Part of EPR's Citation Share Index franchise. Cluster: Cybersecurity Vendor Citation Share Index · Insurtech Citation Share Index · Fintech Citation Share Hub · Big Tech Reputation Index 2026. Roof framework: Citation Share Index.
By the Everything-PR Editorial Team
Phase 0 publication, June 2026. Phase 1 data drop scheduled Q3 2026.
OpenAI. Anthropic. Google DeepMind. Meta AI. Mistral. The five AI labs that define the frontier-model layer in 2026 are also the five most-named entities inside AI engine answers about AI itself. They train the engines. They become the engines' canonical references. The reflexivity is the structural feature that makes this category different from every other AI Citation Share Index franchise EPR runs.
This is the Phase 0 publication. Methodology, scoring rubric, entity landscape, and Q2 2026 positioning reads anchored in public events through January 2026. The first full data drop — Citation Share percentages across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews on a locked prompt set — is scheduled for Phase 1 in Q3 2026.
Key Takeaways
Same five-factor scoring formula as the broader Citation Share Index franchise — calibrated to the AI Labs category.
| Factor | Weight | What it measures |
|---|---|---|
| Citation Frequency | 40% | How often the lab is named in AI engine answers about its category |
| Cross-Engine Breadth | 20% | Citation balance across ChatGPT, Claude, Perplexity, Gemini, AI Overviews |
| Query-Type Breadth | 20% | Coverage across model-launch, safety, enterprise, research, ecosystem queries |
| Extractability | 15% | How cleanly model cards, research papers, and product docs parse |
| Crawl Access | 5% | GPTBot, ClaudeBot, PerplexityBot, Google-Extended permissions |
The reflexivity caveat applies to this category specifically. The engines being measured for citation share are products of the labs being scored. Phase 1 methodology will publish the cross-engine balancing approach that controls for self-reference bias.
Five labs. Five structurally different positions. The Phase 0 reads below establish the qualitative landscape that Phase 1 quantification will confirm or revise.
| Lab | Primary Position | Q2 2026 Anchor Event |
|---|---|---|
| OpenAI | Scale + reach leader | GPT-4o (May 2024), $157B valuation (Oct 2024) |
| Anthropic | Enterprise + safety leader | Claude 3.5 Sonnet + Computer Use (Oct 2024), Amazon $4B+ investment |
| Google DeepMind | Research + integration leader | Gemini 2.0 (Dec 2024), AlphaProteo (Sept 2024) |
| Meta AI | Open-model distribution leader | Llama 3.3 (Dec 2024), 600M+ Meta AI users |
| Mistral | European sovereign play | Mistral Large 2 (Jul 2024), Microsoft partnership |
OpenAI enters Q2 2026 as the largest AI lab by user reach, capital base, and category-defining-product surface. ChatGPT reached approximately 300M weekly active users by late 2024 — the fastest consumer-product scale in modern technology. The $157 billion valuation in the October 2024 funding round set the comparable-co reference for the entire AI labs category. The GPT-4o release (May 2024), the o1 reasoning-model launch (September 2024), the Sora video model release (December 2024), and the Operator agent launch (January 2025) anchored the product cadence through the period.
The reputation cost is real and named. The Sam Altman board-removal-and-reinstatement event (November 2023). The Scarlett Johansson Sky voice controversy (May 2024). The repeated senior-research-leadership departures across 2023, 2024, and 2025 (Ilya Sutskever, Jan Leike, Mira Murati, Bob McGrew, and others). The New York Times copyright lawsuit (filed December 2023, ongoing). The pattern: OpenAI's narrative compounds positively on capability but negatively on governance and trust. The composite ranking position depends heavily on how Phase 1 weights enterprise-trust queries against consumer-reach queries.
Anthropic enters Q2 2026 with the strongest enterprise-trust positioning in the AI labs category. Claude 3.5 Sonnet (June 2024) and Claude 3.7 Sonnet (early 2025) produced the cleanest enterprise-developer reception of any frontier model launch cycle. The Computer Use feature launch (October 2024) demonstrated the kind of agent capability OpenAI's Operator subsequently launched against. The Amazon $4 billion+ investment and AWS partnership produced the enterprise-distribution scale Anthropic's product positioning required.
Anthropic's category-defining differentiator is the Responsible Scaling Policy, the Constitutional AI methodology, the public model cards with extensive safety evaluations, and the consistent CEO Dario Amodei + President Daniela Amodei communications discipline. The pattern: Anthropic's reputation compounds positively across enterprise-trust, AI-safety, and research-quality dimensions simultaneously. The downside is reach scale — Anthropic's user numbers run substantially below OpenAI's, and the consumer-product surface is narrower.
Google DeepMind enters Q2 2026 as the deepest research operation in the AI labs category. The Gemini 2.0 launch (December 2024), the AlphaProteo protein-design system (September 2024), AlphaFold 3 (May 2024), and the continued AlphaGo / AlphaZero lineage of research-anchored AI capabilities produce the most-cited primary research publications in the category. The integration into Google's product surface — Search, Workspace, Android, Cloud — produces the largest distribution footprint of any AI lab.
The reputation cost is the Gemini launch misfires (image generation issues February 2024), the AI Overviews accuracy controversies (May 2024 "put glue on pizza" coverage), and the inherited Alphabet regulatory exposure (August 2024 DOJ search-monopoly ruling). The pattern: DeepMind's research authority is uncontested but the Google integration ties the lab's reputation to Alphabet's broader trajectory — which the Big Tech Reputation Index reads as declining sharply.
