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AT69

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- AT69AT69
  ·06-14 14:46
  Pls do some soul searching and dont squander your fortunes away
  Following Amazon, Meta Imposes Limits on AI Usage. As Tech Giants Reel from Token Costs, Should AI Model Leaders Focus on Profit Margins?
  After Amazon.com (AMZN), Meta Platforms, Inc. (META) is also restricting AI usage, highlighting a critical and often overlooked industry conflict: the very logic of AI commercialization is being...
  Following Amazon, Meta Imposes Limits on AI Usage. As Tech Giants Reel from Token Costs, Should AI Model Leaders Focus on Profit Margins?
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- AT69AT69
  ·06-14 14:46
  Zuckerberg...monkey see..monkey do
  Following Amazon, Meta Imposes Limits on AI Usage. As Tech Giants Reel from Token Costs, Should AI Model Leaders Focus on Profit Margins?
  After Amazon.com (AMZN), Meta Platforms, Inc. (META) is also restricting AI usage, highlighting a critical and often overlooked industry conflict: the very logic of AI commercialization is being...
  Following Amazon, Meta Imposes Limits on AI Usage. As Tech Giants Reel from Token Costs, Should AI Model Leaders Focus on Profit Margins?
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- AT69AT69
  ·06-10
  $Meta Platforms, Inc.(META)$ Seems quite hopeless..let it crash another 50%
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- AT69AT69
  ·06-02
  $Meta Platforms, Inc.(META)$ zuckerberg better buck up..else they may drop out from Mag 7 soon..
  434 Comment
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- AT69AT69
  ·05-08
  $Meta Platforms, Inc.(META)$ Mark zuckerberg only have himself to blame..let the price plunge another 50%
  923 Comment
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- AT69AT69
  ·05-08
  $Meta Platforms, Inc.(META)$ Looks like everyone is dumping this stock..
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- AT69AT69
  ·02-05
  $Alphabet(GOOG)$ Are we seeing start of market meltdown ?
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- AT69AT69
  ·02-05
  $Microsoft(MSFT)$ Markets plunging everyday..hope the selldown will end soon
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- AT69AT69
  ·02-04
  $Microsoft(MSFT)$ Those who short the stock are scrambling to cover their positions
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- AT69AT69
  ·01-15
  $Meta Platforms, Inc.(META)$ Maybe meta will slip to 500
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do some soul searching and dont squander your fortunes away","listText":"Pls do some soul searching and dont squander your fortunes away","text":"Pls do some soul searching and dont squander your fortunes away","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/575124525166832","repostId":"1140497679","repostType":2,"repost":{"id":"1140497679","kind":"news","weMediaInfo":{"introduction":"Global Stock Market Deep Analysis","home_visible":1,"media_name":"Deep News","id":"1039043262","head_image":"https://community-static.tradeup.com/news/8296859682db4b478146245e72de1922"},"pubTimestamp":1781351372,"share":"https://ttm.financial/m/news/1140497679?lang=en_US&edition=fundamental","pubTime":"2026-06-13 19:49","market":"other","language":"en","title":"Following Amazon, Meta Imposes Limits on AI Usage. As Tech Giants Reel from Token Costs, Should AI Model Leaders Focus on Profit Margins?","url":"https://stock-news.laohu8.com/highlight/detail?id=1140497679","media":"Deep News","summary":"After Amazon.com (AMZN), Meta Platforms, Inc. (META) is also restricting AI usage, highlighting a critical and often overlooked industry conflict: the very logic of AI commercialization is being...","content":"<p>After <b>Amazon.com</b> (<b>AMZN</b>), <b>Meta Platforms, Inc.</b> (<b>META</b>) is also restricting AI usage, highlighting a critical and often overlooked industry conflict: the very logic of AI commercialization is being challenged by the soaring costs it generates.<br><br>\nAccording to reports, Meta sent an internal memo to approximately 6,000 employees this week, announcing it will set caps on employee token usage and build a real-time tracking platform to curb the exponential growth of internal AI costs.<br><br>\nThe memo stated that Meta's internal AI usage alone is projected to cost tens of billions of dollars by 2026. This move comes after Meta previously encouraged employees to integrate AI tools into their daily workflows, a strategy it is now forced to abruptly reverse.<br><br>\nConcurrently, reports indicate OpenAI is considering significant token price cuts to attract enterprise clients. Meanwhile, the Silicon Data LLM Token Spending Index, which reflects market willingness to pay for AI, has fallen for seven consecutive trading days—its longest losing streak since January this year.