Meta (META)

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As of Oct 24, 2026, Kalshi and Polymarket have settled 188 word markets on Meta’s earnings calls since 2025, on 58 different words; most reliably said: “Cloud” (5 of 5). Next call: Jan 27, 2027 (15 words listed).

“Muse” on the Oct 21 call · 2:06 · said 91 times. Play the clip

Next: Earnings call ·

15 words listed · Occasion page

Who counts: Kalshi: company speakers + operator

Kalshi

Meta: the words listed for Wed, Jan 27, how often each was said on past occasions, and the probability for this one
WordQ4’24Jan '25Q1’25Apr '25Q2’25Jul '25Q3’25Oct '25Q4’25year agoQ1’26Apr '26Q2’26Jul '26Q3’26last callTrendLast 8ScriptedAll-timeProbabilityMarket
Threads8 times: Threads, Q4’24 Jan '25, counts as said7 times: Threads, Q1’25 Apr '25, counts as said6 times: Threads, Q2’25 Jul '25, counts as said10 times: Threads, Q3’25 Oct '25, counts as said4 times: Threads, Q4’25 Jan '26, counts as said3 times: Threads, Q1’26 Apr '26, counts as said3 times: Threads, Q2’26 Jul '26, counts as said4 times: Threads, Q3’26 Oct '26, counts as saidfalling8/8100%8/8100%18/5831%90%n=5+tx from settlement history blended with transcripts78¢ Kalshi
Muse3+ times0 times: Muse (3+ times), Q4’24 Jan '250 times: Muse (3+ times), Q1’25 Apr '250 times: Muse (3+ times), Q2’25 Jul '250 times: Muse (3+ times), Q3’25 Oct '250 times: Muse (3+ times), Q4’25 Jan '266 times: Muse (3+ times), Q1’26 Apr '26, counts as said15 times: Muse (3+ times), Q2’26 Jul '26, counts as said91 times: Muse (3+ times), Q3’26 Oct '26, counts as saidrising3/838%3/838%3/585%88%n=1+tx from settlement history blended with transcripts82¢ Kalshi
Cloud0 times: Cloud, Q4’24 Jan '250 times: Cloud, Q1’25 Apr '253 times: Cloud, Q2’25 Jul '25, counts as said4 times: Cloud, Q3’25 Oct '25, counts as said3 times: Cloud, Q4’25 Jan '26, counts as said3 times: Cloud, Q1’26 Apr '26, counts as said1 time: Cloud, Q2’26 Jul '26, counts as said1 time: Cloud, Q3’26 Oct '26, counts as saidrising6/875%6/875%13/5822%81%n=5+tx from settlement history blended with transcripts78¢ Kalshi
Advertising1 time: Advertising, Q4’24 Jan '25, counts as said8 times: Advertising, Q1’25 Apr '25, counts as said2 times: Advertising, Q2’25 Jul '25, counts as said3 times: Advertising, Q3’25 Oct '25, counts as said1 time: Advertising, Q4’25 Jan '26, counts as said0 times: Advertising, Q1’26 Apr '260 times: Advertising, Q2’26 Jul '265 times: Advertising, Q3’26 Oct '26, counts as saidfalling6/875%3/838%55/5895%76%n=5+tx from settlement history blended with transcripts66¢ Kalshi
VR / Virtual Reality0 times: VR / Virtual Reality, Q4’24 Jan '251 time: VR / Virtual Reality, Q1’25 Apr '25, counts as said0 times: VR / Virtual Reality, Q2’25 Jul '250 times: VR / Virtual Reality, Q3’25 Oct '252 times: VR / Virtual Reality, Q4’25 Jan '26, counts as said2 times: VR / Virtual Reality, Q1’26 Apr '26, counts as said0 times: VR / Virtual Reality, Q2’26 Jul '264 times: VR / Virtual Reality, Q3’26 Oct '26, counts as saidrising4/850%4/850%42/5872%69%n=6+tx from settlement history blended with transcripts78¢ Kalshi
Silicon8 times: Silicon, Q4’24 Jan '25, counts as said0 times: Silicon, Q1’25 Apr '250 times: Silicon, Q2’25 Jul '250 times: Silicon, Q3’25 Oct '252 times: Silicon, Q4’25 Jan '26, counts as said2 times: Silicon, Q1’26 Apr '26, counts as said1 time: Silicon, Q2’26 Jul '26, counts as said0 times: Silicon, Q3’26 Oct '26falling4/850%4/850%7/5812%48%n=2+tx from settlement history blended with transcripts30¢ Kalshi
Hiring3 times: Hiring, Q4’24 Jan '25, counts as said1 time: Hiring, Q1’25 Apr '25, counts as said3 times: Hiring, Q2’25 Jul '25, counts as said1 time: Hiring, Q3’25 Oct '25, counts as said2 times: Hiring, Q4’25 Jan '26, counts as said1 time: Hiring, Q1’26 Apr '26, counts as said0 times: Hiring, Q2’26 Jul '260 times: Hiring, Q3’26 Oct '26falling6/875%6/875%38/5866%45%n=5+tx from settlement history blended with transcripts21¢ Kalshi
