NEW DeepSeek-R1T2-Chimera is INSANE (FREE!) 🤯

Today I'm going to show you an AI model that just broke the internet. It's called Deepseek TNG R1T2 Chimera and it's 200% faster than the best models out there. This thing combines three AI brains into one superb brain. And here's the crazy part. It's completely free and open source. This could change everything about how we use AI. But there's a catch that most people don't know about. 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. So, here's what happened. 3 days ago, a German company called TNG Technology Consulting just dropped something massive. They took three of the smartest AI models ever made and somehow combined them into one super model, and the results are insane. This new model is called Deep Seek TNG R1T2 Chimera. I know that's a mouthful, but stick with me, cuz what this thing can do will blow your mind. First, let me tell you why this matters. You know how most AI models are either really smart but super slow, or really fast, but not that smart? Well, this model just solved that problem. It's as smart as the best models, but runs twice as fast. That means half the cost and half the wait time. But here's where it gets crazy. They didn't train this model from scratch. That would take millions of dollars and months of work. Instead, they use something called assembly of experts. Think of it like taking the brain of Einstein, the speed of a race car driver, and the efficiency of a computer, and somehow combining them into one superb brain. The three parent models he used are Deepseek R1, Deep Seek R10528, and Deepseek V3 0324. Each one is amazing on its own, but together game changer. Deepseek R1 is the thinking model. It can reason through complex problems like a genius, but it talks too much. Like that smart friend who gives you a 20inute answer to a simple question. Deepseek R10528 is the upgraded version. Even smarter, but even more wordy. Great at math and coding, but it will write you a novel when you just want a simple answer. Deep Seek V324 is the fast one. Quick responses to the point, but not as deep with the thinking. So, what did TNG do? They took the brain power from the first two and the speed from the third. The result is a model that thinks like a genius but talks like a normal person. And the numbers prove it. In benchmark tests, this model scores 90 to 92% as well as the smartest parent model. But here's the kicker. It uses only 40% of the words to give you the same quality answer. That's a 60% reduction in output length. What does that mean for you? Faster responses, lower costs, better efficiency. If you're running a business and using AI for customer service, content creation, or data analysis, this could save you thousands of dollars per month. Let me give you some real examples. Remember AI me? That's a super hard math competition that even smart humans struggle with. Deep Seek R1T2 Chimera crushes it. GPQA Diamond, that's a test that requires PhD level knowledge. This model nails it. But here's what makes this even more special. This isn't some lockedway proprietary model that costs $100 per thousand tokens. This is completely open source with an MIT license. That means you can download it, modify it, use it commercially, whatever you want. And people are already going crazy for it. Within days of release, developers created over 500 different versions of this model. It's being processed on platforms like Open Routter and Shoots at a rate of 5 billion tokens per day. That's massive adoption. The Reddit community is losing their minds over this. One user said, "It's the first time a Chimera model feels like a real upgrade in both speed and quality. " Another said, "It performs way better in math context compared to previous models. People are saying it feels more grounded and avoids making stuff up compared to other models. " But here's something most people don't understand about how this was built. The Assembly of Experts method isn't just combining models. It's like performing brain surgery on three different AI systems and carefully transplanting the best parts into one new brain. They took the routed expert tenses from Deepseek R1. These are the parts that handle specialized reasoning. Think of them as the neurons that fire when the AI is solving complex problems. Then they combine them with the shared experts from Deepseek V324. These handle the basic language understanding and efficiency. But wait, there's more. They also added improvements from Deepseek R10528. This created what they call a try mind configuration. Three brains working as one. The technical term for this is mixture of experts architecture, but the assembly of experts approach is completely different. Most mixture of experts models activate different parts during runtime. This one actually merges the parts into one unified model. And here's something wild. The team at TNG said they expected to find defects when they built this hybrid model, but they found none. Zero. The model actually thinks more clearly and gives more organized responses than its parent models. This fixes something called the think token consistency issue. The

