Learn more
Not the chips. Those changed beyond recognition.
What never changed is why every machine you own still wastes most of what you paid for it.
The industry's answer to every wall is more hardware: more racks, more memory, a bigger bill, more power. The machines already bought sit under-used, and the vendor is paid more the more you consume. That is not an accident. It is the incentive.
We changed it. The same machines, the same models, the same answers, for substantially less, with substantially more completed. It runs in software today on hardware you already own, and we are putting it into silicon. We are paid only out of the reduction, which is why the shadow run is free and the public endpoint answers anyone.
Every figure, with its condition
The numbers, and what they were measured under.
- 84.54%
- off the model bill, in our seeded testseed 3, 3,000 requests. The naive sum of 116.64% is refused
- 39.16%
- off the bill with your model held fixednothing re-routed, nothing swapped
- 63.77%
- less power for the same answerssix levers composed, seed 5. 46.89% on the most hostile traffic we could invent. An estimate, not a meter reading
- 54.5%
- compute saved, zero violationsread the other way, 2.20× the work. One measurement, never two wins
- 6.64×
- the work from the same hardwarezero priority violations, seed 5
- 91×
- reachable compute, nothing boughthow much of what you own can be put to work. Not a speedup for one job
- 21.333×
- smaller memory poolacross 64 machines
- 88.4%
- of requests anticipatedtouching 7.5% of the space. Anticipating nothing gets 0%; repeating the last one gets 55.6%
- O(1)
- the wait, at any sizethe whole trip — including the read — over a 1,000× corpus on a Google Cloud c3 server, measured across multiple runs. A thousand times the data, 6–7% slower
- 1.856–1.926 µs
- a requeston a Google Cloud c3-standard-8, measured across multiple runs
- 1,256 → 243
- dropped frames of 3,00060 fps, seed 7, quality held rather than turned down
- 0
- invented answers in 6,161 questions3,714 unanswerable. It says "I don't know" 4.7% of the time
- 2,007 of 2,007
- attempts to overclaim, refused380 guards. A count, never a percentage
Composed figures are computed on the remainder, never summed. Reproduce them yourself: curl https://api.wubbery.com/v1/public/proof, no key. Measured on the deployed engine at 2026-10-02. We add capabilities continuously, so these are a floor — the live endpoint is always current.
The laws we leap
Six ceilings the industry designs around. One we keep.
- Von Neumann's bottleneck
- 21.333× smaller memory pool; 88.4% of requests anticipated while touching 7.5% of the space.
- Waiting for Moore
- 91× reachable compute from the same silicon.
- The end of Dennard scaling
- 63.77% less power for the same answers.
- Wirth's law
- O(1): the wait at a million items is the wait at a thousand.
- The frame budget
- 1,256 → 243 dropped frames of 3,000, quality held.
- Jevons' paradox
- Inverted. We are paid only out of the reduction, so efficiency is the product, not the leak.
- Amdahl's law
- Kept. Speedups do not add. Our parts summed claim 116.64% off the bill; the composed measurement delivers 84.54%, and that is the number we publish.
Where next