Dividend2 times: Dividend, Q4’24 Jan '25, counts as said1 time: Dividend, Q1’25 Apr '25, counts as said2 times: Dividend, Q2’25 Jul '25, counts as said1 time: Dividend, Q3’25 Oct '25, counts as said0 times: Dividend, Q4’25 Jan '260 times: Dividend, Q1’26 Apr '260 times: Dividend, Q2’26 Jul '261 time: Dividend, Q3’26 Oct '26, counts as saidfalling5/862%5/862%11/5819%44%n=5+tx from settlement history blended with transcripts74¢ Kalshi
Ray-Ban2 times: Ray-Ban, Q4’24 Jan '25, counts as said4 times: Ray-Ban, Q1’25 Apr '25, counts as said3 times: Ray-Ban, Q2’25 Jul '25, counts as said4 times: Ray-Ban, Q3’25 Oct '25, counts as said0 times: Ray-Ban, Q4’25 Jan '263 times: Ray-Ban, Q1’26 Apr '26, counts as said0 times: Ray-Ban, Q2’26 Jul '260 times: Ray-Ban, Q3’26 Oct '26falling5/862%5/862%13/5822%40%n=6+tx from settlement history blended with transcripts30¢ Kalshi
Algorithm0 times: Algorithm, Q4’24 Jan '251 time: Algorithm, Q1’25 Apr '25, counts as said1 time: Algorithm, Q2’25 Jul '25, counts as said0 times: Algorithm, Q3’25 Oct '251 time: Algorithm, Q4’25 Jan '26, counts as said1 time: Algorithm, Q1’26 Apr '26, counts as said0 times: Algorithm, Q2’26 Jul '260 times: Algorithm, Q3’26 Oct '26steady4/850%2/825%11/5819%34%n=5+tx from settlement history blended with transcripts18¢ Kalshi
Oakley0 times: Oakley, Q4’24 Jan '250 times: Oakley, Q1’25 Apr '252 times: Oakley, Q2’25 Jul '25, counts as said3 times: Oakley, Q3’25 Oct '25, counts as said0 times: Oakley, Q4’25 Jan '261 time: Oakley, Q1’26 Apr '26, counts as said0 times: Oakley, Q2’26 Jul '260 times: Oakley, Q3’26 Oct '26falling3/838%3/838%4/587%26%n=5+tx from settlement history blended with transcripts20¢ Kalshi
Hyperion0 times: Hyperion, Q4’24 Jan '250 times: Hyperion, Q1’25 Apr '251 time: Hyperion, Q2’25 Jul '25, counts as said0 times: Hyperion, Q3’25 Oct '250 times: Hyperion, Q4’25 Jan '260 times: Hyperion, Q1’26 Apr '260 times: Hyperion, Q2’26 Jul '260 times: Hyperion, Q3’26 Oct '26steady1/812%1/812%1/582%12%n=5+tx from settlement history blended with transcripts8¢ Kalshi
TikTok1 time: TikTok, Q4’24 Jan '25, counts as said0 times: TikTok, Q1’25 Apr '250 times: TikTok, Q2’25 Jul '250 times: TikTok, Q3’25 Oct '250 times: TikTok, Q4’25 Jan '260 times: TikTok, Q1’26 Apr '260 times: TikTok, Q2’26 Jul '260 times: TikTok, Q3’26 Oct '26falling1/812%1/812%6/5810%11%n=6+tx from settlement history blended with transcripts6¢ Kalshi
Age Verificationnever said0 times: Age Verification, Q4’24 Jan '250 times: Age Verification, Q1’25 Apr '250 times: Age Verification, Q2’25 Jul '250 times: Age Verification, Q3’25 Oct '250 times: Age Verification, Q4’25 Jan '260 times: Age Verification, Q1’26 Apr '260 times: Age Verification, Q2’26 Jul '260 times: Age Verification, Q3’26 Oct '26steady0/80%0/80%0/580%10%n=2+tx from settlement history blended with transcripts6¢ Kalshi
Nebiusnever said0 times: Nebius, Q4’24 Jan '250 times: Nebius, Q1’25 Apr '250 times: Nebius, Q2’25 Jul '250 times: Nebius, Q3’25 Oct '250 times: Nebius, Q4’25 Jan '260 times: Nebius, Q1’26 Apr '260 times: Nebius, Q2’26 Jul '260 times: Nebius, Q3’26 Oct '26steady0/80%0/80%0/580%10%n=2+tx from settlement history blended with transcripts4¢ Kalshi
  • times said on that call
  • counted as said (ring)
  • no call
  • probability next time, with n
  • Select a word or a cell for its quotes
What the columns mean
Last N
of the appearances shown, how many counted as said
Trend
how the count moved over these calls
Scripted
calls of the last 8 where it was said in the prepared remarks
All-time
every call on file
Probability
the calibrated probability for the next listing; n is the settled observations behind it when it was computed, '+tx' adds the transcripts, 'new' means too little history

