom community. You want AI that can analyze landing pages, suggest improvements, and generate conversion focused copy. Normally, you'd need to call an API every time. With LFM 2. 5, the AI runs right in the app. Instant responses. No data sent to external servers. Users love that. Use case three. Edge data extraction. You've got documents, invoices, receipts, forms. You need to pull structured data out of them, turn them into JSON, feed them into your systems. LFM 2. 5 can do this locally. Process hundreds of documents without ever touching the cloud. This is huge for automation workflows, especially when you're dealing with customer data that needs to stay private. Use case 4, Agentic workflows. This is where it gets really interesting. LFM 2. 5 has expanded reinforcement learning. That means it can act like an agent. It can use tools, execute commands, make decisions. You could build a local automation agent that monitors your business metrics, generates reports, and even takes actions based on predefined rules, all running on your own hardware. No external dependencies. Now, here's the cool part. Because this model is open source, you can customize it, fine-tune it on your own data, optimize it for your specific use case. You're not locked into someone else's API or pricing model. And speaking of building things, if you want to learn how to save time and automate your business with AI tools like LFM 2. 5, you need to check out the AI profit boardroom. We teach you how to implement AI automation in practical ways. How to use these tools to streamline your workflows, how to build systems that actually work. No fluff, just actionable strategies. Link in the description. All right, back to LFM 2. 5. Let me talk about the technical

specs because if you're going to build with this, you need to know what you're working with. The context window, this thing handles 32,000 tokens. Some versions go up to 125,000 tokens. That's massive. You can feed it entire documents. Long conversations, multiple pages of data, and it'll process all of it. Vocabulary size, 65,000 tokens. That means multilingual support. You can work in different languages without switching models. speed. On an AMD CPU, you get about 239 tokens per second. On a mobile MPU, about 71 tokens per second. That's decode speed. That's the model generating text, and that's fast enough for real-time applications, memory efficiency. Because of the hybrid architecture, this model uses way less memory than traditional transformers. That means it fits on devices with limited RAM, phones, tablets, edge devices, model variants. There's LFM 2. 5, 1. 2b base. That's the foundation model. Then there's LFM 2. 5 1. 2B Instruct that's tuned for following instructions better for chat bots and assistants. There's also multimodal versions for vision and audio and specialized versions like the Japanese model. Now, let me walk you through how

to actually use this thing because theory is nice, but execution is what matters. Step one, download the model. You go to hugging face, search for LFM 2. 5. Liquid AI has the official model collections there. You pick the variant you want, base or instruct, text or multimodal. Download the weights. Step two, choose your inference framework. You've got options. You can use transformers. That's the standard library from hugging face. Easy to use, good for prototyping, or you can use llama. cpp that's optimized for speed. Step four, integrate into your application. Once you've got the model running, you wrap it in your app logic, build a UI, connect it to your data sources, add error handling, make it production ready, and here's where the magic happens. Because this runs locally, your latency is super low. No network calls, no API rate limits, just pure local compute. That means faster user experiences, more reliable applications, lower costs. Now, let's

talk benchmarks because everyone wants to know how this compares to other models. on instruction following tasks. LFM 2. 5 outperforms its predecessors by a significant margin. The expanded reinforcement learning really shows. It's better at understanding complex instructions. Better at multi-turn conversations, better at staying on task. On speed, it's about 2x faster than comparable models on the same hardware. That's the hybrid architecture paying off. Convolutional blocks are faster than pure attention for certain operations. Grouped query attention reduces the computational load on quality is competitive with models twice its size. That 28 trillion token training data set really helps. More knowledge, better reasoning, more accurate outputs. LFM 2. 5 is a big step

toward making it real. So here's what you should do. Go download LFM 2. 5. Try it out. Build something with it. See how it performs on your use case. Test the speed. Test the quality. See if it fits your needs. And if you want the full process, SOPs and 100 plus AI use cases like this one, join the AI success lab is our free AI community. Links in the comments and description. You'll get all the video notes from there, plus access to our community of 40,000 members who are crushing it with AI. And don't forget to check out the AI profit boardroom for premium training on AI automation. We go deep on implementation. We show you exactly how to use tools like LFM 2. 5 to automate your business, save time, scale operations, build real systems that work. That's it for today. LFM 2. 5 is here. It's powerful. It's free, and it's ready to use. Go build something amazing with it. And let me know in the comments what you create. I read every single one. See you in the next video.