This NEW CHINESE AI AGENT is INSANE! 🤯

A brand new Chinese AI coding agent just dropped and it's beating GPT and Claude on real coding benchmarks. This thing is open source, runs locally, and it's only 40 billion parameters. Wait till you see what it can actually do. This is going to change how we build AI automation systems. Let's dive in. 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, let's talk about

something absolutely wild that just came out of China. It's called iquest Coda V140B Loop Instruct. I know the name is a mouthful, but here's what you need to know. This is a 40 billion parameter AI model built specifically for coding, and it's crushing benchmarks that even GBT and Claude struggle with. We're talking 81. 4% on S. Bench verified. That's the gold standard for testing how well AI can fix real GitHub issues. Claude Sono 4. 5 and GPT are getting beat by a model that's 10 times smaller. Let me say that again. 10 times smaller. And it's completely open source. You can download it right now from HuggingFace. Run it on your own hardware. No API costs, no rate limits. This is huge for anyone building AI automation systems. So, let me break

down what makes this thing so special. First, the architecture. This model uses something called a looped recurrent transformer design. Sounds complicated, but here's what it means. Instead of processing everything in one massive pass, it loops through the information multiple times. It shares parameters across iterations. This makes it way more efficient, lower inference costs, faster deployment, and it still delivers top tier performance. Plus, it has a native 128k token context window. That means you can feed it an entire codebase, not just a single file, not just a few functions, the whole repository. and it understands how everything connects. This is perfect for building complex automation workflows like the ones we use to automate client outreach, content generation, and data processing. Now, here's where it gets

even better. The training method. Most AI models are trained on static snapshots of code. They see a bunch of GitHub repos frozen in time. But IQest Coder does something different. It's trained on Codeflow multi-stage training. That means it learns from commit histories. It sees how code evolves over time, how developers refactor, how bugs get fixed, how features get added. This gives it a much deeper understanding of real world coding. It's not just memorizing syntax. It's learning the logic behind why code changes and that's why it performs so well on practical tasks. Okay, let's

talk benchmarks for a second because this is where things get really interesting. SBench verified 81. 4%. This benchmark tests whether an AI can actually fix real GitHub issues, not toy problems, real bugs from real repositories. IQ Quest Coder scored 81. 4%. That's higher than most models that are way bigger and way more expensive. Big Code Bench 49. 9%. This one tests complex coding tasks across multiple languages. Live Code Bench V6 81. 1%. This is a newer benchmark that focuses on recent coding challenges. Again, top tier performance. And remember this is a 40 billion parameter model. Claude and GPT are in the hundreds of billions. So you're getting comparable or better results with a fraction of the size. Now before we go further, let me show you how this ties into what we're building. At the AI profit boardroom, we use AI coding agents like this to automate everything. Client onboarding systems, lead generation workflows, content creation pipelines. And with tools like iquest coder, you can build these systems yourself. No expensive API calls, no vendor lockin, just pure automation that saves you hours every single day. If you want to learn how to do this, check out the AI profit boardroom. Links are in the description and comments. Right, back to the model. Let me show you how you actually use this thing. It's surprisingly simple. You can run it with the transformers library from hugging face. Now, let's

talk about the variants because iquest coder isn't just one model. It's a whole family. You've got the instru variants. These are tuned for general coding assistance, following instructions, generating clean, readable code. Then you've got the thinking variants. These are reasoning driven models. They break down complex problems step by step, perfect for debugging or system design. And then there are the loop variants. These use the recurrent design I mentioned earlier. Lower footprint, more efficient, same great performance. You can pick whichever one fits your use case. And they're all open source, all available on HuggingFace. Now, let's

talk about deployment because this is where things get really practical. You can run iquest coder on your own hardware. If you've got a beefy GPU, you can run the full 40b model, but if you don't, there are community quantized versions, 4-bit quantized models. These run on consumer hardware. You can even run them on a MacBook with MLX. No cloud costs, no API limits, just pure local inference. This is a gamecher for anyone who wants full control over their AI stack. And for businesses that deal with sensitive data, you're not sending your code to some third-party API. You're running it inhouse. Total privacy, total control. Now, let me be real about the limitations because nothing is perfect. First, iquest coder generates code. It doesn't execute it. That means you need to validate the outputs yourself. Run the code in a sandbox. Test it thoroughly. Don't just copy paste and hope for the best. Second, performance can vary. If you're working with exotic programming languages or proprietary frameworks, it might not perform as well. It's been trained on popular languages and open source repos. So stick to Python, JavaScript, Go Rust, and you'll get the best results. Third, hardware requirements. Running a 40B model isn't trivial. You need good infrastructure. But again, the quantized versions help a lot. Right, let's talk

about what this means for developers, especially if you're building AI automation systems. This model opens up so many possibilities. You can use it to generate custom automation scripts, build APIs on the fly, create data processing pipelines, write unit tests, refactor legacy code, and because it's open source, you can fine-tune it, train it on your own codebase, make it even better for your specific use case. This is the future of development. AI agents that understand code at a deep level that can reason through complex problems that work alongside you as a coding partner. And the best part, you don't need to wait for some big tech company to give you access. You can start using it today. The community is already buzzing about this. People on Reddit and Hugging Face are testing it, sharing results, building integrations. Some are hooking it up to agent frameworks, combining it with other tools, creating entire AI coding workflows. This is exactly the kind of innovation we need. Open models that anyone can use that push the boundaries of what's possible and that make AI accessible to everyone. So, here's what you should do next. Go to hugging face. Search for Aquestoder V140B looper instruct. Download the model. Try it out. See what it can do. Start small. Generate a simple script. Then try something more complex. Build a REST API. Create a data pipeline. Automate a workflow. And then think about how you can use this in your business. What tasks are you doing manually that could be automated? What code are you writing over and over again? Where could an AI coding agent save you hours of work? because that's the real power here. It's not just about having a cool AI model. It's about using it to solve real problems, to build better systems, to save time, to scale your operations. So, if you want to learn how to build AI automation systems like this, join the AI profit boardroom. We'll show you how to use AI coding agents to automate client onboarding, lead generation, content creation, and more. Everything you need to know to save time and scale with AI. Links are in the description and comments. And if you want the full process, SOPs, and 100 BL AI use cases like this one, join the AI success lab. It's our free AI community. You'll get all the video notes from there, plus access to our community of 40,000 members who are crushing it with AI. Links in the comments and description. All right, that's it for this one. IQest Coder V140B Loop Instruct, a 40 billion parameter Chinese AI coding agent that's beating the biggest models in the world. open source, free to use, ready to deploy. Go check it out, try it, build something cool, and let me know in the comments what you think. Julian reads every single one.