Market prices are mid quotes from Kalshi and Polymarket, shown for context, may be delayed by several minutes and are not a signal. Quotes as of Oct 22, 2026 22:11 UTC.

Every word

1–40 of 46, most settled first · page 1 of 2
Meta: every word with settled markets, most settled first
WordQ4’24Jan '25Q1’25Apr '25Q2’25Jul '25Q3’25Oct '25Q4’25Jan '26Q1’26Apr '26Q2’26Jul '26Q3’26last callTrendLast 8ScriptedAll-timeProbability
Llama16 times: Llama, Q4’24 Jan '25, counts as said10 times: Llama, Q1’25 Apr '25, counts as said6 times: Llama, Q2’25 Jul '25, counts as said1 time: Llama, Q3’25 Oct '25, counts as said0 times: Llama, Q4’25 Jan '260 times: Llama, Q1’26 Apr '260 times: Llama, Q2’26 Jul '260 times: Llama, Q3’26 Oct '26falling4/850%3/838%11/5819%19%n=6+tx from settlement history blended with transcripts
Orion2 times: Orion, Q4’24 Jan '25, counts as said0 times: Orion, Q1’25 Apr '251 time: Orion, Q2’25 Jul '25, counts as said1 time: Orion, Q3’25 Oct '25, counts as said0 times: Orion, Q4’25 Jan '260 times: Orion, Q1’26 Apr '260 times: Orion, Q2’26 Jul '260 times: Orion, Q3’26 Oct '26falling3/838%0/80%4/587%19%n=5+tx from settlement history blended with transcripts
WhatsApp6 times: WhatsApp, Q4’24 Jan '25, counts as said13 times: WhatsApp, Q1’25 Apr '25, counts as said10 times: WhatsApp, Q2’25 Jul '25, counts as said6 times: WhatsApp, Q3’25 Oct '25, counts as said6 times: WhatsApp, Q4’25 Jan '26, counts as said5 times: WhatsApp, Q1’26 Apr '26, counts as said11 times: WhatsApp, Q2’26 Jul '26, counts as said3 times: WhatsApp, Q3’26 Oct '26, counts as saidfalling8/8100%8/8100%51/5888%92%n=3+tx from settlement history blended with transcripts
SAM0 times: SAM, Q4’24 Jan '250 times: SAM, Q1’25 Apr '250 times: SAM, Q2’25 Jul '250 times: SAM, Q3’25 Oct '250 times: SAM, Q4’25 Jan '260 times: SAM, Q1’26 Apr '260 times: SAM, Q2’26 Jul '260 times: SAM, Q3’26 Oct '26steady0/80%0/80%1/582%10%n=3+tx from settlement history blended with transcripts
AI / Artificial Intelligence30+ times91 times: AI / Artificial Intelligence 30+ times, Q4’24 Jan '25, counts as said99 times: AI / Artificial Intelligence 30+ times, Q1’25 Apr '25, counts as said72 times: AI / Artificial Intelligence 30+ times, Q2’25 Jul '25, counts as said67 times: AI / Artificial Intelligence 30+ times, Q3’25 Oct '25, counts as said44 times: AI / Artificial Intelligence 30+ times, Q4’25 Jan '26, counts as said59 times: AI / Artificial Intelligence 30+ times, Q1’26 Apr '26, counts as said44 times: AI / Artificial Intelligence 30+ times, Q2’26 Jul '26, counts as said35 times: AI / Artificial Intelligence 30+ times, Q3’26 Oct '26, counts as saidfalling8/8100%5/862%18/5831%79%n=2+tx from settlement history blended with transcripts
Facebook10+ times13 times: Facebook 10+ times, Q4’24 Jan '25, counts as said13 times: Facebook 10+ times, Q1’25 Apr '25, counts as said16 times: Facebook 10+ times, Q2’25 Jul '25, counts as said13 times: Facebook 10+ times, Q3’25 Oct '25, counts as said12 times: Facebook 10+ times, Q4’25 Jan '26, counts as said11 times: Facebook 10+ times, Q1’26 Apr '26, counts as said12 times: Facebook 10+ times, Q2’26 Jul '26, counts as said10 times: Facebook 10+ times, Q3’26 Oct '26, counts as saidsteady8/8100%2/825%56/5897%75%n=2+tx from settlement history blended with transcripts
Instagram7 times: Instagram, Q4’24 Jan '25, counts as said13 times: Instagram, Q1’25 Apr '25, counts as said11 times: Instagram, Q2’25 Jul '25, counts as said11 times: Instagram, Q3’25 Oct '25, counts as said7 times: Instagram, Q4’25 Jan '26, counts as said11 times: Instagram, Q1’26 Apr '26, counts as said16 times: Instagram, Q2’26 Jul '26, counts as said10 times: Instagram, Q3’26 Oct '26, counts as saidsteady8/8100%8/8100%57/5898%94%n=2+tx from settlement history blended with transcripts
