New DeepSeek V4 Update is INSANE! 🤯

Key Takeaways

DeepSeek just dropped something that changes everything. We're talking 1.6 trillion parameters, 1 million token context window, open source, and pricing so low it breaks the market. OpenAI didn't do this. Anthropic didn't do this. Chinese AI lab just did it. And now every developer, every creator, every business owner has access to one of the most powerful AI models ever built for almost nothing. This isn't just a model update. This is a shift. If you're using AI to run your business, to build products, to automate your workflows, this affects you directly. Cuz the rules just changed. DeepSeek just released V4, and it's not a small step forward. It's a massive leap. Two models dropped at once, V4 Pro and V4 Flash. Four Pro is the heavy hitter. 0.6 trillion total parameters, around 49 billion active at any given time thanks to a mixture of experts architecture. This is the model you use when you need serious depth on documents, complex reasoning, multi-step logic across huge amounts of data. 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 drop one below. It genuinely helps. Four Flash is the speed runner. 44 billion total parameters, around 13 billion active. Built for fast, cheap, high-volume tasks. If you're automating workflows at scale, Flash is your go-to. It's lean, quick, and stupidly affordable. Both models are available right now. You can access them at chat.deepseek.com through the API or grab the open weights directly on Hugging Face. This is the part that stops people in their tracks. Million tokens of context. That's not a marketing number. That's a genuine capability shift. Some models cap out at 128K tokens. Some go to 200K. 1 million is a different category entirely. What does 1 million tokens actually mean in practice? Means you can load an entire book and interrogate it. You can feed in a full code base and debug across every file at once. You can take months of business data, support tickets, call notes, CRM records, email threads, and analyze all of it in a single prompt without chunking, without summarizing first, without breaking it into pieces and stitching results back together. That last part is huge. Chunking data is one of the biggest friction points in AI automation right now. It's slow, it breaks things, and it adds layers of complexity that eat up time. With the 1 million context window, that problem mostly disappears. Here's the number that made everyone stop scrolling. Four Flash costs approximately $0.028 per million tokens on cash hits. That is almost nothing. It is cheaper than almost anything else on the market right now. And V4 Pro is still dramatically cheaper than comparable closed models. To put that in context, running a full automated content pipeline, an onboarding system, a business intelligence workflow, all of that becomes affordable at a scale that simply wasn't viable before. This doesn't just make DeepSeek a better option. Changes the math on what's worth building with AI in the first place. Real quick, because this is exactly what we teach. If you want to know how to use AI tools like DeepSeek V4 to build real automated systems inside your business, the workflows, the frameworks, the actual step-by-step process, come join the AI Profit Boardroom. It's where serious people learn serious AI automation. No theory, no hype. Real systems you can plug in and run. Link is in the description, check it out. Back to DeepSeek, because the use cases are where this gets wild. Let me show you what this actually looks like when you sit down and use it. Three use cases, each one with a real prompt and what comes back. Use case one, content strategy for creators. Here's the problem. If you run a YouTube channel or a content business, figuring out what to make next is always a grind. You look at analytics, guess what worked, try to spot patterns manually. Takes hours and you're still guessing. With DeepSeek V4's 1 million context window, you load in every video transcript you've ever published. Every single one. Then you run this prompt. Here are the transcripts of all my YouTube videos. Analyze them and identify the five topics that generated the most depth of engagement based on content density, the three biggest content gaps where my audience likely has questions I haven't answered, and write me a 12-video content plan for the next quarter that fills those gaps and builds on my strongest topics. Format the plan with a title, one-line hook, and key talking points for each video. What comes back is a full quarter of content apt to your actual archive. Based on what you've actually made, not generic advice. A plan built from your specific content history. For the AI Profit Boardroom, that means every video we make next is rooted in what our audience actually engages with. Use case two, member onboarding personalization. Here's the problem. When someone joins a community or a course, they get the same welcome email, the same start here page, the same generic path as everyone else. Every member is different, different goals, different experience level, different starting point. You load in your full training library, every module, every resource, every SOP, along with the intake form a new member just filled out. Then you run this prompt. A new member just joined the AI Profit Boardroom. Here is their intake form. They run a small content agency. They have basic knowledge of ChatGPT. Their main goal is to automate client reporting and content delivery, and they have 5 hours per week to dedicate to learning. Here is our full resource library. Build them a personalized 30-day learning path. It's the exact resources in order, explain why each one is relevant to their situation, and tell them what to skip for now. What comes back is a fully personalized onboarding plan for that exact member. A template, custom road map built from their goals and your actual content without extra work from the team. Every new member gets that experience automatically. Use case three, business intelligence from raw data. Here's the problem. Most businesses are sitting on a goldmine of data they never actually use. Support tickets, sales call notes, CRM entries, email threads, it all just piles up. Nobody has time to read through all of it and pull out the real insights. You export three months of support tickets, sales call transcripts, and lost deal notes. You drop it all in. Then you run this prompt. Here are three months of support tickets, sales call transcripts, and notes from deals we didn't close. Analyze all of it and give me the top five questions or objections that come up before someone decides to buy, the top three complaints or friction points that existing members bring up most, and one recommendation for a new resource or feature we could create that would directly address the most common gap you see across all three data sources. Comes back is a clear picture of exactly what your audience needs, what you think they need, what they're actually telling you, extracted from real conversations. That's the kind of insight that used to take weeks of manual review. You don't need to understand the engineering to use this model, but knowing why it works the way it does makes you a smarter user. DeepSeek uses mixture of experts architecture, MoE version. Imagine you have a team of 100 specialists. Every time a task comes in, only the three or four people relevant to that task activate and do the work. Rest stay idle. That's MoE inside the model. 1.6 trillion parameters total, but only a small fraction firing on any given query. That's how you get top-tier output at a fraction of the compute cost. Let's talk benchmarks, cuz numbers without context are just noise. MMLU Pro sits at 87.5%. That's a strong general knowledge and reasoning score. CodeBench hits 93.5%, which is exceptional for coding performance. The scores put DeepSeek V4 firmly in the top tier of available models. Be honest take. Is it perfect? For real business tasks, writing, summarizing, coding, data analysis, automation, content generation, DeepSeek V4 competes directly with the best in class at a fraction of the price, fully open, fully accessible. That trade-off is worth understanding clearly. It's where to go next. If you want to learn exactly how to use tools like DeepSeek V4 inside a real business, not just experiment with it, but actually build systems that run, come join the AI Profit Boardroom. Your frameworks, your workflows, your automation. Link is in the description. And if you want something completely free, join the AI Success Lab. It's our free community with over 40,000 members using AI to run smarter operations right now. You'll get the full notes from this video, access to over 100 AI use cases, and the SOPs to implement them today. Links are in the comments and the description. Try DeepSeek V4 right now at chat.deepseek.com. Free to use, no wait list. If you got value from this, leave a comment. Julian reads every single one. And subscribe, cuz this space moves fast and I'll be