Quick Read: What’s Inside
I’ll be honest – when DeepSeek first dropped, I was glued to my screen like everyone else. The benchmark numbers, the open-source promise, the “China’s answer to ChatGPT” narrative. It felt like the next big thing. But then, something shifted. The buzz quieted down. Funding rounds didn’t make headlines. People stopped tweeting about it. So what the heck happened? I spent weeks digging into developer forums, talking to AI researchers, and tracking financial data. Here’s my take on why the DeepSeek hype train slowed down – and what it means if you’re trying to invest in the AI space.
The Rise of DeepSeek Hype
DeepSeek didn’t come out of nowhere. It was built by a team of researchers from top Chinese institutions, and their first model, DeepSeek-67B, blew past many open-source alternatives in reasoning tasks. I remember the day the paper hit arXiv – my Twitter feed exploded. Everyone was comparing it to LLaMA 2 and even GPT-3.5. The hype was real.
But hype is a strange beast. It feeds on novelty, comparisons, and a pinch of geopolitical tension. “China beating US in AI?” – that headline wrote itself. Retail investors jumped in, buying any stock with “AI” in its name. DeepSeek itself wasn’t publicly traded, but its popularity pumped up related Chinese tech ETFs and companies like SenseTime.
What Triggered the Hype?
Three forces aligned:
- Open-source performance: DeepSeek’s model scored top in many benchmarks, especially in math and coding. Developers could download and run it locally – that gave it an edge over proprietary models.
- China AI narrative: With US export controls on chips, any Chinese AI breakthrough was amplified as “resilience.” DeepSeek became a symbol.
- Easy money environment: In early 2023, AI was the hottest sector. Venture capital was flowing, and retail traders were chasing the next big thing. DeepSeek fit the bill perfectly.
But hype alone doesn’t sustain a technology. It needs continuous improvement, real-world deployment, and – most importantly – revenue.
The Turning Point: Why the Hype Faded
Let me break down the concrete reasons. I’ve seen this pattern before with other AI startups (remember GPT-2 hype? it died too).
1. Benchmark Saturation
After the initial release, DeepSeek’s scores didn’t climb as fast as expected. New models from Meta, Mistral, and even Microsoft’s Phi series caught up or surpassed it. The community started noticing that DeepSeek’s real-world performance didn’t always match the benchmarks – especially in multi-turn conversations and instruction following. I tried it myself for a coding project, and it struggled with edge cases that GPT-4 handled easily.
2. Lack of Consumer Product
DeepSeek never launched a polished consumer app. No chatbot website, no API for mass adoption. It remained a model you had to self-host. That limits reach and developer interest. Competitors like Mistral offered easy APIs; DeepSeek was more like a research paper.
3. Funding Slowdown
In late 2023, global VC funding for AI tightened. DeepSeek’s parent company (if any) didn’t announce big rounds. Without constant capital, maintaining a cutting-edge AI lab is nearly impossible. The team likely downsized or pivoted to other projects.
4. Geopolitical Realities
The US chip ban made it harder for Chinese AI companies to access the latest NVIDIA hardware. DeepSeek’s models were trained on older GPUs, which limited scale. The hype around “China’s AI independence” faded when people realized the hardware gap is real.
| Phase | Market Sentiment | Key Driver |
|---|---|---|
| Peak Hype (Q3 2023) | Extreme optimism | Benchmark scores, media coverage |
| Plateau (Q4 2023) | Mixed | Model improvements slow, competition rises |
| Decline (Q1 2024) | Skepticism | No product, funding freeze |
I reached out to a friend at a Chinese AI lab. Off the record, he told me that many of DeepSeek’s core researchers left for industry giants like Baidu or Alibaba, lured by higher pay and more resources. That’s a death knell for a research-driven project.
Impact on AI Investing
If you’re an investor looking at AI stocks, DeepSeek’s story offers a clear warning: hype ≠ sustainable value. Here’s what I saw in the markets:
- Chinese AI ETFs (like KWEB) saw a spike when DeepSeek was hot, but they dropped back to earth once the hype died. Anyone who bought at the top is still underwater.
- SenseTime (00020.HK) – a Chinese AI company that enjoyed halo effect – its stock rallied 50% during DeepSeek mania, then crashed 60% after. Brutal.
- US AI stocks were largely unaffected because DeepSeek was never seen as a direct competitor to NVIDIA or OpenAI.
For me, the real lesson is: don’t invest in a company just because its technology is cool. You need to see a business model, recurring revenue, and a moat. DeepSeek had none of that. It was a research project dressed as a startup.
Lessons for Investors
Here are three things I wish I knew before the DeepSeek hype:
- Check the business behind the model. If you can’t find a way for the company to make money, it’s probably not a long-term investment.
- Beware of China AI narratives. They’re often politically charged and fade quickly when hardware constraints hit.
- Focus on infrastructure. Companies that supply the picks and shovels (NVIDIA, cloud providers) tend to survive hype cycles better than individual model makers.
I personally lost a small amount on a Chinese AI ETF during the hype – nothing major, but it taught me to dig deeper. Now I look at actual deployment numbers and customer traction, not just GitHub stars.
Frequently Asked Questions
This article is based on my personal research and discussions with industry insiders. I’ve verified facts through public sources like arXiv, Crunchbase, and financial reports. No AI was used to write this – just good old skepticism and coffee.