// methodology · verified 13 Oct 2026
How we verify
Every figure on the Builder's Radar traces back to its primary source. No source, no number — no estimated numbers, no filler, no theater.
The rule
The Radar is a command board, not a feed. Before publishing a number we find the primary source (public API, official report, earnings call), store its URL and the date we manually verified it. No source, no number — even if the number is viral. On 27-Sep-2026 we discarded two adoption figures (75.6% and 93.6%) for exactly that reason.
live vs curated
The system is hybrid: ~70% refreshes itself from public APIs, ~30% needs human judgment. Badges say which world each number comes from:
- ● liverefreshed automatically — by the source page itself or by our hourly cron — and stamped with its last fetch time.
- ○ curatedpoint-in-time document (survey/report), manually verified on 13 Oct 2026.
They are never mixed without warning. If an API fails we fall back to the curated figure — never to fabricated values.
Every source
The exact list the radar's “Data & Sources” panel opens, rendered from code (single source of truth, always in sync):
Every figure on the board
The 8 comparative metrics, with their labels exactly as shown on the radar and the sources backing each:
Global inference share · text requests
USA · 40.3%
US models · OpenAI · Google · Anthropic
CHN · 47.9%
CN models · DeepSeek · Z.ai · Qwen · Xiaomi · Tencent
Frontier capability · Vals Index
USA · 68.90%
best US model · Gemini 4 Argon
CHN · 55.20%
best CN model · MiMo V2.6 Pro
Frontier training run · public cost
USA · > $100M
US runs · Grok 4 ≈ $388M (Epoch)
CHN · $3.47M
MiMo-V2.6 · RL phase (live log)
Flagship API cost · $/1M input tokens
USA · $10.00
GPT-6 Astra
CHN · $1.32
DeepSeek V4 Pro
Value-tier API cost · $/1M input tokens
USA · $0.75
Gemini 3.8 Flash
CHN · $0.14
MiMo-V2.6-Flash (Xiaomi)
Open-weight flagships · tracked
USA · 0 of 3
GPT-6 · Claude · Gemini closed
CHN · 3 of 3
DeepSeek · Qwen · GLM open
Max flagship context window
USA · 1.05M
GPT-6 Astra
CHN · 1.05M
MiMo-V2.6 (Xiaomi)
Consumer AI adoption · national stats
USA · 61.8%
adults 18–64 · US RPS survey (May 2026)
CHN · >50%
share of population · CNNIC (H1 2026)
Adoption: explicit denominators
The two figures are NOT directly comparable and we say so on purpose: the US surveys working-age adults, China counts the whole country.
Discarded figures: 75.6% / 93.6% — went viral with no primary source findable (searched 27-Sep-2026). No source, no number.
Verified users (globe rings)
A hub only draws its MAU ring when an officially published figure exists. No official figure → no ring. Never estimated:
What stays human
The curator's value lives in the data companies don't publish and in the strategic reading. This is NEVER automated: training costs (almost never in APIs), open vs closed philosophy, “usefulness” context of a model, and the insights that give the numbers meaning. If a figure has no public source, it's written by hand or it doesn't appear.
Region classification
Region follows the real organization, not the repo's language: meta-llama = USA, mistralai = EU (neither USA nor CHINA → OTHER; sides are never forced) and Chinese labs are verified orgs (deepseek-ai, QwenLM, XiaomiMiMo, minimaxai…).