Reality Lab6 times: Reality Lab, Q4’24 Jan '25, counts as said10 times: Reality Lab, Q1’25 Apr '25, counts as said7 times: Reality Lab, Q2’25 Jul '25, counts as said7 times: Reality Lab, Q3’25 Oct '25, counts as said5 times: Reality Lab, Q4’25 Jan '26, counts as said1 time: Reality Lab, Q1’26 Apr '26, counts as said1 time: Reality Lab, Q2’26 Jul '26, counts as said5 times: Reality Lab, Q3’26 Oct '26, counts as saidfalling8/8100%8/8100%24/5841%89%n=2+tx from settlement history blended with transcripts
Revenue5+ times24 times: Revenue 5+ times, Q4’24 Jan '25, counts as said22 times: Revenue 5+ times, Q1’25 Apr '25, counts as said22 times: Revenue 5+ times, Q2’25 Jul '25, counts as said32 times: Revenue 5+ times, Q3’25 Oct '25, counts as said17 times: Revenue 5+ times, Q4’25 Jan '26, counts as said15 times: Revenue 5+ times, Q1’26 Apr '26, counts as said16 times: Revenue 5+ times, Q2’26 Jul '26, counts as said32 times: Revenue 5+ times, Q3’26 Oct '26, counts as saidsteady8/8100%8/8100%57/5898%90%n=2+tx from settlement history blended with transcripts
Channel0 times: Channel, Q4’24 Jan '250 times: Channel, Q1’25 Apr '252 times: Channel, Q2’25 Jul '25, counts as said0 times: Channel, Q3’25 Oct '250 times: Channel, Q4’25 Jan '260 times: Channel, Q1’26 Apr '263 times: Channel, Q2’26 Jul '26, counts as said1 time: Channel, Q3’26 Oct '26, counts as saidrising3/838%2/825%26/5845%51%n=2+tx from settlement history blended with transcripts
Metaverse2 times: Metaverse, Q4’24 Jan '25, counts as said1 time: Metaverse, Q1’25 Apr '25, counts as said1 time: Metaverse, Q2’25 Jul '25, counts as said0 times: Metaverse, Q3’25 Oct '250 times: Metaverse, Q4’25 Jan '261 time: Metaverse, Q1’26 Apr '26, counts as said0 times: Metaverse, Q2’26 Jul '260 times: Metaverse, Q3’26 Oct '26falling4/850%3/838%17/5829%29%n=2+tx from settlement history blended with transcripts
World Cup0 times: World Cup, Q4’24 Jan '250 times: World Cup, Q1’25 Apr '250 times: World Cup, Q2’25 Jul '250 times: World Cup, Q3’25 Oct '250 times: World Cup, Q4’25 Jan '260 times: World Cup, Q1’26 Apr '261 time: World Cup, Q2’26 Jul '26, counts as said0 times: World Cup, Q3’26 Oct '26steady1/812%1/812%8/5814%24%n=2+tx from settlement history blended with transcripts
Antitrust0 times: Antitrust, Q4’24 Jan '250 times: Antitrust, Q1’25 Apr '250 times: Antitrust, Q2’25 Jul '250 times: Antitrust, Q3’25 Oct '250 times: Antitrust, Q4’25 Jan '260 times: Antitrust, Q1’26 Apr '260 times: Antitrust, Q2’26 Jul '260 times: Antitrust, Q3’26 Oct '26steady0/80%0/80%2/583%12%n=2+tx from settlement history blended with transcripts
Behemoth0 times: Behemoth, Q4’24 Jan '254 times: Behemoth, Q1’25 Apr '25, counts as said1 time: Behemoth, Q2’25 Jul '25, counts as said0 times: Behemoth, Q3’25 Oct '250 times: Behemoth, Q4’25 Jan '260 times: Behemoth, Q1’26 Apr '260 times: Behemoth, Q2’26 Jul '260 times: Behemoth, Q3’26 Oct '26falling2/825%1/812%2/583%17%n=2+tx from settlement history blended with transcripts
Maverick0 times: Maverick, Q4’24 Jan '250 times: Maverick, Q1’25 Apr '250 times: Maverick, Q2’25 Jul '250 times: Maverick, Q3’25 Oct '250 times: Maverick, Q4’25 Jan '260 times: Maverick, Q1’26 Apr '260 times: Maverick, Q2’26 Jul '260 times: Maverick, Q3’26 Oct '26steady0/80%0/80%1/582%12%n=2+tx from settlement history blended with transcripts
Scoutnever said0 times: Scout, Q4’24 Jan '250 times: Scout, Q1’25 Apr '250 times: Scout, Q2’25 Jul '250 times: Scout, Q3’25 Oct '250 times: Scout, Q4’25 Jan '260 times: Scout, Q1’26 Apr '260 times: Scout, Q2’26 Jul '260 times: Scout, Q3’26 Oct '26steady0/80%0/80%0/580%12%n=2+tx from settlement history blended with transcripts
UK / United Kingdom0 times: UK / United Kingdom, Q4’24 Jan '250 times: UK / United Kingdom, Q1’25 Apr '250 times: UK / United Kingdom, Q2’25 Jul '250 times: UK / United Kingdom, Q3’25 Oct '251 time: UK / United Kingdom, Q4’25 Jan '26, counts as said0 times: UK / United Kingdom, Q1’26 Apr '260 times: UK / United Kingdom, Q2’26 Jul '260 times: UK / United Kingdom, Q3’26 Oct '26steady1/812%1/812%7/5812%17%n=2+tx from settlement history blended with transcripts
