Private LLM developers outpace public hyperscaler models
The leading private LLM developers (OpenAI and Anthropic) are capturing the core value of the AI boom, while public hyperscalers' proprietary models are lagging in token volume growth.
The argument
The speakers noted that while Google's Gemini token production grew from 10 billion to 16 billion per minute, Anthropic's token volume grew 10x to 15x in the same period, suggesting the 'big two' private players are pulling away.
The thesis, stress-tested
✓ What validates it
- ✓Anthropic and OpenAI maintaining dominant market share in enterprise API usage
- ✓Google's Gemini failing to close the performance and adoption gap in developer evals
▸ Risks discussed
- ▸Hyperscalers being relegated to low-margin distribution and compute providers
- ▸High capital requirements for proprietary model development
Hear it yourself
"when, you know, when when the music stops, who has a chair with a trillion dollars on it. Right? And that's what we're all trying to figure out here. You know, there still remains probably in that substack you quoted and others. There's remains a lot of skepticism that's investment ties. It's consuming all of our free their free cash flow. Are they really capturing yeah. Microsoft's own some of OpenAI's IP, but are they really capturing that value? And we went from free cash flow engines to no free cash flow."
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