The AI race, measured

Unbiased, data-driven research on the AI race. Who's actually winning, how fast it's moving, and what it means.
Chart of the day
METR Projections — Two Labs, Two Trajectories
Latest: Anthropic broke the METR trend at Sonnet 4.5 — doubling every 1.7 months while OpenAI holds steady at 3.8. Mythos forecast: 28h, GPT-5.5: 9h.
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Published research preview
How Public Markets Already Own the AI Frontier
Anthropic and OpenAI are private; their cap tables aren't. Six US-listed names sit on most of the upside — and not all the exposure is what it looks like.
Apr 2026
How Long Can Claude Mythos Work Alone?
METR hasn't scored Mythos yet — we predicted it. Regression across 19 models puts it at ~15 hours of autonomous work. If the frontier is accelerating, it could be 30.
Apr 2026
Do Benchmark Breakthroughs Actually Matter?
We tested whether SOTA events move stock prices or token consumption. Answer: they shift usage within 2 weeks, but markets don't care. 30+ interactive charts.
Mar 2026
Kimi, Composer, and the Build vs Buy Dilemma
Cursor quietly switched from Anthropic to a fine-tuned open-weight model. We traced it in real-time through 6 data feeds before anyone reported it.
Mar 2026
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About

Many viewpoints, one record.

The AI race, told through evidence. Collected at the source, every day.

Most of the AI story is told through press releases and announcements. The data underneath — model pricing, token consumption, benchmarks, agent commits, training compute, developer adoption — lives in dozens of incompatible places and changes weekly. There is no canonical source.

We built one. Synopticon collects across the AI ecosystem every day and keeps a continuous record of what's moving in the race. Starting tomorrow, no one could reconstruct the history.

The product is in the triangulation. Anthropic claims one thing, OpenRouter shows another, Portkey shows a third — and the gap between them is usually where the story is. We track those gaps daily and publish what they show, in granular detail: by lab and model, by benchmark category, by enterprise vs. developer routing, by SDK adoption per package. Not "AI capex up 40%." That's the wrong map.

What you get: research investors and operators can act on. Evidence first. No sponsored takes. No claim without a chart.

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