July was the month AI stopped being expensive. Here's what actually happened.

I've been tracking this space for a while and July felt different from any month I can remember. Three things happened that I think most people haven't fully processed yet. On July 9th, three major labs released new models on the same day. That had never happened before. OpenAI launched Sol, Terra, and Luna, a tiered family ranging from $1 to $30 per million tokens. For the first time, companies can actually match the model to the task instead of paying top dollar for everything. Same day, Grok 4.5 pushed hard into coding, and Meta released a system that can process one million tokens in a single request, roughly the size of an entire company's internal documentation. Then Moonshot in China dropped Kimi K3. 2.8 trillion parameters, free to download, run it on your own servers. Independent benchmarks put it close to the top commercial models. That gap looked impossible to close twelve months ago. Here's what I think actually changed this month. Cost is no longer the main barrier to using serious AI. And control is no longer limited to three or four companies. That's a real shift in who holds the leverage, away from the providers and toward the businesses using the technology. Curious whether anyone is already seeing this play out in how their organization is thinking about AI spend or vendor lock-in.