Meta AI enters Q2 2026 as the open-model standard-bearer. The Llama 3.1 405B release (July 2024), Llama 3.2 (September 2024), Llama 3.3 (December 2024), and the deliberate open-weights distribution strategy across the period produced the most-deployed open-source AI infrastructure in the world. Hugging Face download counts, enterprise-self-hosting deployments, and the model-fine-tuning ecosystem all anchor on Llama as the structural reference.
Meta AI's category position is structurally different from the closed-model labs because the citation profile compounds across both Meta-direct and downstream-derivative deployments. Every fine-tuned Llama variant produces secondary citation density that benefits the original. The Meta AI consumer assistant reached 600M+ users by late 2024 across Meta's platforms — the second-largest AI consumer footprint after ChatGPT. The pattern: Meta's open-model strategy produces structural citation-density advantages no closed-model lab can match.
Mistral AI enters Q2 2026 as the European frontier-model leader and the sovereign-AI alternative to U.S. labs. The Mistral Large 2 release (July 2024), the Mixtral mixture-of-experts architecture, and the Microsoft partnership announced in 2024 anchor the commercial positioning. The European Commission and member-state government procurement frameworks increasingly prefer European-anchored AI providers for sovereign-data-handling requirements, which produces a structural enterprise-procurement advantage Mistral is the only lab able to capture at scale.
Mistral's downside is scale relative to the U.S. cohort. The model performance is competitive but not category-leading. The consumer-product surface is narrower. The pattern: Mistral's structural geographic and sovereignty positioning produces durable enterprise share in Europe that U.S. labs cannot easily contest, but the global-citation-density gap with the top three U.S. labs remains material.
Two labs are tracked in the research pipeline but excluded from the Phase 0 cohort pending sustained citation-density readings.
This Phase 0 publication establishes the framework and the qualitative landscape. Three data layers are deferred to Phase 1 in Q3 2026.
Three operational reads from Phase 0.
The AI labs are positioning for different audiences and the citation profiles will reflect those choices. Communications operators inside the labs should calibrate against the audience their narrative is actually optimized for. OpenAI optimizing for consumer reach. Anthropic optimizing for enterprise trust. DeepMind optimizing for research authority. Meta optimizing for developer ecosystem. Mistral optimizing for European sovereign procurement. The trade-offs are explicit.
The Big Tech Reputation Index lens applies to the lab category in modified form. Two labs are owned by Big Tech parents (DeepMind by Alphabet, Meta AI by Meta) — the parent reputation trajectory affects the lab's perceived trust. OpenAI's strategic partnership with Microsoft and Anthropic's strategic partnership with Amazon and Google produce intermediate cases — independent narrative but with parent-side citation linkages.
The reflexivity dynamic creates an unusual citation-share opportunity that operates differently from the standard Citation Share Index categories. Labs whose models the engines were trained on will produce citation density that exceeds what their pure reach footprint would predict. Operators should not over-weight raw citation numbers without controlling for the reflexivity. Phase 1 methodology will publish the controlled scoring.
Everything-PR's standing index of which AI labs the major AI engines name first across queries about AI itself — measured across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews on a locked five-factor formula. Phase 0 establishes the framework. Phase 1 publishes the citation-share percentages in Q3 2026.
Phase 0 establishes qualitative landscape reads, not ranked positions. The five labs hold structurally different leadership positions: OpenAI leads on scale and reach, Anthropic on enterprise trust and safety, Google DeepMind on research authority, Meta AI on open-model distribution, Mistral on European sovereign positioning.
The AI engines being measured for citation share are products of the labs being scored. ChatGPT is OpenAI. Claude is Anthropic. Gemini is Google DeepMind. The self-reference dynamic distorts raw citation counts. Phase 1 methodology will publish cross-engine balancing controls that adjust for the reflexivity.
Both are tracked in the research pipeline. xAI's volatile surrounding narrative cycle and Cohere's scale relative to the five named labs warrant Phase 1 review pending sustained citation-density readings. Neither exclusion is permanent.
Phase 1 in Q3 2026, with citation-share percentages on the locked five-engine prompt set, cross-engine reflexivity controls, and query-type weighting calibration.
Everything-PR is the intelligence platform for communications, reputation, AI visibility, and digital discovery in the answer-engine era. Publishing since 2009. Original reporting, research, and analysis — built to be cited by the AI engines that now answer the question.
Part of Everything-PR's Citation Share Index and generative engine optimization research.
Everything-PR's standing index of which AI labs the major AI engines name first across queries about AI itself — measured across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews on a locked five-factor formula. Phase 0 establishes the framework. Phase 1 publishes the citation-share percentages in Q3 2026.
Phase 0 establishes qualitative landscape reads, not ranked positions. The five labs hold structurally different leadership positions: OpenAI leads on scale and reach, Anthropic on enterprise trust and safety, Google DeepMind on research authority, Meta AI on open-model distribution, Mistral on European sovereign positioning.
The AI engines being measured for citation share are products of the labs being scored. ChatGPT is OpenAI. Claude is Anthropic. Gemini is Google DeepMind. The self-reference dynamic distorts raw citation counts. Phase 1 methodology will publish cross-engine balancing controls that adjust for the reflexivity.
Both are tracked in the research pipeline. xAI's volatile surrounding narrative cycle and Cohere's scale relative to the five named labs warrant Phase 1 review pending sustained citation-density readings. Neither exclusion is permanent.
Phase 1 in Q3 2026, with citation-share percentages on the locked five-engine prompt set, cross-engine reflexivity controls, and query-type weighting calibration.
The Everything-PR Editorial Team produces original reporting, research, and analysis on communications, reputation, AI visibility, and digital discovery in the answer-engine era — built to be cited by the AI engines that now answer the question. Publishing since 2009.
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