This New CHINESE AI Agent is Insane! (FREE!) 🤯

Two open-source AI coding agents just shocked everyone. They beat GPT4 on real tasks. They cost almost nothing to run and nobody's talking about them yet. This changes everything for AI automation. Let me show you why. 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. All right, listen up. Something massive just happened in the AI world and almost nobody noticed. Two new AI coding agents from a company called Quai just entered the top 10 globally. Not top 10 open- source models, top 10 of all models. That includes GPT4, Claude, Gemini, everything. And here's the crazy part. They're completely open source. You can run them yourself. You can customize them. You can deploy them however you want. This is huge for anyone building AI automation systems. And I'm going to show you exactly why these matter and how you can use them right now. Let me break this down super

simple. Quai released two models that work together. Think of them like a team. One is the engine, one is the driver, and together they build better code than most paid AI tools. The first one is called Quiccoder 23BA V1. This is the engine. It's a 23 billion parameter model built specifically for code. But here's what makes it special. It uses something called mixture of experts architecture. What does that mean? Instead of using all 23 billion parameters every single time, it only activates about 4 billion per task. That makes it incredibly fast and cheap to run. We're talking about 130 of the cost of traditional models with the same power. This is not some toy model. This is production AI that developers are actually using in real products right now. The second model is called Catcoder

Pro V1. This is the driver. This is the one that does the actual reasoning, planning, and multi-step coding tasks. It's built on top of Quiccoder using something called SRPO training. That stands for scalable reinforcement preference optimization. Basically, they trained it on thousands of real world coding tasks, not just benchmarks, real developer workflows, bug fixes, refactoring, building full applications from scratch. And the results speak for themselves. Catcoder Pro became one of the top five most used programming models on Open Router. almost immediately after launch. Open router is where developers go to test and compare AI models. So, this tells you that real engineers are choosing this over GPT4 and Claude for actual work. But wait, it gets better. In late 2025, Quai pushed a

massive update, and this is where things get really interesting. The updated version of Cat Coder Pro scored 64 on the artificial analysis intelligence index. That put it at number 10 globally among all AI models in the world. Not just coding models, all models. Let me put that in perspective. This open- source model is competing directly with closed source giants that cost millions of dollars to develop and it's winning. So what changed in this update? Five major things. First, boosted benchmark performance. It got way better at code generation, bug fixing, and multifile reasoning. These are the tasks that actually matter when you're building real applications. Second, strengthened reasoning. The model can now plan longer sequences of actions without losing track of what it's doing. This is critical for complex automation tasks. Third, enhanced front-end capabilities. This is huge for anyone building web apps or automation dashboards. It now generates cleaner React View and Next. js code, better CSS layouts, better component structure. Fourth, elevated tool use precision. When the model calls functions or APIs, it's way more accurate now. Fewer mistakes, fewer hallucinations, more reliable automation. Fifth, reduced hallucination overall. It stopped inventing fake APIs and fake imports. This was a big problem with earlier coding models. Not anymore.

Now, here's why this matters for you specifically. If you're building AI automation for your business, you need reliable coding agents. You need tools that can actually build interfaces, connect APIs, and create workflows without constant supervision. Up until now, your options were either expensive closed source models like GPT4 or open- source models that weren't quite good enough for production use. These two models change that equation completely. Let me give you a real example. Let's say you want to build a custom dashboard for the AI profit boardroom. Something that shows member analytics, tracks engagement, and displays AI automation results in real time. You could prompt cat coder pro like this. Build a responsive Nex. js dashboard for the AI profit boardroom. Include authentication, API routes for member data, and a clean modern UI that showcases the value of AI automation to potential members. And here's what happens. The model doesn't just spit out a template. It actually thinks through the architecture. It plans the component structure. It writes clean production ready code for the authentication system. It creates proper API routes. It builds a responsive front end that actually works. No fake imports, no invented libraries, no broken logic. This is the kind of output you'd expect from a senior developer, not a junior AI that hallucinates half the time. And because it's open source, you can run it locally. You can fine-tune it on your specific use cases. You can integrate it directly into your automation workflows without sending everything through an external API. Here's something else that's incredible about this. If you want to learn how to actually implement AI automation systems like this, how to build custom dashboards, how to connect these models to your business workflows, the AI profit boardroom has full SOPs and templates for exactly this kind of work. You can automate client onboarding, build custom reporting tools, create AI powered lead generation systems, all using models like Qucoder and Kayat Coder Pro. We'll drop the link in the comments and description so you

can check it out. Now, let's talk about how these two models actually work together because this is important to understand. Qucoder 23BA 4V1 is the fast, cheap, scalable layer. It handles code completion, syntax generation, and structured output. Think of it like the muscle. CAT Coder Pro V1 is the reasoning, planning, and tool use layer. It handles multi-step execution, decision-making, and complex logic. Think of it like the brain. This two-layer approach is exactly how the best AI systems are built. Claude Code works this way. GPT4 Turbo with tools works this way. Gemini agents work this way, but those are all closed source and expensive. Quite just open source the entire stack. That's a massive deal because these models are open source. You're not locked into any platform. You're not paying per token. You're not waiting in API cues. You have complete control. This is what production grade open AI actually looks like. Now, let's talk about where these models beat GPT4 and Claude. First, cost. Running your own open-source model is dramatically cheaper than paying for API calls, especially at scale. If you're building serious automation, this adds up fast. Second, openness. You can inspect the model. You can fine-tune it. You can modify the architecture if you need to. Try doing that with GPT4. Third, control. You're not subject to rate limits, policy changes, or sudden price increases. You own the infrastructure. Fourth, deployment flexibility. You can run these models on your own servers, in private clouds, or even on local machines. Perfect for sensitive business data. For anyone serious about AI automation, these advantages matter a lot. Now, here's my take on where this

is heading in 2026. Open source coding agents are winning. The gap between closed and open models is shrinking fast. What used to take a $100 million training budget can now be done for a fraction of that cost using smart architecture and better training methods. Qui proved this. They built a top 10 global model using mixture of experts and SRPO training. Other companies are going to follow this playbook. If you want the full process, SOPs, and over a 100 AI use cases like this one, join the AI profit boardroom. Links in the comments and description, you'll get all the video notes from there, plus access to our community of entrepreneurs who are implementing AI automation in their businesses right now. And if you want even more resources, join the AI Success Lab. It's our free AI community with over 40,000 members. You'll get access to templates, workflows, and a massive community of people solving real problems with AI every single day. These two models from Quiet are just the beginning. Open- source AI is accelerating faster than anyone expected, and if you're not paying attention, you're going to get left behind. That's it for today. Drop a comment and let me know what you think about these new models.