Answer Capsule
Surfer SEO is a good fit for AI SEO Tools for Content Gap Analysis when the buyer wants competitor-led topical and on-page gap discovery connected directly to content briefs, optimization, audits, and production, with an emerging AI-answer visibility layer. Six of the seven included platforms named Surfer SEO during the ranking stage, and five of six fit assessments rated it good or strong, with one mixed. The strongest reason to consider it is the documented workflow from Topical Map and Content Editor gap findings into drafting and updating content. The main limitation is that its AI-answer tracking covers a narrow set of engines and does not replace dedicated AI-search intelligence, technical SEO, or backlink analysis.
Research Snapshot
| Field | Value |
|---|---|
| Platform mentions in ranking stage | 6 of 7 included platforms |
| Share of included platform responses | 85.7% |
| Average listed rank | 3.83 |
| Best listed rank | 2 |
| Relevant product/model/plan | Surfer Content Editor, Topical Map, Content Audit, and AI Tracker; evaluate Essential or Scale only after confirming current feature access and pricing |
| Overall use-case fit | Good |
| Research date | 2026-09-18 |
Why Surfer SEO Qualified for This Study
Questions This Section Answers
- Is Surfer SEO a good choice for AI SEO Tools for Content Gap Analysis?
- What makes Surfer SEO relevant for finding competitor content gaps in 2026?
Surfer SEO qualified because multiple platforms independently described it as a content-gap and content-optimization system rather than a generic SEO suite. Six of the seven included platforms named it during ranking discovery, and it appeared at an average listed rank of 3.83 with a best rank of 2. Five of the six platforms that returned a usable fit assessment rated the fit good or strong; one rated it mixed.
The qualification rests on documented capability, not on consensus alone. Surfer's own documentation describes Topical Map as a competitor-analysis workflow for finding topic coverage gaps and selecting opportunities, with Google Search Console connection required for the described workflow [1]. Independent reviews describe Surfer as excelling at content gap analysis and topic cluster planning [2], and its SERP analyzer as revealing gaps when top competitors cover a subtopic the buyer's page does not [3].
Surfer also qualified because its gap findings connect to execution. The platform links competitor and SERP analysis to content briefs, on-page optimization, audits, and AI-assisted production, which is the workflow the study's use case describes [5]. Platform agreement here reflects repeated description of the same product workflow, not proof that the tool improves rankings, citations, traffic, or revenue.
The Product, Model, Plan, or Service Most Relevant to AI SEO Tools for Content Gap Analysis
Questions This Section Answers
- Which Surfer SEO plan should a buyer choose for competitor content gap analysis?
- Is Surfer AI Tracker included in the Surfer SEO plan a buyer needs for AI-answer gap analysis?
The relevant Surfer SEO surface for this use case is the combination of Content Editor, Topical Map, Content Audit, and AI Tracker, evaluated on the Essential or Scale plan only after confirming current feature access and pricing [7]. Platforms named different plan labels for the same capability set, which is itself a buying signal.
Platforms most often pointed to Scale or Pro as the tier where the fuller gap-analysis stack lives. One platform described AI Tracker as included with Scale at five prompts and available as a paid upgrade on other plans [8]. Another described advanced gap features such as Coverage Gap as sitting in a Pro tier [9]. A third recommended the Scale plan with AI Tracker, Content Editor, Topical Map, and Coverage Booster, with Essential positioned for basic content optimization [10].
The capability set that matters for this use case includes:
- Topical Map for comparing competitor topic coverage and selecting opportunities [11].
- Content Editor for comparing a page against top-ranking competitors and flagging missing terms and entities [14].
- Content Audit for finding quick-win refreshes and improvement candidates [16].
- AI Tracker and Mention Gap for identifying AI answers where competitors appear and the buyer's brand does not [18].
What the AI Platforms Agreed About
Questions This Section Answers
- What do AI platforms agree Surfer SEO does well for content gap analysis?
- Does Surfer SEO connect content gap findings to actual content creation?
Platforms broadly agreed on three points: Surfer identifies topical and on-page gaps against competitors, it connects those findings to content production, and it adds a limited AI-answer visibility layer.
On gap discovery, Surfer's Topical Map is documented as comparing competitor topic coverage, identifying where competitors are weak, and selecting topics or keywords for new content [21]. Independent reviews describe Topical Map as clustering keywords by SERP similarity to expose pillar opportunities and coverage gaps [22], and as showing what competitors cover, where they are strong, and where they have dropped the ball [23].
