Top 10 Open Source AI Models!

Today I'm going to show you the top 10 opensource AI models. These models are totally free. You can use them right now and some of them are actually better than Chat GPT. This is going to change how you think about AI forever. Let's get into it. So here's what's crazy about 2026. Open source AI models aren't just little experiments anymore. They're actually competing with and sometimes beating the big guys like GPT and Gemini. I'm talking about models with massive context windows. models that can think through problems like a human. Models that can look at images and write code from screenshots. This stuff is wild. Let me break down the top 10 for you. But first, you need to understand why this matters. These aren't toys. These are production ready models that real companies are using right now. Some have context windows of 200,000 to 256,000 tokens. That means they can read entire books and remember every detail. They can analyze huge research papers. They can help you with massive coding projects. This is the real deal. 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. Number one on the list is Kimmy

K2. 5 Thinking. This model is insane. It can do vision tasks, text tasks, and coding all at the same time. You can literally show it a video of a user interface and it will reconstruct the code for you. That's not sci-fi. That's happening right now. The reasoning ability on this thing rivals human level planning and it's open source. You can download the weights from hogging phase today. Companies are using this for document automation and building coding assistance. The multimodal capabilities mean it can see and understand images while also processing text and writing code. is like having three specialized AI models in one package and the thinking mode means it actually reasons through problems step by step instead of just guessing. This is the future of AI right here. Number two is GLM 4. 7. This model is a beast for coding and it has incredible multi-turn reasoning which means it can have actual conversations about code. It doesn't just spit out answers. It works with you. It has plugins and terminal integration, so it can chain tasks together automatically. Imagine telling an AI to build a feature and it actually does all the steps without you holding its hand. That's what GLM 4. 7 can do. Developers are using this to augment their workflow. It's not replacing developers. It's making them 10 times faster. You can find it on Open Router API or download the weights from Hugging Face. The real world coding performance on this thing beats a lot of alternatives and it's completely free. Number three is QME3

235B A22B instruct. This is a massive mixture of experts model. That means it has billions of parameters, but only uses a small portion for each task. So, it's fast and efficient while still being incredibly smart. It has dual mode thinking. You can switch between deep reasoning mode and quick chat mode depending on what you need. The multilingual support is incredible. The logic and math performance blow other models out of the water. And you can actually see the difference when you compare the reasoning outputs to the regular chat outputs. It's like watching two different brains work. One is careful and methodical. The other is quick and conversational. Both are useful for different tasks. Number four is DeepSeek V3. 2. This model uses something called sparse attention. Instead of looking at every single token, it smartly picks which ones matter. That makes it incredibly fast. And they used reinforcement learning to boost its performance even more. on reasoning benchmarks. This thing competes with GPT level models. We're talking about complex problem solving, math, logic, all of it. The algorithmic breakthroughs in this model are what make it special. It's not just bigger, it's smarter about how it processes information, and that means you get better results with less compute power. For anyone running AI locally, that's a game changer. Number five is Mistral

Large 3. This is Mistral AI's new flagship model. It's multimodal, has a 256,000 token context window, and it's licensed under Apache 2. 0. That means you can use it commercially without restrictions. It handles text and images really well. You can show it a picture and ask complex questions about it. You can feed it long documents and have it analyze them. This is a great general purpose model. If you're not sure which model to start with, Mistra large 3 is a solid choice. You can run it through Olmer on your local machine. It's fast, it's capable, and is versatile enough to handle most tasks you throw at it. Now, here's where things get really interesting. If you want to learn how to actually use these models to scale your business, get more customers, and save hundreds of hours with AI automation, you need to check out the AI profit boardroom. This is where we show you exactly how to implement open-source AI models like these into your workflows. We've got members who are automating their entire content creation pipelines. Trust me, if you're serious about leveraging AI, this is where you need to be. Number six is

LongCat Flash Chat. This model is optimized for long context conversations. The benchmark scores put it right up there with the top models like Miniax and GLM. It's especially good at maintaining context over really long chats. If you're building chat bots or AI assistants that need to remember details from earlier in the conversation, this is your model. Number seven is Mimo V2 Flash. This is Shyomi's efficient mixture of experts model. It has hybrid attention and a huge context window. But here's the kicker. It's incredibly cheap to run. The efficiency on this thing is off the charts. For coding and reasoning tasks, it punches way above its weight. This is perfect if you're you can get professional-grade results with hardware you probably already have. Number eight is Miniax M2. 1 Preview. This is an Aentic model. That means it's designed to use tools and interact with other systems. It can plan multi-step workflows, execute them, and adjust based on results. The long reasoning capabilities make it great for complex tasks that require thinking ahead. Imagine setting up automated workflows where the AI actually makes decisions about which tools to use and when. That's what agentic models like this enable. It's not just responding to prompts. It's actively working toward goals. Number nine is Gemma 3 27B it.

This is Google's open multimodal model. It balances creativity with utility really well. It can handle text and image tasks. The emotional understanding on this model is surprisingly good. If you're building AI that needs to understand nuance and context in human communication, Gemma is worth looking at. Google decided to release this as open- source, which is huge. You're getting research grade AI from one of the biggest tech companies in the world, and you can use it however you want. Number 10 is Intellect 3. This is a 106 billion parameter mixture of experts model. What makes it special is the full open training pipeline. They released everything, the code, the data, the reinforcement learning stack, all of it. For math encoding performance per parameter, this model is incredibly efficient. It's smaller than some of the other models on this list, but it's smarter about how it uses its parameters. This proves that you don't always need the biggest model. Sometimes the smaller well-trained model can beat the massive one. And for developers who want to understand how these models are built, having the full training pipeline is invaluable. Here's how you can start

using them. Most of these models are on hugging face. You can download the weights and run them locally if you have the hardware. If not, platforms like Open Router and Alama let you access them through APIs. Some are free. Looking ahead, we're going to see more of this. Mini models that run on your phone. Huge mixture of experts models for enterprise use. Everything in between. The barrier to entry for AI is dropping to zero. And that means anyone with an idea and some technical skills can build something amazing. And one more thing, if you want to learn how to actually use these models to scale your business, get more customers, and save hundreds of hours with AI automation, you need to check out the AI profit boardroom. This is where we show you exactly how to implement open-source AI models like these into your workflows. We've got members who are automating their entire content creation pipelines. Trust me, if you're serious about leveraging AI, this is where you need to be. And if you want the full process, SOPs, and 100 plus AI use cases like these open-source models, join the AI success lab. Links in the comments and description. You'll get all the video notes from there, plus access to our community of 38,000 members who are crushing it with AI. All right, thanks for watching. Hit the like and subscribe button and I will see you in the next