How the Index measures and publishes

How often three model APIs name or cite each model and API platform when asked a fixed, public set of buying questions.

Reviewed AEO and AI-search analytics vendors ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Domains ranked by unique cited answers, prompt breadth, engine breadth, and position.

The pages AI answers cite most across the public buying questions, ranked by the share of answers that cite them.

Vendor recommendation presence when every buying prompt explicitly asks for the United States market.

Vendor recommendation presence when every buying prompt explicitly asks for the United Kingdom market.

Vendor recommendation presence when every buying prompt explicitly asks for the Canadian market.

Vendor recommendation presence when every buying prompt explicitly asks for the Australian market.

Vendor recommendation presence in a disclosed enterprise VP of marketing prompt context.

Vendor recommendation presence in a disclosed in-house SEO and AEO lead prompt context.

Vendor recommendation presence in a disclosed multi-client agency-owner prompt context.

Vendor recommendation presence in a disclosed small-team founder prompt context.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

Reviewed brands ranked by the share of all the category's answers that name or cite them.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed brands ranked by answer-level citations to their reviewed domains.

Reviewed brands ranked by how many of the three model APIs name or cite them.

The brand named most for each public buying question, and how many of the three model APIs agree.

Prompts ranked by mean pairwise Jaccard distance between the reviewed-brand sets surfaced by each engine.

Prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

Reviewed brands ranked by how often OpenAI's model API names or cites them in answers to the category's recommendation questions.

Reviewed brands ranked by how often Anthropic's model API names or cites them in answers to the category's recommendation questions.

Reviewed brands ranked by how often Google's Gemini model API names or cites them in answers to the category's recommendation questions.

Hugging Face repository downloads and engagement for a fixed, reviewed model cohort.

Exact model configurations ranked by the latest official LiveBench release: one benchmark's view of capability.

Official cost per successful LiveBench task beside capability, token use, and the exact prices frozen into the release.

Exact model-plus-inference configurations ranked by UC Berkeley BFCL V4 overall accuracy, with tool-use breakdowns, cost, latency, and source evidence.

Official style-controlled text human-preference ratings with confidence bounds, variance, vote counts, and a frozen dataset revision.

Statewide average retail electricity prices for commercial and industrial customers, from EIA.

Reviewed first-party project announcements ranked by disclosed reference amount, with qualifiers preserved and actual spend explicitly separated.

EPA eGRID generation-based annual state CO2e output rates with nameplate capacity, net generation, and coal, gas, nuclear, and renewable mix. Not consumption-based, marginal, or data-center-specific.

Reviewed vector retrieval platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

A reviewed first-party project cohort with announced, under-construction, and energized stages plus separately scoped disclosed datacenter and compute MW. Permits and grid queues are never inferred.

Announced and permitted capacity separated by development stage and confidence.

Reviewed GPU infrastructure providers ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed cloud platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Hourly Akash Network median and minimum GPU-hour prices, available units, total supply, provider count, memory, and interface.

Exact Linux on-demand Azure West US 3 VM and normalized physical GPU-hour retail prices for a fixed reviewed SKU cohort.

First-party reported accelerator memory capacity and bandwidth for a fixed reviewed NVIDIA and AMD cohort.

Exact public Linux on-demand EC2 prices in US East (N. Virginia), normalized by documented physical GPU count.

Epoch AI current positive-capacity facilities ranked by estimated total facility MW, with 2025-dollar capex and calculated H100-equivalent compute beside every row.

Latest future-dated Epoch AI capacity milestone per facility, with planned MW, 2025-dollar capex, H100e, construction status, evidence, and uncertainty preserved.

Epoch AI estimates of the compute each company owns, in H100 equivalents, with uncertainty bands and chip context. It counts hardware owned; how much of it runs is a separate question.

Reviewed platforms ranked by the share of all the category's answers that name or cite them.

Reviewed platforms ranked by distinct answer-level citations to their canonical domains.

Reviewed platforms ranked by how many of the three model APIs name or cite them.

The platform named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each platform is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each platform is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each platform is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed providers ranked by the share of all the category's answers that name or cite them.

Reviewed providers ranked by distinct answer-level citations to their canonical domains.

Reviewed providers ranked by how many of the three model APIs name or cite them.

The provider named most for each infrastructure buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each provider is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each provider is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each provider is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed providers ranked by the share of all the category's answers that name or cite them.

