China's DeepSeek V4 AI Just Changed Everything

China's DeepSeek version 4 AI just changed everything. So DeepSeek version 4 is coming and it's not running on NVIDIA chips. And that's the news that just dropped this week. According to the information citing five people with direct knowledge, DeepSeek's next major model called V4 is built to run on the latest chips made by Huawei.

China's own chip, not American, not NVIDIA, Huawei. And here's why this actually matters for your business. V3 and R1 were the models that tanked NVIDIA's stock price last year in a single day. Investors panicked because DeepSeek proved you could build a world-class AI model at a fraction of the cost of American labs.

Now V4 is doing something even bigger. It's providing China and proving China can build those models without US chips at all. So let's talk about what V4 actually is first. DeepSeek's been quietly iterating since R1 dropped in January 2025.

V3, then V3.1, and then V3.2. Each one getting faster, smarter, and cheaper. Now V4 is supposed to be the big leap. We're talking a million token context window.

That means you can feed it an entire business's worth of documents, contracts, emails, reports, SPS. And it processes all of it in one single go. V3 topped out at 128,000 tokens. V4 is nearly eight times larger.

And it reportedly runs locally on your own hardware for free. Think about what that means. So right now, if you're using Claude, Chachi, Petit, or Gemini, you're paying per token. Every word in, every word out, you get billed.

With V4, you're running on your own machine. Your API bill drops to zero. And an agency running AI-generated content, for example, SEO reports, or lead generation workflows could potentially wipe out their AI costs entirely. But the real story here isn't the model, it's the chips.

So DeepSeek has spent months working directly with Huawei and a second Chinese chip designer called Cambricon Technologies to write pieces of the model's underlying code, specifically to make it run on non-NVIDIA hardware. This is not a small task by any means. Most AI models are deeply tied to the hardware they were trained on. Porting a model to different chips is like rebuilding an engine to run on different fuel.

You have to rebuild core parts of it from scratch. They did it anyway, and it's working. Alibaba, ByteDance, and Tencent have already placed bulk orders for Huawei's upcoming chip, which means hundreds of thousands of units specifically to run V4. These are three of the biggest tech companies in the world, and they're betting on Huawei's chip.

That's a big signal. DeepSeek is also building two additional V4 variants, each one optimized for different use cases. Each one designed to run on Chinese hardware. So this isn't like a one-off experiment.

It's a full infrastructure strategy. If you're a business owner trying to figure out where AI is going, well, here's the open loop that you need to sit with. What happens when China has a world-class AI model that runs completely independent of the US chip supply chain? What does that do to pricing, to competition, to access?

If you want to know how to actually use models like DeepSeek V4 in your business the moment it drops, with step-by-step tutorials, a 30-day roadmap, and an automation plan and coaching calls walking you through exactly how to set it up for lead-gen content and client work inside the AI profit boardroom, we've got 2,700 business owners already automating with tools like DeepSeek, Claude, and more. The moment V4 launches, we'll be breaking it down in detail. How to run it, how to use it, how to get results from it fast. Link in the comments description or go to theairprofitboardroom.com to get access.

Now back to the story, because here's where it gets really interesting. DeepSeek hasn't shared V4 with NVIDIA or AMD for performance optimization. That is normally standard practice in the AI industry. Usually when you're about to release a major AI model, you work with the chip makers to make sure it runs as efficiently as possible on the hardware.

DeepSeek skipped that process entirely. They gave early access to Huawei instead. That's a deliberate move and it sends a message. The US has been tightening chip export restrictions on China for years now.

NVIDIA's H100s, A100s, China can't get them anymore, at least not legally. So DeepSeek is doing what any smart operator does when a supply chain is cut off. They find another way. They build around it.

Huawei's chips, the Ascend line, are getting genuinely competitive. And are they as fast as NVIDIA's best? Not yet. The performance gap is probably real.

But engineers who have worked with both will tell you there's a meaningful difference still in raw throughput. But here's the thing. DeepSeek's whole game has never been build the most expensive, most powerful model. That's not the game they play.

Their game is build the best model per dollar spent. And that's how V3 shocked the world. It matched and beat GPT-4 class models at a fraction of the training cost. If they can do the same thing with V4 on Huawei chips, they get 90% of NVIDIA's performance at half the cost.

And that changes the math for everyone. V4 is expected to land in the next few weeks. There's no official release date yet. But when it drops, it won't just be a model launch.

It will be a proof of concept that China can run frontier AI without American chips. So what does this mean practically for someone running a business right now? Well, here's the first thing. DeepSeek models have always been open way.

That means the trained parameters are public. You download them. You run them yourself. You own the whole thing.

V4 will almost certainly follow the same pattern. And if V4 matches even V3.2's performance, which already rivals GPT-4 class output for most business tasks, which was important last year. Obviously, they've got new models now. Then you have access to a top tier AI model that can run for free on your own hardware.

For example, if you're an SEO agency, you can run hundreds of content briefs a month where you run the whole operation locally. Zero API costs. Full control of the data. Free.

And nobody sees your client work but you. If you're a solo consultant, for example, doing market research, proposal writing, competitor analysis, same story. You could feed version four on entire industry reports at one million tokens, getting a full breakdown without paying anything per token, right? The million token context window alone is a thing people are sleeping on right now with most models, particularly AI agency hit the limit fast, right?

And you're chunking documents. You're losing context. You're piecing things back together. V4 removes that ceiling.

You feed everything at once and it holds it all at once, right? Now, the honest part here is that there are real concerns about deep-seek models for business use. China's data compliance laws that don't align with Western requirements. If you're in a regulated industry, finance, healthcare, legal, using a model hosted on Chinese servers creates genuine risk.

The answer is you could run it locally on your own infrastructure air-gapped. That solves the privacy problem entirely. Performance is also still a question mark too. The benchmarks being thrown around for V4 are mostly pre-release speculation.

Some of them have already been flagged as potentially unreliable. The real numbers come when people actually run it. And that's always been true with deep-seek. The paper says one real thing and the real world testing tells you more.

But here's the trajectory. V3 shocked people. V3.2 was genuinely impressive. If V4 continues that curve and there's no reason to think it won't, then we're looking at another moment where Chinese AI punches way above the cost it took to build it.

Deep-seek V3 triggered a global stock sell-off when it launched. Investors looked at what had been built and what it costs to build it, and they panicked because it broke the assumption that you need billions in compute to stay competitive. V4 is doing something bigger. It's breaking the assumption that you need American chips to stay competitive.

And that's a different kind of move. And every business owner using AI tools now should be watching it. The AI chip war is real. The model is real.

And for the first time, China is genuinely competitive on both fronts. Not because they copied what Nvidia built, but because they spent months rewriting code from scratch to work around it. V4 is coming in the next few weeks. And when it drops, the conversation is going to change again.

If you want to be ready when V4 lands, to know exactly how to set it up, run it locally, and use it to automate your lead generation, your content, your client delivery, the AI profit boardroom is where you want to be. We've got members already running deep-seek workflows for content creation, SEO, business automation. The moment V4 drops, we'll have step-by-step tutorials live with walkthroughs of how to run it on your own setup and coaching course specifically covering how to get V4 working in your business. You're also going to get 2,700 members that you can connect with and just a community with people always online.

Link in the comments description or go to the AI profit boardroom to check it out. Thanks for watching.