<br><br>\nThese combined signals have rapidly heightened market skepticism about the sustainability of AI commercialization. For investors, the core question is no longer whether AI demand exists, but rather: when tech giants themselves start scrutinizing their token bills, how much profit margin remains for the large AI model providers?<br><br>\n<b>The Uncontrolled Token Bill: Meta's Internal \"Spending Spree\"</b><br><br>\nThe direct catalyst for Meta tightening AI usage was a frenzy of token consumption fueled by internal incentives.<br><br>\nLast November, Meta explicitly told employees that demonstrating \"AI-driven work results\" would be a \"core performance requirement\" this year, with top performers receiving rewards. This directive led to an unintended consequence this spring: some employees engaged in a competition dubbed \"tokenmaxxing,\" vying for spots on an internal leaderboard called \"Claudeonomics,\" which ranked the top 250 employees by token usage.<br><br>\nInternal data shows employees consumed 60.2 trillion tokens in a 30-day period, with the figure later climbing to 73.7 trillion, leading to the leaderboard being taken down. Some employees reportedly instructed AI agents to run multiple tasks simultaneously to artificially inflate token consumption.<br><br>\nMeta's Chief Technology Officer Andrew Bosworth warned in an April memo that \"nobody should be using AI just to use AI,\" stressing that \"Token usage is not a measure of impact in any sense.\" However, mere warnings proved insufficient to halt the rising costs.<br><br>\n<b>Systematic Response: The AI Gateway and Internal Tool Substitution</b><br><br>\nFaced with runaway spending, Meta is implementing a systematic cost-control mechanism.<br><br>\nAccording to the internal memo, Meta has built a central dashboard called \"AI Gateway\" for real-time monitoring of company-wide AI usage and expenditure, with plans to add automated alerts for abnormal consumption spikes. The company intends to roll out these control tools to a broader employee base in the coming weeks and establish a more structured token budget allocation system by 2027.<br><br>\nSimultaneously, Meta is pushing employees to shift from third-party AI tools to in-house solutions. Its new Applied AI Engineering department is tasking engineers with improving the internal coding assistant MetaCode (formerly Devmate), aiming to reduce reliance on Anthropic's Claude, which is currently the primary tool for Meta's engineers in coding work.<br><br>\nIt's noted that Meta is not completely blocking access to third-party models; employees can still use tools from OpenAI, Anthropic, and Google, but internal tools will be explicitly prioritized.<br><br>\n<b>Industry Echo: Major Tech Firms Hitting the Brakes</b><br><br>\nMeta is not alone. Token bill pressures are resonating across the tech industry.<br><br>\nReports indicate Amazon recently shut down an internal AI leaderboard because employees were performing unnecessary operations to \"boost scores,\" causing a sharp rise in compute costs. Amazon has also begun using a metric called \"standardized deployment\" to evaluate whether engineers regularly use AI to generate useful code, rather than simply measuring token consumption.<br><br>\nFurthermore, reports suggest Uber and ServiceNow exhausted their annual budgets for Anthropic tools early in 2026. ServiceNow is also monitoring daily employee usage to track and compress costs. Venture capital firms are setting AI usage caps for employees due to daily token fees often reaching thousands of dollars.<br><br>\nAgainst this backdrop, rumors of OpenAI's price cuts carry deeper significance.<br><br>\nReports state OpenAI is considering significant reductions in token fees charged to users, partly to get ahead of potential similar moves by Anthropic.<br><br>\nOpenAI's CEO Sam Altman recently acknowledged that AI usage costs are \"a huge problem\" and stated the company would \"help people get more value for less money.\"<br><br>\nThe timing of this statement is notable—OpenAI has confidentially filed for an IPO this week, and Anthropic is also on a countdown to its public listing. While price cuts can help win enterprise clients, they directly erode profit margins for both companies, which are currently losing billions due to the massive compute power required for their AI systems.<br><br>\n<b>Token Index Decline: What is the Market Repricing?</b><br><br>\nCapital markets are already feeling the chill.<br><br>\nThe Silicon Data LLM Token Spending Index has fallen for seven consecutive trading days as of June 11, marking its longest losing streak since January, with declines recorded in 11 of the past 12 days.<br><br>\nThis index measures the average payment level per million tokens used across the market. It more than doubled since December last year and continued climbing until May 2026 before sharply reversing course.