previous Chimera models had problems with their reasoning chains. Sometimes they would start thinking about a problem and then get distracted or confused. R1T2 solved this completely. Now let's talk about real world performance. This model is 20% faster than the original Deep Seek R1 and more than twice as fast as R1 528. But it's not just about speed, it's about intelligence, too. On the GPQA benchmark, which tests general knowledge at PhD level, this model scores significantly higher than the original R1. On army 2024 and 2025, the super hard math competitions, it crushes the competition and the hugging face community is going wild. Vibbavs Free Vastav, a senior leader at HuggingFace, tweeted, "Damn, Deepseek R1T200% faster than R10528 and 20% faster than R1. Significantly better than R1 on GPQA and AI 24 made via Assembly of Experts with DSV3, R1, and R10528. And it's MIT licensed, available on HuggingFace. But here's what really matters for your business. This model can handle complex reasoning tasks while keeping costs low. If you're doing customer support, content creation, data analysis, code generation, or any other AI heavy work, this could dramatically reduce your costs. Think about it. If you're paying for API calls to GPT4 or Claude, and this model gives you similar quality at a fraction of the cost, that's money back in your pocket. And since it's open source, you can even run it on your own servers if you have the hardware. Speaking of hardware, this is a 6 and21 billion parameter model. That's massive. You'll need serious computing power to run it. But TNG also offers access through their cluster and it's available on platforms like Open Router where you can access it through APIs. Now, there are some limitations you need to know about. This model doesn't support function calling or tool use yet. That's because it inherited some limitations from its DeepS R1 parent, but the team says they might fix this in future updates. Also, if you're in Europe, pay attention. The EU AI Act takes effect on August 2nd, 2025. TNG recommends that European users either make sure they comply with the requirements or stop using the model after August 1st. But if you're in the US or other countries, you're good to go. Here's something interesting about the team behind this. TNG Technology Consulting is a 24-year-old German company founded in 2001. They work with telecommunications, insurance, e-commerce, automotive, logistics, and finance companies. They're not some random startup. They know what they're doing, and they're not trying to compete with the biggest proprietary models. Their focus is on efficiency and cost reduction. They want to give businesses a powerful AI tool that doesn't break the budget. The response from the AI community has been incredible. The model was trending as the number two model on open router with over 1 billion processed tokens. Developers are already building applications with it. The Reddit local llama community is praising its responsiveness and balance between speed and quality. One user said it exhibits a more grounded persona and avoids hallucinations better than R1 or V3based models. That's huge for production environments where reliability matters. Here's what this means for the future of AI. We're seeing a shift towards model merging as a viable alternative to training from scratch. Instead of spending millions of dollars and months of time training new models, teams can combine existing models to create something better. This democratizes AI development. Smaller companies and research teams can now create powerful models without massive budgets. And since this model is open source, anyone can build on top of it. But here's the real kicker. This assembly of experts method works at massive scale. We're talking about a 6 in1 billion parameter model here that proves this technique can work for the biggest most complex AI systems. TNG published their research paper on AR chief detailing exactly how they built this. They're being completely transparent about their methods. This means other teams can replicate and improve on their work and they encourage community experimentation. They want people to fine-tune this model, use it for reinforcement learning and build new applications with it. This is open science at its best. Now let's talk about practical applications. If you're running a business, here are some ways you could use this model right now. Customer support chatbots that can handle complex questions without giving you essay length responses, content generation for blogs, social media, and marketing materials that's both highquality and cost-effective. Code generation and debugging for development teams, data analysis and report generation for business intelligence, internal knowledge based queries where both speed and accuracy matter. The cost savings could be massive. If you're currently spending thousands per month on AI API calls, this could cut that cost dramatically while maintaining or improving quality. But here's what really excites me about this. This isn't just about one model. This is about a new approach to building AI systems. The assembly of experts method could be applied to other models and use cases. Imagine combining the best coding model with the best writing reasoning model or taking the best image generation model and combining it

with the best text model for multimodal applications. The possibilities are endless. And since the method is open source, we're going to see rapid innovation and experimentation from the community. But there's one more thing that makes this really special. The team at TNG isn't done. They've already released multiple Chimera models and R1T2 is just the latest. They're continuously improving and experimenting with new combinations. And remember, this is just the beginning. The parent models themselves keep getting better. Deep See just released R1 off 28 with significant improvements. As the parent models improve, future Chimera models will be even better. This is exactly the kind of innovation that gets me excited about AI. We're not just seeing incremental improvements. We're seeing fundamental breakthroughs in how AI systems are built and deployed. The fact that this is completely open source makes it even better. This isn't locked away in some corporate lab. Anyone can download it, experiment with it, and build on it. That's how we get rapid innovation and real progress. So, what should you do with this information? First, if you're running a business that uses AI, start testing this model. See how it performs for your specific use cases. The cost savings alone could be worth it. Second, if you're a developer or researcher, dive into the technical details. Read the paper, understand the assembly of experts method, and think about how you could apply it to your own projects. Third, keep an eye on this space. The pace of innovation in open- source AI is accelerating. Models like this are going to keep getting better, faster, and cheaper. And finally, start thinking about how you can take advantage of these tools in your business or career. The companies and individuals who adopt these technologies early are going to have a massive advantage. This is just the beginning. We're entering a new era of AI where the best tools are open, accessible, and constantly improving. The question isn't whether AI will transform your industry. The question is whether you'll be ready when it does. If you want to stay ahead of the curve and scale your business with AI automation, you need to check out my AI profit boardroom. It's the best place to learn how to use AI to get more customers and save hundreds of hours with automation. The strategies I share there could save you thousands of dollars per month and give you a massive competitive advantage. Also, if you want a free SEO strategy session to see how we can help you get more leads and customers, the link is in the comments and description below. My team has helped hundreds of businesses grow with SEO and AI, and we'd love to help you, too. And if you want access to the exact SOPs and processes we use, plus over a 100 AI use cases, check out the AI success lab. The link is in the comments and description. You'll get step-by-step tutorials, proven strategies, and access to a community of 14,000 members who are already using AI to grow their businesses. Don't miss out on being part of something bigger than yourself.