Insights // the AI wave, in numbers
Four years in, the numbers tell a calmer story than the headlines
Manta Labs ships AI work for working businesses. The brief on this page is the same brief we walk into every engagement with — what is actually moving, by how much, and where the money goes. We refresh it as new data lands.
As of 6 May 2026 · sources at the bottom
0,
Models tracked since 1950 (Epoch AI)
0.0T
Tokens processed every day across the major providers
0.00M
Hopper-class GPUs deployed worldwide by end of 2025
$0.0B
Private AI investment in the US, 2025 (≈23× China)
01
The labs
The revenue race
Two quarters ago this was a one-horse race. It isn't any more.
Annualized revenue//OpenAI · Anthropic · Google AI
Run-rate, not booked. Numbers come from disclosed quarterly figures and Epoch AI's revenue dataset. The yellow band marks the quarter where Anthropic crossed OpenAI on annualized run-rate.
Source: Epoch AI revenue tracker; SaaStr; Sacra.
$28M → $24B
OpenAI: roughly 850× in four years.
~$100M → $30B
Anthropic: a 300× climb, mostly in the last six quarters.
0 → $14B
Google AI: late to monetize, now compounding fast.
02
The training
The compute curve
Frontier models double on training compute every six months. They have done so for a decade. The slope hasn't bent.
Source: Epoch AI — large-scale AI models database. Y-axis is log-FLOPs.
Two practical implications. First, the largest run on record (Grok 4) emitted more than 72,000 tons of CO₂-equivalent — published in the 2026 AI Index. Second, the next jump on this chart will not come from more H100s; it will come from the GB200 / GB300 generation now landing in hyperscaler racks.
03
The price
The cost of intelligence collapsed
A thousandfold cheaper, in three years, for the same work. This is the chart that matters for anyone shipping product.
1,000×
Cheaper to run GPT-3-class intelligence today than at launch. GPT-4-class follows the same curve, eighteen months behind. Token prices fall roughly an order of magnitude each year.
Nov 2022 → May 2026 · per million tokens
Source: Epoch AI — LLM inference price trends; Stanford AI Index 2026.
04
The volume
The token tsunami
If revenue is the score, tokens are the play count. One provider is now larger than the next four combined.
Source: provider disclosures (Microsoft, Google), OpenRouter analytics, ByteDance press notes.
ByteDance's lead is almost entirely AI-generated short video — a different use case than the chat-and-code workloads driving Western providers. For the western stack, agentic flows are the new headline; one well-scoped agent run consumes more tokens in an hour than a whole team of users did in 2024.
05
The bill
The electricity bill is real
The IEA expects data-centre demand to roughly double by 2030. AI is the reason.
Source: IEA — Energy and AI (2025 + 2026 updates). Yellow segments are the AI share of total data-centre load.
+50%
AI-focused data-centre electricity, 2025 alone.
945 TWh
Projected total data-centre electricity in 2030 — about 3% of global demand.
4×
Expected growth in AI-optimised data-centre electricity by 2030.
06
The market
Adoption faster than the internet
Generative AI hit 53% population adoption in three years. The internet took seven. The PC took ten.
Source: Stanford AI Index 2026 (consumer adoption); Pew Research; historical Census Bureau.
07
The releases
Four years of frontier
Yellow dots mark releases that reset the frontier. Everything else is the field keeping up.
Source: Epoch AI; llm-timeline.com; provider announcements.
How this stays current//the boring middle
We refresh this page from a pipeline, not a press cycle. An Inngest job runs once a day, pulls the latest CSVs and APIs from the sources below, normalizes the fields the page renders, and writes a snapshot to Postgres. The page reads the latest snapshot at request time. If a source is down or a number looks wrong, the previous snapshot stays live.
- RevenueweeklyEpoch AI revenue dataset (CSV, public).
- Compute · modelsweeklyEpoch AI large-scale AI models database.
- Inference priceweeklyArtificial Analysis API + Epoch's inference-price tracker.
- Token volumeweeklyOpenRouter analytics + provider earnings disclosures.
- EnergyannualIEA — Energy and AI (Base Case scenario).
- Adoption · headlinesannualStanford HAI — AI Index 2026.
See site/app/(marketing)/insights/DATA_PIPELINE.md for the implementation notes.
If the chart that matters most is the cost-collapse one, the question is what you ship with it
That's where we come in. Pick a workflow that's bleeding time. We'll ship a working fix.