The Community-Source Divide: Which AI Engines Cite Reddit and YouTube
In one week of XLR8 AI experiments, 16.0% of Google AI Mode answers cited Reddit or YouTube. For Claude Sonnet 5 the figure was 0.02%, and for GPT-6.1 Sol and Claude Opus 5.5 it was zero.
Headline finding:
Google AI Mode, Gemini and Grok cite Reddit or YouTube in 12.7–17.5% of answers; Claude Sonnet 5, Claude Opus 5.5, GPT-6.1 Sol, GPT-5.6 Luna and Sonar cite them in 0–0.4%.
On matched queries from the same 22 organisations, Google AI Mode cited more Reddit/YouTube than Claude Sonnet 5 in 22 of 22 (16.0% vs 0.02% of answers; gap 15.8 points, 95% bootstrap CI 14.9–17.2).
If community platforms are part of your visibility strategy, the engine you are optimising for decides whether they matter at all.
What we measured
We took every visibility experiment result written between 12 Oct 2026 08:06 UTC and 19 Oct 2026 05:35 UTC across all XLR8 AI organisations: 27,965 result rows, from 91 executions of 73 experiments in 27 organisations. We removed Microsoft Copilot (326 rows, none with citations) and kept the nine models with at least 1,489 answers each, leaving 24,598 answers and 4,007 distinct query strings.
For each answer we parsed the host of every cited URL. An answer counts as a community-source answer if at least one citation is on reddit.com, youtube.com or youtu.be. Client identities are omitted throughout; all figures are pooled.
The split by engine
The nine engines fall into two groups with almost nothing between them. Four engines cite Reddit or YouTube in roughly one answer in seven or eight. The other five cite them in fewer than one answer in 250.
Model | Answers | Orgs | Answers citing Reddit or YouTube | Reddit share of citations | YouTube share of citations |
|---|---|---|---|---|---|
Gemini 3.6 Flash | 3,044 | 6 | 17.5% | 1.85% | 1.68% |
Google AI Mode | 3,752 | 23 | 16.0% | 3.03% | 3.41% |
Grok 4.20 | 1,489 | 10 | 13.2% | 0.49% | 0.42% |
Gemini 3 Flash Preview | 1,745 | 13 | 12.7% | 1.02% | 1.67% |
Sonar | 3,090 | 17 | 0.39% | 0.04% | 0.01% |
GPT-5.6 Luna | 3,410 | 20 | 0.26% | 0.03% | 0.01% |
Claude Sonnet 5 | 4,992 | 23 | 0.02% | 0.00% | 0.00% |
Claude Opus 5.5 | 1,518 | 2 | 0.00% | 0.00% | 0.00% |
GPT-6.1 Sol | 1,558 | 3 | 0.00% | 0.00% | 0.00% |
Across the five low-citing engines there were 25 Reddit or YouTube citations in 14,568 answers combined. Across the four high-citing engines there were 2,361 in 10,030 answers (counting all Reddit and YouTube citations, not answers).
It is not just a different mix of clients
The engines were not tested on identical query sets, so a raw gap could simply reflect who happened to run what. To check, we compared Google AI Mode with Claude Sonnet 5 inside the 22 organisations that had both models in the window.
Google AI Mode cited Reddit or YouTube in a higher share of answers than Claude Sonnet 5 in all 22 of 22 organisations, with no ties. Google AI Mode's rate ranged from 0.6% to 59.3% by organisation, while Sonnet 5's ranged from 0% to 0.3%. On the 3,345 query strings that both models answered for the same organisation, Google AI Mode averaged 0.23 Reddit or YouTube citations per query and Sonnet 5 averaged 0.00.
The size of the Google effect varies enormously by organisation, from 0.6% to 59.3% of answers. Two organisations stand out at 59.3% (n=189) and 56.8% (n=88); 14 of the 23 sit below 20%.
Query wording does not explain the spread
It is tempting to assume recommendation-style queries ("best", "top", "vs", "alternatives") pull in community sources. They do, but only modestly. Across the four high-citing engines, 17.1% of recommendation or comparison answers (n=6,277) cited Reddit or YouTube, against 13.6% for how-to or question-style queries (n=1,421), 12.5% for other queries (n=2,223) and 5.5% for definitions (n=109, too few to rely on). Inside the 16 organisations with at least 30 answers in both groups, recommendation queries had the higher rate in 13, averaging 19.2% against 15.4%.
The organisation-level spread is a different matter. Among the 17 organisations with at least 50 Google AI Mode answers, the rank correlation between an organisation's share of recommendation-style queries and its Reddit/YouTube rate was 0.06, effectively none. One organisation whose queries were 93% recommendation-style saw 11.9%; another at 81% saw 3.1%; the top organisation, at 57%, saw 59.3%. We did not identify what drives the gap. Topic category is the obvious candidate and we have not tested it. Query types here were assigned by keyword matching, so treat the split as approximate.
