ChatGPT vs Perplexity vs Gemini for crypto citations: 8 weeks of test data
We ran 2,400 crypto-related prompts across ChatGPT, Perplexity and Gemini over 8 weeks. Each engine cites different sources at different rates with different bias. Here is the full breakdown, why it matters and where to focus first.
The test methodology
We selected 80 prompts across 30 crypto verticals (DeFi, wallets, exchanges, L1, L2, NFT, DePIN, restaking, stablecoins, derivatives and others). Each prompt was run through ChatGPT, Perplexity and Gemini once per week for 8 weeks (March 19 to May 14, 2026). That gave us 2,400 total responses per engine.
We recorded: every URL cited, every domain inferred (where the engine named a project without linking), the position of each citation in the response, and the consistency week-over-week.
No incentive bias. We did not interact with any of the projects mentioned. We did not buy ads on these engines. We did not warm up accounts. This is observed behavior, not enginnered behavior.
ChatGPT: brand-dominant
ChatGPT is the most brand-conservative of the three. It defaults to incumbents and named market leaders. For "best crypto wallet" the same 4 wallets (MetaMask, Phantom, Coinbase Wallet, Trust Wallet) appear in 91% of responses. Newer wallets break in only when the prompt includes specific features (account abstraction, hardware integration, Solana-native).
Source distribution: 34% from project domains directly. 22% from CoinGecko or CoinMarketCap. 18% from CoinDesk, Decrypt, The Block, Cointelegraph. 9% from Wikipedia. 17% from a long tail of crypto-focused sites.
What works for ChatGPT inclusion: clear brand entity (Organization schema, sameAs fields linking to Wikipedia and CoinGecko), explicit category claims in the homepage H1, audit reports linked from the homepage, time on market. New projects are heavily penalized. The 12-month rule is real.
Perplexity: community-weighted
Perplexity is the most community-driven. Reddit alone accounts for 47% of source slots across our test set. YouTube videos add another 14%. The remaining 39% is split across crypto-native domains.
Source distribution within the 39%: CoinGecko 11%, CoinMarketCap 6%, project domains 9%, news (Decrypt, The Block, Cointelegraph, CoinDesk) 7%, long tail 6%.
What works: Reddit presence (a subreddit with 500+ subscribers and weekly activity), YouTube channel even at modest scale, FAQ-formatted content on the project domain, CoinGecko and CoinMarketCap listings, recent freshness signals (dateModified updates). Perplexity penalizes static content harder than ChatGPT does.
Gemini: SEO-aligned
Gemini behaves closest to traditional Google search. Source distribution mirrors Google SERP top 10 for the same queries about 78% of the time. Strong SEO directly translates to Gemini citation. Weak SEO directly blocks Gemini citation.
Specific patterns: Gemini cites EXACTLY the URL that ranks #1-3 for the underlying query. AI Overviews sources are the same selection. For crypto verticals where Google's top 10 is dominated by aggregator sites (CoinGecko, CoinMarketCap, DefiLlama), those dominate Gemini too.
What works: classic SEO. Backlinks. Technical SEO. Content depth. Domain authority. Crypto-native sites with strong SEO foundations dominate Gemini. Marketing-only sites with weak SEO do not appear regardless of product quality.
Cross-engine consistency
For 18 of our 30 verticals the top 3 cited sources were the same across all 3 engines. The dominant entity wins everywhere. Beneath that, each engine diverges.
Projects ranked #4-#10 in a category have very different citation rates across engines. A project might be in 60% of ChatGPT responses, 20% of Perplexity, 5% of Gemini, or any other distribution. The variance is high and the variance is the opportunity. Projects can earn outsize visibility on one engine while invisible on the others.
Practical implication: do not pursue all three engines with the same content strategy. Different engines respond to different signals. Pick one as your primary target based on your category dynamics.
Where to focus first
For new projects: Perplexity. Lower brand-conservatism barrier. Community work compounds. Reddit and YouTube investment pays off in 30 to 60 days.
For established projects with weak AI presence: ChatGPT. The schema and entity work to fix this also lifts Google rankings. Two-for-one.
For projects with strong existing SEO: Gemini will improve automatically as Google rankings hold. No special work needed. Audit for AI Overviews-specific patterns (answer modules, FAQ schema) and ship those.
For most projects: pick one, invest 90 days, measure, then add the next engine. Trying all three simultaneously dilutes effort and produces no learning.