MiniMax-M1: This NEW Chinese AI Agent is INSANE…

Today I'm going to show you a brand new AI from China that's making everyone lose their minds. It's called Miniax M1 and it's completely free. This thing can build entire Netflix clones in 60 seconds with zero coding and it only costs $534,000 to train. That's 200 times cheaper than GPT4. 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. On June 16th, 2025

Miniax dropped M1 and the AI world exploded. This thing handles 1 million tokens of input. That's 10 novels at once. Chat GPT only 128,000 tokens, one novel. But here's the kicker. They trained it for $534,700. Open AI spent over $100 million on GPT4. Same performance, 200x cheaper. Minimax invented lightning attention. It uses only 25% of the computing power other models need. When Deep Seek R1 processes 100,000 tokens is like running four supercomputers. MiniaX M1, one computer on eco mode and it's completely open source. Apache 2. 0 0 license. Download it, modify it, use it commercially. Free

ARM 2024 math competition M1 scored 86%. Beat open AI Claude and Gemini Software Engineering SWE 56% better than most human programmers. Agent Tasks TU Bench 62. 8%. Beats Deep Seek and Matches Claude Long Context OpenAI MRCR 73. 4%. It actually remembers everything you feed it. Real world examples. Mchoy

built a Netflix clone in 60 seconds. Working trailers, responsive design, everything. Zero coding. Another guy created an animated maze game. Just ask for it. Done. People are building full applications faster than ever before. 456 billion parameters total, but only 45. 9 billion active at once. It's like having 32 specialists, but only waking up the ones you need. They used 512H800 GPUs for three weeks. Not even the best GPUs. These are the ones America won't sell to China. Their Cisco training algorithm is the secret source. Instead of brute force learning, it teaches the AI to think better. The mixture of experts architecture means each expert handles what they're best at. Math expert for math, code expert for coding, no wasted compute. Most AIs forget what

you told them after a few paragraphs, like talking to someone with amnesia. Minax M1's million token window means you can feed it your entire company knowledge base. All your SOPs, documentation, customer history. It remembers everything for businesses. This is huge. No more copypasting context. No more, as I mentioned earlier, reminders. Just pure productivity. This isn't just a chatbot. The agent mode can write and deploy code, build complete web apps, create presentations, manage workflows across tools, debug and fix its own mistakes. One command, full execution, no handholding. The tests I ran, I was skeptical, so I tested it with brutal challenges. Test one

business analysis, fedit 500 pages of merger documents, financials, pitch decks, market research, legal issues. asked if Tech Corp should buy Dataflow, Inc. The documents showed Tech Corp. had $50 million revenue, but declining margins. Dataf Flow had great tech, but 35% customer churn, and pending lawsuits. It analyzed everything perfectly, caught the declining margins, high churn, patent problems. Then it calculated the financial impact, assessed integration risks, and recommended a specific earnout structure to protect TechC Corp. Even suggested which data flow engineers to retain.

Test two, engineering math. Gave it a PhD level problem. Design a soccer ball-shaped pressure chamber with material limits and $50,000 budget. This required calculating pentagonal and hexagonal face dimensions. Handling 2. 5 atmosphere internal pressure using materials that cost $12 per kilogram with specific stress limits. It solved everything. Showed the geometric derivations. Calculated minimum wall thickness for safety. Optimized material usage to stay under budget. Even included safety factors I hadn't asked for. The math was perfect. Test three

fixed broken code showed it garbage Python trading code that crashes above 10,000 trades per second. The code used lists for order storage. O searches recalculated entire portfolios on every trade. Zero concurrency. It completely redesigned the architecture. switched to hashmaps and priority cues, 01 lookups, implemented lock free concurrent processing, added memory pooling, created separate threads for order matching and risk calculation, even added circuit breakers for market volatility, professional level optimization that would handle 100,000 plus trades per second. Test four

investment research asked for a full renewable energy storage investment report. Market analysis, financials, patents, regulations, supply chain risks. It analyzed battery storage, pumped hydro, and emerging tech markets, found the top five companies, compared their three-year financials, identified 47 key patents, mapped regulations across the US, EU, and China, and flagged lithium supply risks. The kicker, it created a competitive matrix scoring each technology on cost, efficiency, and scalability. Then gave specific buyell recommendations with price targets, investment bank quality work. Test five, environmental data.

Five years of satellite images, sensor data from 20 stations, species counts, water quality, weather data, all messy with gaps. The data included hourly temperature/ salinity readings, 2 years worth, monthly chemical analysis, and inconsistent species surveys. Some sensors had failed for months. It found correlations between storms and ecosystem damage. Identified a 2. 3° C temperature threshold that triggered species migration. Detected phosphorus spikes preceding algae blooms. Even calculated which sensor failures had the biggest data impact and recommended three specific locations for new sensors based on coverage gaps. Every test pushed different limits. Context length, reasoning depth, code generation, data synthesis. It nailed them all. what this really means. Chinese companies keep releasing models that match or beat Western ones for pennies on the dollar. Deep Seek in January, butterfly effect in March, now Miniax. While Open AI burns billions and charges $20 a month, China gives away better tech for free. The mixture of experts architecture with lightning attention is a gamecher. 75% less compute for same results. If you're paying thousands monthly for AI tools, why? You could run this on your own servers for free. Real business applications customer service. Feed it your entire help documentation. It'll handle complex support tickets better than tier 2 agents. Content creation, not just blog posts, full marketing campaigns, email sequences, social media strategies with your brand voice builtin, code development. From fixing bugs to building features, it understands entire code bases, not just snippets. Data analysis. Throw spreadsheets, reports, databases at it. Get insights that would take analysts weeks. Process automation. Connect it to your tools via API. Automate workflows that normally need multiple employees. The function calling means it can actually do things, not just talk about them. Start small. Download the model.

Test it on one specific task. If you're technical, use VLM. Set up proper infrastructure. Integrate with your stack. If you're not, services are popping up to host it. Some free, some cheap. Way cheaper than OpenAI. The 40K version is fine for most tasks. Use 80,000 for complex analysis or massive documents. Temperature 1. 0. Top P 0. 95 works best. Don't overthink the settings. How to use it? Go to HuggingFace or GitHub. Search Miniax M1. Two versions. M1 140K and M1 180K. The 80K is better for complex tasks. Run it with VLLM for best performance or use transformers for simplicity. It supports function calling, web search, tool integration, connect it to anything. This isn't just another AI model. It's proof the entire AI cost structure is collapsing. If they can build this for half a million, what's coming next? The barriers are gone. The capabilities are here. And it's free. Julian Goldie reads every comment, so make sure you comment below. Want to scale your business with AI? Check out my AI profit boardroom. We've got 1,000 members already crushing it. Link in comments and description. Need help with SEO? Book a free SEO strategy session with Goldie Agency. Link below. Get our complete SOPs and 100 plus AI use cases in the AI success lab. 14,000 members are already implementing. Links below. The AI revolution is here. Models like Minax M1 prove everything we thought about AI costs is wrong. You're either using AI or getting replaced by it. The choice is yours. See you in the next one.