On competitor benchmarking, the SERP analyzer benchmarks word count, heading structure, and NLP terms competitors use [25], and one review described it as compressing roughly two hours of manual competitive analysis into about ten minutes [27]. That time-saving figure is a platform-reported review claim, not an independently verified measurement.
On AI-answer gaps, Surfer's Mention Gap identifies prompts or AI answers where competitors are mentioned while the buyer's brand is absent, with sentiment analysis for how sources frame the brand [28]. Independent reviews describe AI Tracker metrics including Visibility Score, Share of Voice, Mention Gap, Sentiment Analysis, and Top Sources [29], and note that Mention Gap surfaces topics where competitors are cited but the user is not [30].
On actionability, platforms agreed that findings feed directly into drafting and optimization. Content Editor uses ranking-page analysis to provide optimization recommendations and connect research to content creation [31], and Auto-Optimize can apply gap-filling changes such as adding missing entities and facts [32]. An April 2026 update reportedly added a direct optimize-from-tracker button that jumps a gap into Content Editor [34].
Where the AI Platforms Disagreed or Were Uncertain
Questions This Section Answers
- How reliable is Surfer SEO AI Tracker for measuring AI-answer visibility gaps?
- Which AI engines does Surfer SEO fail to track for content gap analysis?
The clearest disagreement was about AI-answer coverage. One platform described AI Tracker as supporting visibility analysis across ChatGPT, Perplexity, Google AI Mode, Google AI Overview, and Google Gemini, with Visibility Score, Share of Voice, Mention Gap, sentiment, exports, and daily refreshes [35]. Independent reviews countered that Claude, Copilot, Grok, Meta AI, and DeepSeek are not tracked at all, calling this a large gap if the audience uses anything beyond ChatGPT, Perplexity, or Google [36]. One platform went further, stating that Surfer does not appear to offer native analysis across ten or more AI platforms or specific LLM citation tracking [39].
Accuracy and methodology were also contested. Independent reviews described AI Tracker as providing directional insights while raising questions about accuracy and snapshot-based methodology [40]. One review noted the tool cannot retroactively show how a brand performed in AI answers months ago, because data builds only from the moment prompts are added [42].
Pricing and plan naming produced the widest spread. The ranking-stage recommendation listed Essential at $89/month billed annually and Scale at $175/month billed annually [43], while other sources reported Essential at $99/month or $79/month annual and Scale at $219/month or $175/month annual [44]. One review stated that Surfer renamed plans in 2026 and that Essential at $89 and Scale at $129 no longer exist [46]. Surfer's own pricing page shows monthly amounts that appear around $82 and $182 without fully exposing plan labels in the retrieved excerpt [47]. One platform rated pricing confidence low and another rated it high, which reflects the underlying inconsistency rather than a settled answer [48].
Two further uncertainties matter for this use case. First, it is unclear whether AI Tracker is bundled into higher plans or sold primarily as a separate add-on in all cases [49]. Second, non-English accuracy is disputed: Surfer officially supports NLP analysis and Facts in 15+ languages [51], but agencies working with Spanish and German sites reported grammar issues and less accurate term suggestions during audits [52].
Use-Case-Specific Features and Capabilities
Questions This Section Answers
- Does Surfer SEO prioritize content gaps by business value or only by content score?
- Can Surfer SEO export AI-answer gap data for reporting and analysis?
For content-gap analysis specifically, Surfer's capabilities split into four areas: topical gap discovery, on-page gap analysis, AI-answer gap analysis, and prioritization.
Topical gap discovery runs through Topical Map, which is documented as comparing competitor topic coverage and selecting opportunities, with Google Search Console connection required for the described workflow [53]. Independent reviews describe Topical Map as prioritizing pages with the best ranking opportunities using easy-to-digest visuals [54] and as providing an actionable list of best next steps weekly based on SERP and domain performance [55].
On-page gap analysis runs through Content Editor and Content Audit. Content Editor compares the buyer's page against top-ranking competitor pages and highlights missing or incomplete terms, entities, and recommended word counts [56]. Auto-Optimize analyzes content against competitors to boost Content Score by adding relevant terms and missing sections [57]. Content Audit is positioned to suggest articles with the best quick-win potential to refresh [58].