AI recommendation0 times: AI recommendation, Q4’24 Jan '251 time: AI recommendation, Q1’25 Apr '25, counts as said0 times: AI recommendation, Q2’25 Jul '251 time: AI recommendation, Q3’25 Oct '25, counts as said0 times: AI recommendation, Q4’25 Jan '260 times: AI recommendation, Q1’26 Apr '260 times: AI recommendation, Q2’26 Jul '260 times: AI recommendation, Q3’26 Oct '26falling2/825%2/825%6/5810%24%n=1+tx from settlement history blended with transcripts
Efficiency9 times: Efficiency, Q4’24 Jan '25, counts as said8 times: Efficiency, Q1’25 Apr '25, counts as said4 times: Efficiency, Q2’25 Jul '25, counts as said3 times: Efficiency, Q3’25 Oct '25, counts as said6 times: Efficiency, Q4’25 Jan '26, counts as said6 times: Efficiency, Q1’26 Apr '26, counts as said3 times: Efficiency, Q2’26 Jul '26, counts as said18 times: Efficiency, Q3’26 Oct '26, counts as saidrising8/8100%8/8100%31/5853%93%n=1+tx from settlement history blended with transcripts
Election0 times: Election, Q4’24 Jan '251 time: Election, Q1’25 Apr '25, counts as said0 times: Election, Q2’25 Jul '250 times: Election, Q3’25 Oct '251 time: Election, Q4’25 Jan '26, counts as said0 times: Election, Q1’26 Apr '260 times: Election, Q2’26 Jul '260 times: Election, Q3’26 Oct '26steady2/825%0/80%22/5838%31%n=1+tx from settlement history blended with transcripts
Europe / European1 time: Europe / European, Q4’24 Jan '25, counts as said8 times: Europe / European, Q1’25 Apr '25, counts as said5 times: Europe / European, Q2’25 Jul '25, counts as said2 times: Europe / European, Q3’25 Oct '25, counts as said2 times: Europe / European, Q4’25 Jan '26, counts as said0 times: Europe / European, Q1’26 Apr '260 times: Europe / European, Q2’26 Jul '260 times: Europe / European, Q3’26 Oct '26falling5/862%5/862%49/5884%45%n=1+tx from settlement history blended with transcripts
Generative AI / Gen AI / Gen-AI14 times: Generative AI / Gen AI / Gen-AI, Q4’24 Jan '25, counts as said5 times: Generative AI / Gen AI / Gen-AI, Q1’25 Apr '25, counts as said5 times: Generative AI / Gen AI / Gen-AI, Q2’25 Jul '25, counts as said1 time: Generative AI / Gen AI / Gen-AI, Q3’25 Oct '25, counts as said0 times: Generative AI / Gen AI / Gen-AI, Q4’25 Jan '261 time: Generative AI / Gen AI / Gen-AI, Q1’26 Apr '26, counts as said1 time: Generative AI / Gen AI / Gen-AI, Q2’26 Jul '26, counts as said2 times: Generative AI / Gen AI / Gen-AI, Q3’26 Oct '26, counts as saidfalling7/888%7/888%15/5826%68%n=1+tx from settlement history blended with transcripts
Meta AI27 times: Meta AI, Q4’24 Jan '25, counts as said33 times: Meta AI, Q1’25 Apr '25, counts as said16 times: Meta AI, Q2’25 Jul '25, counts as said14 times: Meta AI, Q3’25 Oct '25, counts as said10 times: Meta AI, Q4’25 Jan '26, counts as said15 times: Meta AI, Q1’26 Apr '26, counts as said5 times: Meta AI, Q2’26 Jul '26, counts as said7 times: Meta AI, Q3’26 Oct '26, counts as saidfalling8/8100%8/8100%13/5822%93%n=1+tx from settlement history blended with transcripts
Muse0 times: Muse, Q4’24 Jan '250 times: Muse, Q1’25 Apr '250 times: Muse, Q2’25 Jul '250 times: Muse, Q3’25 Oct '250 times: Muse, Q4’25 Jan '266 times: Muse, Q1’26 Apr '26, counts as said15 times: Muse, Q2’26 Jul '26, counts as said91 times: Muse, Q3’26 Oct '26, counts as saidrising3/838%3/838%3/585%93%n=1+tx from settlement history blended with transcripts
Muse10+ times0 times: Muse 10+ times, Q4’24 Jan '250 times: Muse 10+ times, Q1’25 Apr '250 times: Muse 10+ times, Q2’25 Jul '250 times: Muse 10+ times, Q3’25 Oct '250 times: Muse 10+ times, Q4’25 Jan '2612 times: Muse 10+ times, Q1’26 Apr '26, counts as said16 times: Muse 10+ times, Q2’26 Jul '26, counts as said97 times: Muse 10+ times, Q3’26 Oct '26, counts as saidrising3/838%2/825%3/585%75%n=1+tx from settlement history blended with transcripts
