For the last few years, the AI space has been defined by a single truth: OpenAI was ahead. Far ahead. They had the best models, the biggest breakthroughs, and a pricing structure that reflected their dominance. And despite all the advancements in open-source AI and competing models, that still hasn’t changed. GPT-4o remains the best overall model in terms of quality, reasoning ability, and flexibility.
But something else has changed: the cost dynamics of AI are shifting rapidly, and OpenAI is no longer operating in a world where they can price however they want. The industry isn’t just catching up in some areas—it’s racing past OpenAI in terms of affordability, and quality to some point, and that’s putting serious pressure on their once-unshakable position.
How We Got Here
Two years ago, AI models were prohibitively expensive. GPT-3 launched at around $60 per million tokens, which meant only well-funded companies could afford to deploy it at scale. But then, prices began dropping—fast.
GPT-3.5, GPT-4, and now GPT-4o have all been major quality improvements, but the real story is in the cost curve. Running a state-of-the-art model has gone from “ridiculously expensive” to “nearly free” in some cases. Today, there are AI models that cost mere cents per million tokens—and that’s a fundamental shift in how AI businesses operate.
What caused this? Competition.
When OpenAI was the only game in town, they had full control. But over the last year, new players, Google, Anthropic, Mistral, DeepSeek, have introduced competitive models, often at drastically lower prices. Open-source AI, once a niche effort, is now a real force, with models like DeepSeek R1 and Mixtral delivering solid performance for a fraction of OpenAI’s cost.
However, while these alternative models are improving, none of them have truly surpassed GPT-4o. OpenAI still holds the crown in overall reasoning ability, flexibility, and consistency. The real challenge isn’t only quality—it’s whether they can maintain their position while prices collapse around them.
The Three Fronts of the AI War
There are three major areas where AI companies are competing:
- Model Quality – How good is the output? How well can the model reason, summarize, or generate text?
- Inference Cost – How much does it cost to run a query?
- Context Window & Usability – How much information can the model process at once, and how easy is it to use?
For years, OpenAI led in all three. Now, they still dominate in quality and usability—but they’re losing badly in cost.
1. Quality - OpenAI Still Reigns Supreme
Despite all the excitement around open-source and competing models, GPT-4o remains unmatched. It has better reasoning ability, more nuanced responses, and fewer hallucinations than any other publicly available model.
Some competitors—like Claude 3 and DeepSeek R1—perform well in specific areas, but none of them consistently outperform GPT-4o across the board. This means OpenAI still holds a real competitive advantage—but the problem is that better quality alone might not be enough anymore.
2. Price - OpenAI Is Losing the Cost War
This is where OpenAI is facing real pressure.
AI generation is becoming a commodity, and OpenAI is no longer dictating the prices. Google’s Gemini 1.5/2, DeepSeek R1, and open-source models like Mixtral are all delivering solid quality at significantly lower costs.
The biggest wake-up call came when DeepSeek released a near-GPT-4-quality model for pennies. OpenAI had no choice but to respond, slashing prices aggressively with GPT-4o. But even then, they still aren’t the cheapest option.
In other words:
- OpenAI has the best model, but it’s expensive.
- Competitors are closing the quality gap while drastically undercutting OpenAI on price.
- Developers and businesses are now forced to ask: is GPT-4o’s superiority worth the extra cost?
3. Context & Usability - The Wildcard
OpenAI still dominates in usability. ChatGPT is far more polished than competitors, with smoother interactions, better memory, and a cleaner UI.
But Google is making big strides with Gemini’s massive 1M-token context window, which allows users to input far more information at once. If this becomes the industry standard, OpenAI will have to follow—or risk losing ground in areas where context size matters most.
Why OpenAI’s Moat Is Shrinking
The big realization hitting the AI world is this: having the best model is no longer enough.
A year ago, OpenAI could justify its higher prices because of its clear quality lead. But as competitors get better, that argument is getting weaker. If DeepSeek’s next model is 95% as good as GPT-4o but 10x cheaper, why would most businesses stick with OpenAI?
The reality is that switching AI providers is easier than ever.
Changing from OpenAI to another model often requires just one line of code. This is a nightmare scenario for OpenAI.
In traditional cloud computing (AWS, Azure, Google Cloud), switching providers is painful because infrastructure is deeply integrated. AI models don’t have this kind of lock-in. If OpenAI charges too much, developers can just switch overnight.
And they are.
The New AI Business Model - The Wrappers Win
This has led to an unexpected outcome: the companies making the most money in AI aren’t the model creators—they’re the ones building on top of them.
OpenAI, Google, and Anthropic are fighting a brutal, low-margin war. Meanwhile, companies like Perplexity, Poe, and anyone running an AI-powered SaaS business are thriving.
Why? Because they aren’t selling raw AI models—they’re selling experience, workflows, and solutions.
For example:
- Notion AI integrates LLMs into note-taking and project management.
- Perplexity AI is a chat-first search engine that outperforms Google in certain areas.
- Quora's Poe, and other similar offerings, has gained traction by offering seamless access to multiple AI models, allowing users to compare and switch between them effortlessly.
The companies making real money aren’t OpenAI or Anthropic. It’s the platforms that use them.
Sunil Ramlochan
What Happens Next?
The AI industry is at a turning point. OpenAI, once an untouchable giant, is now playing defense. They’re being forced to slash prices, optimize their models, and even release open-source projects—things they never would have done just a year ago.
So, what happens next?
- More Open-Source Disruption – Models like DeepSeek R1 and Mistral Mixtral are proving that open-source AI can compete at the highest levels. This trend will only accelerate.
- AI Becomes a Commodity – Just like cloud computing, AI models are becoming a commodity. The real value will be in who builds the best products on top of them.
- Google and Meta Get More Aggressive – Google has been slow, but Gemini 1.5 showed that they’re finally catching up. Meta’s next LLaMA models will be even better. OpenAI won’t be the only big player for much longer.
- The Real Winners Will Be the Builders – The people who use AI to solve real problems—not just those training models—will capture the most value. AI is no longer about research papers; it’s about who ships the best product.
OpenAI Still Leads, But the Market is Changing
OpenAI still has the best model—but they’re no longer an uncontested leader. The problem is that quality alone isn’t enough anymore.
As AI gets cheaper, the true battle isn’t about who has the best model—it’s about who can use AI most effectively. And that’s good news for everyone building in this space.
The AI gold rush isn’t about who digs up the biggest nugget anymore. It’s about who turns the gold into something useful.