AI-answer gap analysis runs through AI Tracker and Mention Gap. Mention Gap identifies AI answers where competitors are mentioned and the buyer's brand is absent, with sentiment analysis [59]. AI Tracker is documented with Visibility Score, Share of Voice, Mention Gap, sentiment, exports, and daily refreshes [60]. One platform noted the standalone AI Search Analytics documentation lists $82/month annually for 50 daily prompts, $158/month annually for 100, $308/month annually for 200, and custom pricing for unlimited prompts [60].
Prioritization is the weakest documented area. Surfer provides topic, keyword, content-score, and visibility indicators, but the reviewed evidence does not establish a robust, universal prioritization model combining business value, traffic potential, conversion impact, authority, and AI-answer opportunity across all channels [60]. One platform described prioritization as largely tied to on-page optimization scores rather than a multi-factor AI-driven model [56]. Another described Topical Map as ranking gaps by coverage lift and search volume [62]. Buyers should treat prioritization as indicator-based rather than validated business-impact scoring.
Pricing, Fees, Contracts, and Ongoing Costs
Questions This Section Answers
- How much does Surfer SEO cost per month for content gap analysis, and are there add-on fees?
- What is Surfer SEO's cancellation and refund policy for annual plans?
Pricing is the least settled part of this evaluation. The ranking-stage recommendation listed Essential at $89/month billed annually and Scale at $175/month billed annually [63]. Independent reviews reported Essential at $99/month or $79/month annual and Scale at $219/month or $175/month annual [64]. One review stated that Surfer renamed plans in 2026 and that Essential at $89 and Scale at $129 no longer exist [66]. Surfer's pricing page shows monthly amounts that appear around $82 and $182 in the retrieved excerpt [67]. These figures conflict and should be verified at checkout.
Known cost components reported across platforms:
| Cost item | Reported figure | Source |
|---|---|---|
| Essential / Standard | $99/month, or $79/month annual | |
| Scale / Pro | $219/month, or $175/month annual | |
| Peace of Mind | $299/month | |
| Enterprise | $999/month minimum | |
| AI Tracker add-on | $95/month for 25 prompts | |
| AI Search Analytics standalone | $82/month annual for 50 daily prompts | |
| SERP Analyzer add-on | $29/month on Essential | |
| Additional AI articles | $29 per article, or about $15 with bulk packages | |
| Rank Tracker | $17/month for 200 keywords |
Annual billing discounts are reported at up to 17% versus monthly [68], with one platform describing 20–25% [64]. One independent review estimated that total cost with SERP Analyzer and AI Tracker add-ons approaches or exceeds $200/month [69].
Contract terms are partially documented. Surfer documentation describes a 7-day trial with access to selected features [68]. One platform stated the trial converts to the selected subscription unless canceled before it ends, and that the pricing page states a 7-day refund policy for monthly Essential or Scale subscriptions, with eligibility for annual plans and add-ons requiring confirmation [68]. Another platform stated the 7-day money-back guarantee covers base subscription plans only and does not cover add-ons, usage overages, or renewals [70]. Surfer's pricing page states that annual plans are charged for the entire year upfront and that credits reset yearly on annual plans (official:C2). One platform noted that Surfer no longer offers free trials [64], which conflicts with the documented 7-day trial and should be verified.
Best Suited For
Questions This Section Answers
- Who gets the most value from Surfer SEO for content gap analysis?
- Is Surfer SEO worth it for a content team publishing ten or more articles per month?
Surfer SEO is best suited to content teams that need to identify missing topics, subtopics, entities, and competitor coverage before creating or updating pages [71]. It fits organizations that want one workflow from SERP and competitor analysis through content briefs, optimization, audits, and AI-visibility monitoring [72], and buyers prioritizing Google-oriented content gap analysis with an emerging AI-search visibility layer [71].
Platforms converged on mid-market content teams and agencies producing at least ten articles monthly, with SERP-driven gap analysis and on-page optimization needs [75]. One platform described Surfer as popular with content teams, freelance writers, and SEO agencies needing a structured optimization workflow [75]. Another positioned it for companies optimizing for both traditional search and AI search visibility across ChatGPT, Perplexity, Google AI Overviews, and Gemini [77].
The strongest fit is where gap findings must translate immediately into a draft, optimization task, audit, or content update [72]. Buyers who need that continuity, and who accept that AI-answer coverage is a supplementary layer rather than a complete measurement system, are the best match.
Probably Not Best Suited For
Questions This Section Answers
- Who should not choose Surfer SEO for AI SEO Tools for Content Gap Analysis?