Quarter15+ times10 times: Quarter 15+ times, Q4’24 Jan '25, below the threshold20 times: Quarter 15+ times, Q1’25 Apr '25, counts as said25 times: Quarter 15+ times, Q2’25 Jul '25, counts as said22 times: Quarter 15+ times, Q3’25 Oct '25, counts as said11 times: Quarter 15+ times, Q4’25 Jan '26, below the threshold20 times: Quarter 15+ times, Q1’26 Apr '26, counts as said17 times: Quarter 15+ times, Q2’26 Jul '26, counts as said15 times: Quarter 15+ times, Q3’26 Oct '26, counts as saidsteady6/875%4/850%50/5886%61%n=1+tx from settlement history blended with transcripts
Reality6 times: Reality, Q4’24 Jan '25, counts as said11 times: Reality, Q1’25 Apr '25, counts as said7 times: Reality, Q2’25 Jul '25, counts as said7 times: Reality, Q3’25 Oct '25, counts as said6 times: Reality, Q4’25 Jan '26, counts as said1 time: Reality, Q1’26 Apr '26, counts as said1 time: Reality, Q2’26 Jul '26, counts as said7 times: Reality, Q3’26 Oct '26, counts as saidfalling8/8100%8/8100%48/5883%87%n=1+tx from settlement history blended with transcripts
Reels4 times: Reels, Q4’24 Jan '25, counts as said5 times: Reels, Q1’25 Apr '25, counts as said4 times: Reels, Q2’25 Jul '25, counts as said3 times: Reels, Q3’25 Oct '25, counts as said4 times: Reels, Q4’25 Jan '26, counts as said2 times: Reels, Q1’26 Apr '26, counts as said5 times: Reels, Q2’26 Jul '26, counts as said11 times: Reels, Q3’26 Oct '26, counts as saidrising8/8100%8/8100%26/5845%90%n=1+tx from settlement history blended with transcripts
Regulator / Regulatory / Regulation5 times: Regulator / Regulatory / Regulation, Q4’24 Jan '25, counts as said3 times: Regulator / Regulatory / Regulation, Q1’25 Apr '25, counts as said3 times: Regulator / Regulatory / Regulation, Q2’25 Jul '25, counts as said2 times: Regulator / Regulatory / Regulation, Q3’25 Oct '25, counts as said1 time: Regulator / Regulatory / Regulation, Q4’25 Jan '26, counts as said1 time: Regulator / Regulatory / Regulation, Q1’26 Apr '26, counts as said1 time: Regulator / Regulatory / Regulation, Q2’26 Jul '26, counts as said1 time: Regulator / Regulatory / Regulation, Q3’26 Oct '26, counts as saidfalling8/8100%8/8100%33/5857%73%n=1+tx from settlement history blended with transcripts
SI / Super Intelligence0 times: SI / Super Intelligence, Q4’24 Jan '250 times: SI / Super Intelligence, Q1’25 Apr '2520 times: SI / Super Intelligence, Q2’25 Jul '25, counts as said10 times: SI / Super Intelligence, Q3’25 Oct '25, counts as said6 times: SI / Super Intelligence, Q4’25 Jan '26, counts as said9 times: SI / Super Intelligence, Q1’26 Apr '26, counts as said10 times: SI / Super Intelligence, Q2’26 Jul '26, counts as said12 times: SI / Super Intelligence, Q3’26 Oct '26, counts as saidrising6/875%6/875%6/5810%92%n=1+tx from settlement history blended with transcripts
ActivityPubnever said0 times: ActivityPub, Q4’24 Jan '250 times: ActivityPub, Q1’25 Apr '250 times: ActivityPub, Q2’25 Jul '250 times: ActivityPub, Q3’25 Oct '250 times: ActivityPub, Q4’25 Jan '260 times: ActivityPub, Q1’26 Apr '260 times: ActivityPub, Q2’26 Jul '260 times: ActivityPub, Q3’26 Oct '26steady0/80%0/80%0/580%13%n=1+tx from settlement history blended with transcripts
Ad targeting / Ad-targeting0 times: Ad targeting / Ad-targeting, Q4’24 Jan '250 times: Ad targeting / Ad-targeting, Q1’25 Apr '250 times: Ad targeting / Ad-targeting, Q2’25 Jul '250 times: Ad targeting / Ad-targeting, Q3’25 Oct '250 times: Ad targeting / Ad-targeting, Q4’25 Jan '260 times: Ad targeting / Ad-targeting, Q1’26 Apr '260 times: Ad targeting / Ad-targeting, Q2’26 Jul '260 times: Ad targeting / Ad-targeting, Q3’26 Oct '26steady0/80%0/80%15/5826%13%n=1+tx from settlement history blended with transcripts