Reviewed providers ranked by distinct answer-level citations to their canonical domains.

Reviewed providers ranked by how many of the three model APIs name or cite them.

The provider named most for each cloud buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each provider is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each provider is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each provider is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reported revenue, assets, CapEx, cash, and attributable AI-cloud revenue with raw values and source periods.

Latest reported fiscal-year capital expenditure.

Companies ordered by disclosed forward capital expenditure.

SEC-reported total-company TTM CapEx divided by TTM revenue, with latest-quarter CapEx, debt, exact filing evidence, and incomplete issuers excluded.

Who produces chips, models, clouds, applications, and datacenter capacity.

Latest full-company annualized revenue values from Epoch AI, with ARR versus other bases, evidence class, confidence, and source date preserved.

Cumulative closed primary equity funding from Epoch AI. Debt, secondary sales, discussions, cancelled rounds, and valuations are excluded.

Latest Epoch AI records explicitly scoped to the full company; division, role, contractor, and missing-scope values remain outside the leaderboard.

Latest publishable annual compute-spend evidence from Epoch AI, with totals separated from derived inference-plus-R&D component sums and never labeled CapEx.

The public companies financing the AI build-out, ranked by long-term debt relative to total assets, from company filings.

Stars, forks, open work, and repository freshness for a fixed, reviewed AI-tooling cohort.

OpenAlex-indexed AI works and citation signals for a fixed, reviewed lab and institution cohort.

Trailing-365-day OpenAlex-indexed AI works by authorship country, with the exact all-work denominator, unknown geography, and multinational counting disclosed.

Institutions ranked by field-normalized output and citation impact.

Reviewed AI tracing and evaluation platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Exact npm downloads and separate GitHub activity for a fixed reviewed cohort of agent frameworks, agent SDKs, and MCP tools.

Reviewed agent frameworks ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed enterprise search and retrieval platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed coding tools ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed security vendors ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed CRM vendors ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed data platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed integration platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed analytics platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed service platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed marketing platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed revenue-data platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed workforce platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed finance platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed workplace platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed creative platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed commerce platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed AI meeting assistants ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed AI research assistants ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed AI writing and content platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed AI image generation platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed AI video generation platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed AI voice and audio platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed legal AI platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed clinical AI documentation platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Exact BLS SOC 15-2051 state employment ranked with concentration, annual pay, survey error, and suppression status preserved.

Reviewed AI customer agent platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Hugging Face downloads, likes and repository recency for a fixed, reviewed set of datasets: a measure of activity on the platform.

Net trailing-365-day federal transaction obligations by recipient using an exact AI phrase, NAICS, and PSC contract; potential award value is excluded.

The same qualifying USAspending transactions grouped by exact awarding-agency name, with obligations and deobligations included and potential award value excluded.

Reviewed platforms ranked by the share of all the category's answers that name or cite them.

Reviewed platforms ranked by distinct answer-level citations to their canonical domains.

Reviewed platforms ranked by how many of the three model APIs name or cite them.

The platform named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each platform is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each platform is named or cited in Anthropic's model API answers to the category's recommendation questions.

Reviewed frameworks ranked by the share of all the category's answers that name or cite them.

How often each platform is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed frameworks ranked by distinct answer-level citations to their canonical domains.

Reviewed frameworks ranked by how many of the three model APIs name or cite them.

The framework named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each framework is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each framework is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each framework is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed platforms ranked by the share of all the category's answers that name or cite them.

Reviewed platforms ranked by distinct answer-level citations to their canonical domains.

Reviewed platforms ranked by how many of the three model APIs name or cite them.

The platform named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each platform is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each platform is named or cited in Anthropic's model API answers to the category's recommendation questions.

Reviewed tools ranked by the share of all the category's answers that name or cite them.

How often each platform is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed tools ranked by distinct answer-level citations to their canonical domains.

Reviewed tools ranked by how many of the three model APIs name or cite them.

The tool named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each tool is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each tool is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each tool is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each security buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each CRM buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each data platform buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each integration buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each analytics buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each service buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each marketing buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each revenue data buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each workforce buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each finance buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each workplace buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each creative buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each commerce buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.