- Is Surfer SEO a poor fit for teams that need backlink or technical SEO gap analysis?
Surfer SEO is probably not the best fit for enterprise buyers requiring a mature, dedicated AI-search intelligence platform with broad model, language, geography, citation, and recommendation analytics [78]. It is also a weak fit for teams needing a complete SEO suite with deep technical crawling, backlink analysis, and comprehensive rank tracking included [79].
Independent reviews stated that Surfer has no technical SEO features, zero support for site audits, crawl analysis, and page speed diagnostics [80], and no backlink analysis or insight into backlink profiles and link-building opportunities [81]. One review noted no backlink analysis, no technical audit, and no rank tracking in base plans, with keyword research returning far fewer results than Ahrefs or Semrush [82].
Other poor-fit situations reported by platforms:
- Organizations publishing fewer than four articles monthly, where per-article cost becomes prohibitive [83].
- Teams whose audience relies heavily on Claude, Copilot, Grok, DeepSeek, or Meta AI, which Surfer does not track [84].
- Brands needing long-term historical AI visibility data, since Mention Gap captures prospectively from setup date [86].
- Buyers seeking a fully automated system that independently discovers, scores, and prioritizes all content opportunities without substantial human review [78].
- Teams that need claim-level auditing of AI-generated answers for accuracy or source strength [87].
When Another Option May Be Better
Questions This Section Answers
- What is a better alternative to Surfer SEO for broad AI-search visibility monitoring?
- When should a buyer choose Ahrefs, Semrush, or MarketMuse instead of Surfer SEO?
Another option may be better in five recurring situations that platforms described.
First, when the primary requirement is broad monitoring of AI answers, citation sources, competitor mentions, prompt portfolios, languages, locations, and model-level reporting rather than content production, a dedicated AI-search visibility platform is the better choice [88]. One platform specifically recommended WriteWorks for citation-gap scoring across ten or more AI platforms and Pressfit.ai for category-level visibility into which domains AI models cite [89].
Second, when backlink intelligence, keyword-level competitor research, technical SEO, and broader domain-level content-gap comparisons are equally important, Ahrefs or Semrush is the better fit, with Ahrefs independently described as offering competitor content-gap analysis and broader SEO capabilities [88].
Third, when the buyer prioritizes advanced topic modeling, content briefs, cluster planning, and competitive gap analysis over integrated AI-answer monitoring, MarketMuse is the recommended alternative [88].
Fourth, when rank tracking, site auditing, backlinks, competitor research, and content optimization must be bundled, SE Ranking or another full-stack SEO platform is the better choice [88].
Fifth, when the buyer needs to audit why Google AI Overviews chose specific competitors, or needs claim-strength analysis and correction of AI-generated misinformation, the LLM Gap Analyzer is the recommended alternative [93]. For very constrained budgets, one platform suggested Frase as a more budget-friendly alternative for lighter content optimization [94].
Questions to Verify Before Buying
Questions This Section Answers
- What should a buyer confirm with Surfer SEO before signing an annual contract?
- Which Surfer SEO plan includes AI Tracker, and what are the prompt limits?
The following questions come directly from platform-reported verification lists and should be resolved before purchase.
- What exact features and usage limits are included in Essential and Scale for a United States account on the purchase date [95]?
- Is AI Tracker included, an add-on, or a separate AI Search Analytics subscription for the selected plan [95]?
- Does Coverage Booster exist in the selected plan, and what are its monthly limits and output types [95]?
- Which AI models, search experiences, languages, countries, locations, and recommendation platforms can be tracked today [95]?
- Are prompts user-defined, Surfer-generated, or both, and how are prompt volume and refresh limits calculated [95]?
- Does Mention Gap identify missing brand mentions, missing citations, missing topics, or all three [99]?
- How are content-gap opportunities prioritized, and can the scoring incorporate traffic, conversions, business value, authority, or first-party data [95]?
- Can the buyer export raw prompt results, cited URLs, competitor comparisons, historical data, and audit results through an API or CSV [95]?
- What happens to unused credits, tracked prompts, projects, and historical data after cancellation or plan downgrade [95]?
- What are the exact annual commitment, auto-renewal, cancellation, refund, seat, workspace, and overage terms [95]?
- Does the 7-day money-back guarantee align with the buyer's procurement process, given that one platform states Surfer no longer offers free trials [102]?
- If the buyer relies on Surfer AI drafts, is there capacity to budget 30–60 minutes per article for editorial review and fact-checking [103]?