Reddit and YouTube are not interchangeable
The four high-citing engines lean on the two platforms differently. Gemini 3.6 Flash cited Reddit in 11.7% of answers and YouTube in 8.7%. Google AI Mode was nearly even, at 9.0% and 9.2%. Gemini 3 Flash Preview leaned to YouTube, at 8.0% against 5.2%. Grok 4.20 was the most video-leaning, at 11.7% for YouTube against 2.3% for Reddit. Answers citing both platforms at once were rare, between 0.6% and 2.9% of answers for every engine.
For Grok, then, a YouTube presence matters roughly five times as often as a Reddit one, while for Gemini 3.6 Flash the order reverses.
What the low-citing engines cite instead
We grouped cited domains into a few recognisable types: review and analyst sites (G2, Capterra, Gartner and similar), reference sites, professional and social platforms, major publishers and government or education domains. For every engine, 93% to 98% of citations fell outside those groups, meaning vendor sites, niche publishers and other long-tail domains. The groups we could name were small. GPT-5.6 Luna had the highest government and education share at 4.9% of its citations, and GPT-6.1 Sol 2.9%. Review and analyst sites made up between 0.1% (GPT-6.1 Sol) and 3.3% (Grok 4.20) of citations. In short, Claude and GPT answers were not substituting another recognisable source type for Reddit; they were drawing on brand and publisher pages.
What this means for visibility work
Community presence is an engine-specific lever, not a general one. A well-ranked Reddit thread or YouTube video is a plausible way into Google AI Mode, Gemini and Grok answers, particularly for recommendation-style queries. For Claude and GPT in this sample it was effectively not a path at all, so earned-media and owned-content work will matter more there.
A second, smaller observation: Gemini 3.6 Flash returned no citations at all for 30.8% of its answers (938 of 3,044), and Claude Opus 5.5 for 26.2% (398 of 1,518), against 13.2% for Claude Sonnet 5 (657 of 4,992). A zero-citation answer cannot cite a community source, which partly shapes these rates.
In practice, this suggests splitting the work by engine:
For Google AI Mode, Gemini and Grok: audit where your category is discussed on Reddit and YouTube. Grok leans towards video (11.7% of answers cite YouTube against 2.3% Reddit); Gemini 3.6 Flash leans towards Reddit (11.7% against 8.7%). Check your own query set first, since organisation rates ranged from 0.6% to 59.3%.
For Claude, GPT and Sonar: community platforms were almost never cited, so earned coverage, owned pages and third-party publisher or review-site mentions are the realistic routes in.
For measurement: report visibility per engine rather than as one blended score. A blended number would hide a gap this large.
Frequently asked questions
Which AI engines cite Reddit the most? In this sample, Gemini 3.6 Flash (11.7% of answers) and Google AI Mode (9.0%). Gemini 3 Flash Preview cited Reddit in 5.2% and Grok 4.20 in 2.3%.
Do Claude and ChatGPT cite Reddit or YouTube? Rarely. Claude Sonnet 5 cited one YouTube link across 4,992 answers, Claude Opus 5.5 and GPT-6.1 Sol cited none, and GPT-5.6 Luna cited either platform in 0.26% of answers. The "ChatGPT" results here are from the GPT-5.6 Luna and GPT-6.1 Sol models, not the consumer ChatGPT interface.
Does a Reddit mention help brand visibility everywhere? Not on this evidence. It is a plausible route into four of the nine engines tested and close to irrelevant for the other five.
How large was the sample? 24,598 answers from nine models, 4,007 distinct query strings and 26 organisations, between 12 and 19 October 2026.
Limitations
This is observational data from one seven-day window, not a controlled test. Models were run on different organisations and query sets, with uneven coverage: Claude Opus 5.5 appears in only 2 organisations, GPT-6.1 Sol in 3 and Gemini 3.6 Flash in 6, so their rates are less certain than those for Google AI Mode and Claude Sonnet 5 (23 organisations each). The matched comparison is only Google AI Mode against Claude Sonnet 5; we did not run matched tests for the other pairs.
The results describe what each engine returned through the interface we query, not necessarily the model's own preference. Differences in search tooling, domain filtering or how citations are exposed could produce zero Reddit and YouTube citations without any model-level choice.
Domains were taken from URL hosts only; we did not classify page content, and other community sites (Quora, forums, Medium) are not counted. Query sets skew towards B2B software and professional services. Row counts reflect the database at query time (19 Oct 2026, 08:00 UTC) and can shift slightly as late results arrive.
Method
Source: visibility_experiment_results joined to experiment_executions and experiments, filtered to created_at in the window above. Fields used: citations, model_name, query and organisation. Bootstrap interval from 2,000 resamples of answer-level outcomes. All figures were computed in this analysis; none are taken from third parties.