Anthropic0 times: Anthropic, Q4’24 Jan '250 times: Anthropic, Q1’25 Apr '250 times: Anthropic, Q2’25 Jul '250 times: Anthropic, Q3’25 Oct '251 time: Anthropic, Q4’25 Jan '26, counts as said0 times: Anthropic, Q1’26 Apr '260 times: Anthropic, Q2’26 Jul '260 times: Anthropic, Q3’26 Oct '26steady1/812%0/80%1/582%20%n=1+tx from settlement history blended with transcripts
AR / Augmented Reality1 time: AR / Augmented Reality, Q4’24 Jan '25, counts as said0 times: AR / Augmented Reality, Q1’25 Apr '250 times: AR / Augmented Reality, Q2’25 Jul '250 times: AR / Augmented Reality, Q3’25 Oct '250 times: AR / Augmented Reality, Q4’25 Jan '260 times: AR / Augmented Reality, Q1’26 Apr '260 times: AR / Augmented Reality, Q2’26 Jul '260 times: AR / Augmented Reality, Q3’26 Oct '26falling1/812%0/80%37/5864%17%n=1+tx from settlement history blended with transcripts
China1 time: China, Q4’24 Jan '25, counts as said2 times: China, Q1’25 Apr '25, counts as said0 times: China, Q2’25 Jul '250 times: China, Q3’25 Oct '250 times: China, Q4’25 Jan '260 times: China, Q1’26 Apr '260 times: China, Q2’26 Jul '260 times: China, Q3’26 Oct '26falling2/825%0/80%23/5840%18%n=1+tx from settlement history blended with transcripts
Expense10+ times14 times: Expense 10+ times, Q4’24 Jan '25, counts as said11 times: Expense 10+ times, Q1’25 Apr '25, counts as said27 times: Expense 10+ times, Q2’25 Jul '25, counts as said9 times: Expense 10+ times, Q3’25 Oct '25, below the threshold10 times: Expense 10+ times, Q4’25 Jan '26, counts as said3 times: Expense 10+ times, Q1’26 Apr '26, below the threshold7 times: Expense 10+ times, Q2’26 Jul '26, below the threshold6 times: Expense 10+ times, Q3’26 Oct '26, below the thresholdfalling4/850%3/838%41/5871%25%n=1+tx from settlement history blended with transcripts
Hiring freeze0 times: Hiring freeze, Q4’24 Jan '250 times: Hiring freeze, Q1’25 Apr '250 times: Hiring freeze, Q2’25 Jul '250 times: Hiring freeze, Q3’25 Oct '250 times: Hiring freeze, Q4’25 Jan '260 times: Hiring freeze, Q1’26 Apr '260 times: Hiring freeze, Q2’26 Jul '260 times: Hiring freeze, Q3’26 Oct '26steady0/80%0/80%3/585%13%n=1+tx from settlement history blended with transcripts
Horizon Worlds0 times: Horizon Worlds, Q4’24 Jan '250 times: Horizon Worlds, Q1’25 Apr '250 times: Horizon Worlds, Q2’25 Jul '250 times: Horizon Worlds, Q3’25 Oct '250 times: Horizon Worlds, Q4’25 Jan '260 times: Horizon Worlds, Q1’26 Apr '260 times: Horizon Worlds, Q2’26 Jul '260 times: Horizon Worlds, Q3’26 Oct '26steady0/80%0/80%1/582%13%n=1+tx from settlement history blended with transcripts
Nebius / Hyperion0 times: Nebius / Hyperion, Q4’24 Jan '250 times: Nebius / Hyperion, Q1’25 Apr '251 time: Nebius / Hyperion, Q2’25 Jul '25, counts as said0 times: Nebius / Hyperion, Q3’25 Oct '250 times: Nebius / Hyperion, Q4’25 Jan '260 times: Nebius / Hyperion, Q1’26 Apr '260 times: Nebius / Hyperion, Q2’26 Jul '260 times: Nebius / Hyperion, Q3’26 Oct '26steady1/812%1/812%1/582%14%n=1+tx from settlement history blended with transcripts
Prediction Market / Kalshinever said0 times: Prediction Market / Kalshi, Q4’24 Jan '250 times: Prediction Market / Kalshi, Q1’25 Apr '250 times: Prediction Market / Kalshi, Q2’25 Jul '250 times: Prediction Market / Kalshi, Q3’25 Oct '250 times: Prediction Market / Kalshi, Q4’25 Jan '260 times: Prediction Market / Kalshi, Q1’26 Apr '260 times: Prediction Market / Kalshi, Q2’26 Jul '260 times: Prediction Market / Kalshi, Q3’26 Oct '26steady0/80%0/80%0/580%12%n=1+tx from settlement history blended with transcripts
What the columns mean
Last N
of the appearances shown, how many counted as said
Trend
how the count moved over these calls
Scripted
calls of the last 8 where it was said in the prepared remarks
All-time
every call on file
Probability
the calibrated probability for the next listing; n is the settled observations behind it when it was computed, '+tx' adds the transcripts, 'new' means too little history