Final AI Consensus Verdict
Surfer SEO is a good fit for AI SEO Tools for Content Gap Analysis when the buyer's priority is competitor-led topical and on-page gap discovery that flows directly into briefs, optimization, audits, and content production, with an initial AI-answer visibility and competitor-mention layer attached. Six of seven included platforms named it during ranking discovery, and five of six fit assessments rated it good or strong, with one mixed.
The strongest reason to consider it is the documented continuity from gap finding to content execution [104]. The main limitation is that its AI-answer tracking covers a narrow engine set and does not replace dedicated AI-search intelligence, technical SEO, or backlink analysis [107].
Purchase should be contingent on verifying current plan packaging, AI Tracker inclusion, model and language coverage, prompt limits, and checkout pricing, because public pricing and plan names conflict across sources [110]. Buyers who need broad, independent AI-search measurement or a complete SEO suite should plan to pair Surfer with a complementary platform rather than rely on it alone.
How This Review Was Produced
This review was produced from a seven-platform research run dated 2026-09-18, using the supplied platform fit-research responses, ranking statistics, and citation catalog. Each platform returned a fit assessment, strengths, limitations, pricing and terms, and questions to verify before buying. The article preserves platform-reported claims as platform-reported and does not present them as independently verified facts. Company-owned documentation is distinguished from independent reviews throughout. No personal testing, customer experience, or independent verification was performed at the writing stage.
Methodology Limitations
Six of the seven included platforms returned a usable fit assessment, so the fit findings should not be described as unanimous. Platform mentions in the ranking stage count only platforms that named the entity during ranking discovery, which is a different measure from fit assessment.
Platform-reported research dates differ from the authoritative run date. DeepSeek reported a research date of 2026-06-11, while the other platforms reported 2026-09-18. Platform-reported dates are provenance metadata and do not independently prove freshness.
The supplied URLs were collected from platform responses and were not independently validated by the writing stage. Citations are platform-reported evidence, not independently verified facts. Claims from platforms without retrieved citations are labeled platform-reported or unverified.
Conflicting product names, pricing, and capabilities were not resolved by guessing. Where sources disagreed, the conflict is described and buyers are directed to verify. Missing pricing, unclear plan inclusions, and undocumented coverage breadth are disclosed rather than filled in. No controlled evidence was supplied showing that Surfer improves rankings, AI citations, recommendations, traffic, or revenue.
Explore more ai seo content optimization guidance in the category directory.
Sources
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- AI research evidence record deepseek:c1
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- AI research evidence record perplexity:8
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- AI research evidence record anthropic:27-2
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- AI research evidence record anthropic:6-6
- AI research evidence record anthropic:6-7
- AI research evidence record anthropic:5-6
- AI research evidence record openai:c4
- AI research evidence record anthropic:10-10
- AI research evidence record anthropic:4-8
- AI research evidence record openai:c2
- AI research evidence record anthropic:7-6
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- AI research evidence record anthropic:10-1
- AI research evidence record openai:c1
- AI research evidence record anthropic:30-2
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- AI research evidence record anthropic:34-4
- AI research evidence record kimi:writeworks-features
- AI research evidence record anthropic:18-13
- AI research evidence record anthropic:37-7
- AI research evidence record anthropic:33-5
- AI research evidence record deepseek:c4
- AI research evidence record anthropic:12-2
- AI research evidence record anthropic:12-11
- AI research evidence record anthropic:15-2
- AI research evidence record perplexity:2
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- AI research evidence record anthropic:16-3
- AI research evidence record anthropic:12-2
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Additional AI research evidence112 records
- AI research evidence record openai:c3
- AI research evidence record anthropic:2-4
- AI research evidence record anthropic:5-4
- AI research evidence record anthropic:5-5
- AI research evidence record openai:c2
- AI research evidence record openai:c5
- AI research evidence record openai:c1
- AI research evidence record perplexity:13
- AI research evidence record grok:web:3
- AI research evidence record kimi:surfer-indirect
