A couple of years ago, it seemed that AI would be completely controlled by a few large companies. Whoever had more GPUs and money was the boss.
Then came Llama, Mistral, DeepSeek, Qwen, and Phi, and it became clear that the market would take a completely different path.
➡️ How it is changing AI Market?
It's not just about quality. The most interesting thing is that open-source models are changing the industry, not just because of quality. Although their quality is already pretty good.
The problem is that closed models tie you too tightly to someone else's infrastructure. Today, the API works; tomorrow prices have changed, limits have been cut, policies have been changed, a region has been shut down, the model has gotten worse after an update, and you have no control over any of it.
Why do open-source models change the rules of the game?
With open-source, everything is different.
You want to run locally, fine-tune, quantize, change the inference stack, optimize latency, and keep data within the company? Fine.
For businesses, this makes a huge difference. Especially regarding private data, compliance, large volumes of requests, and expensive inference. There's another important effect: Open-source is rapidly moving the industry forward because thousands of engineers test models, find weaknesses, work on optimizations, create inference engines, and release fine-tuning tools.
Progress doesn't come from the top down but from all sides at once.
What's particularly interesting right now?
Sometimes a small open-source model on a good inference pipeline feels more useful than a huge closed LLM, especially in production, because in reality, it's not just about benchmarks.
What matters? Price, control, latency, stability, and the ability to integrate the model into the system.
Main idea seems to be that the AI market is gradually moving away from the concept of "One gigantic model for everything" towards "Many specialized models for specific tasks."
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