More words (6 left)

Appearances and settled record

latest 12

Our transcript counts matched how 186 of 188 settled words resolved (98.9%). How we check.

Recent appearances and how their listed words settled
DateAppearanceTextWordsSettledOur count agreed
Oct 21, 2026Earnings call FY26 Q3Speaker-labelled transcript3015 yes · 15 no30/30 (100%)
Jul 29, 2026Earnings call FY26 Q2Speaker-labelled transcript4211 yes · 31 no42/42 (100%)
Apr 29, 2026Earnings call FY26 Q1Speaker-labelled transcript158 yes · 7 no15/15 (100%)
Jan 28, 2026Earnings call FY25 Q4Speaker-labelled transcript147 yes · 7 no13/14 (93%)
Oct 29, 2025Earnings call FY25 Q3Speaker-labelled transcript4220 yes · 22 no42/42 (100%)
Jul 30, 2025Earnings call FY25 Q2Speaker-labelled transcript2517 yes · 8 no25/25 (100%)
Apr 30, 2025Earnings call FY25 Q1Speaker-labelled transcript2012 yes · 8 no19/20 (95%)
Jan 29, 2025Earnings call FY24 Q4Speaker-labelled transcript0––
Oct 30, 2024Earnings call FY24 Q3Speaker-labelled transcript0––
Jul 31, 2024Earnings call FY24 Q2Speaker-labelled transcript0––
Apr 24, 2024Earnings call FY24 Q1Speaker-labelled transcript0––
Feb 1, 2024Earnings call FY23 Q4Speaker-labelled transcript0––

Citeparrot.markets, “Meta (META): earnings call word history”, as of Oct 24, 2026, https://parrot.markets/earnings/META (CC BY 4.0)

Agents: this page as TSV at /api/v1/entity/meta · words: /api/v1/history?entity=meta · columnar JSON in #parrot-data · llms.txt · MCP