- AI research evidence record openai:c3
- AI research evidence record anthropic:27-2
- AI research evidence record anthropic:27-4
- AI research evidence record deepseek:c1
- AI research evidence record anthropic:22-17
- AI research evidence record perplexity:8
- AI research evidence record perplexity:9
- AI research evidence record openai:c4
- AI research evidence record anthropic:4-2
- AI research evidence record anthropic:4-8
- AI research evidence record openai:c3
- AI research evidence record anthropic:24-5
- AI research evidence record anthropic:27-2
- AI research evidence record anthropic:27-4
- AI research evidence record anthropic:6-6
- AI research evidence record anthropic:6-7
- AI research evidence record anthropic:5-6
- AI research evidence record openai:c4
- AI research evidence record anthropic:10-10
- AI research evidence record anthropic:4-8
- AI research evidence record openai:c2
- AI research evidence record anthropic:7-6
- AI research evidence record anthropic:22-17
- AI research evidence record anthropic:10-1
- AI research evidence record openai:c1
- AI research evidence record anthropic:30-2
- AI research evidence record anthropic:30-13
- AI research evidence record anthropic:34-4
- AI research evidence record kimi:writeworks-features
- AI research evidence record anthropic:18-13
- AI research evidence record anthropic:37-7
- AI research evidence record anthropic:33-5
- AI research evidence record deepseek:c4
- AI research evidence record anthropic:12-2
- AI research evidence record anthropic:12-11
- AI research evidence record anthropic:15-2
- AI research evidence record perplexity:2
- AI research evidence record perplexity:1
- AI research evidence record perplexity:13
- AI research evidence record perplexity:15
- AI research evidence record anthropic:4-14
- AI research evidence record anthropic:31-8
- AI research evidence record openai:c3
- AI research evidence record anthropic:23-11
- AI research evidence record anthropic:26-6
- AI research evidence record deepseek:c1
- AI research evidence record anthropic:22-17
- AI research evidence record perplexity:9
- AI research evidence record openai:c4
- AI research evidence record openai:c1
- AI research evidence record openai:c5
- AI research evidence record anthropic:24-5
- AI research evidence record deepseek:c4
- AI research evidence record anthropic:12-2
- AI research evidence record anthropic:12-11
- AI research evidence record anthropic:15-2
- AI research evidence record perplexity:2
- AI research evidence record openai:c7
- AI research evidence record anthropic:36-5
- AI research evidence record anthropic:16-3
- AI research evidence record openai:c1
- AI research evidence record openai:c2
- AI research evidence record openai:c5
- AI research evidence record openai:c4
- AI research evidence record anthropic:24-4
- AI research evidence record anthropic:2-4
- AI research evidence record anthropic:10-10
- AI research evidence record openai:c1
- AI research evidence record openai:c5
- AI research evidence record anthropic:29-8
- AI research evidence record anthropic:29-9
- AI research evidence record anthropic:36-6
- AI research evidence record anthropic:12-2
- AI research evidence record anthropic:30-2
- AI research evidence record anthropic:34-4
- AI research evidence record anthropic:33-5
- AI research evidence record kimi:semrush-llm-gap
- AI research evidence record openai:c1
- AI research evidence record kimi:writeworks-features
- AI research evidence record kimi:pressfit-ai
- AI research evidence record anthropic:29-9
- AI research evidence record anthropic:36-6
- AI research evidence record kimi:semrush-llm-gap
- AI research evidence record anthropic:12-2
- AI research evidence record openai:c1
- AI research evidence record perplexity:13
- AI research evidence record perplexity:15
- AI research evidence record anthropic:30-2
- AI research evidence record openai:c4
- AI research evidence record deepseek:c1
- AI research evidence record anthropic:16-3
- AI research evidence record anthropic:12-2
- AI research evidence record anthropic:36-7
- AI research evidence record openai:c2
- AI research evidence record openai:c5
- AI research evidence record anthropic:10-1
- AI research evidence record anthropic:30-2
- AI research evidence record anthropic:29-8
- AI research evidence record anthropic:29-9
- AI research evidence record openai:c1
- AI research evidence record anthropic:15-2
- AI research evidence record perplexity:2
Verify this research
Review the study details behind this page or download the public machine-readable verification record.
- Study date
- September 18, 2026
- Platforms analyzed
- 7
- Source records
- 41
- Ranking mentions
- 6 of 7
- Platform share
- 86%
- Final consensus rank
- #4
Research trail and source mix
Configured platforms
openai, anthropic, deepseek, grok, perplexity, kimi, google
Source mix
23 independent · 18 company-owned
Evidence support
34 direct · 7 partial
Important limitation
Use the run research_date as the study date. Platform-reported dates are provenance metadata and do not independently prove freshness.
Source snapshot SHA-256 30f9997f60d4ae32bac6c480ecd8b5f66caabee07420ebb774c79373bf26e3fa