<br><br>\nA macro strategist described this chart as \"the single most important chart in the entire market right now,\" warning that if token pricing continues to weaken, the trading logic for related investments from memory to broader hardware and data centers in this cycle could face an end.<br><br>\nWall Street interpretations vary. JPMorgan characterizes the current trend as a \"minimal speed bump,\" while Citadel points out that the core constraint for AI adoption has shifted from \"the most capable model\" to \"cost and scarcity,\" with users accelerating their migration to cheaper models.<br><br>\nBehind this divergence lies a more fundamental valuation question: Is the decline in token consumption a signal of peak AI demand, or the result of users rationally choosing lower-cost models? The answer will directly impact capital expenditure expectations and valuation logic for companies like Nvidia, cloud providers, and the entire AI hardware supply chain.<br><br>\n<b>A Turning Point for the Commercial Narrative</b><br><br>\nFrom a broader perspective, Meta's move to restrict AI usage reflects a deeper shift in the generative AI commercialization narrative.<br><br>\nOver the past three years, the AI industry has undergone a three-stage evolution: from subsidizing users to gain adoption, to monthly subscriptions hiding costs, to per-token billing triggering an enterprise bill crisis. Now, as the growth narrative of \"more token consumption is better\" reaches its limit, the industry faces not just a pricing decision, but a more fundamental challenge of business model reconstruction.<br><br>\nMeta is investing a massive annual capital expenditure, partly to expand AI infrastructure including data centers, AI chips, and talent recruitment. Simultaneously, the company faces pressure from investors to generate visible returns from its enormous AI investments—Meta has already launched paid subscription tiers in Facebook, Instagram, and WhatsApp and plans to charge businesses using its AI business agents.<br><br>\nHowever, if even Meta's internal AI usage costs have become unsustainable, the profitability prospects of its enterprise AI agent business also face scrutiny. For the entire industry, how to tell the next chapter of the commercialization story remains an unanswered question.</p>","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>Following Amazon, Meta Imposes Limits on AI Usage. 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As Tech Giants Reel from Token Costs, Should AI Model Leaders Focus on Profit Margins?\n</h2>\n\n<h4 class=\"meta\">\n\n\n<a class=\"head\" href=\"https://laohu8.com/wemedia/1039043262\">\n\n\n<div class=\"h-thumb\" style=\"background-image:url(https://community-static.tradeup.com/news/8296859682db4b478146245e72de1922);background-size:cover;\"></div>\n\n<div class=\"h-content\">\n<p class=\"h-name\">Deep News </p>\n<p class=\"h-time\">2026-06-13 19:49</p>\n</div>\n\n</a>\n\n\n</h4>\n\n</header>\n<article>\n<p>After <b>Amazon.com</b> (<b>AMZN</b>), <b>Meta Platforms, Inc.</b> (<b>META</b>) is also restricting AI usage, highlighting a critical and often overlooked industry conflict: the very logic of AI commercialization is being challenged by the soaring costs it generates.<br><br>\nAccording to reports, Meta sent an internal memo to approximately 6,000 employees this week, announcing it will set caps on employee token usage and build a real-time tracking platform to curb the exponential growth of internal AI costs.<br><br>\nThe memo stated that Meta's internal AI usage alone is projected to cost tens of billions of dollars by 2026. This move comes after Meta previously encouraged employees to integrate AI tools into their daily workflows, a strategy it is now forced to abruptly reverse.<br><br>\nConcurrently, reports indicate OpenAI is considering significant token price cuts to attract enterprise clients. Meanwhile, the Silicon Data LLM Token Spending Index, which reflects market willingness to pay for AI, has fallen for seven consecutive trading days—its longest losing streak since January this year.<br><br>\nThese combined signals have rapidly heightened market skepticism about the sustainability of AI commercialization. For investors, the core question is no longer whether AI demand exists, but rather: when tech giants themselves start scrutinizing their token bills, how much profit margin remains for the large AI model providers?<br><br>\n<b>The Uncontrolled Token Bill: Meta's Internal \"Spending Spree\"</b><br><br>\nThe direct catalyst for Meta tightening AI usage was a frenzy of token consumption fueled by internal incentives.<br><br>\nLast November, Meta explicitly told employees that demonstrating \"AI-driven work results\" would be a \"core performance requirement\" this year, with top performers receiving rewards. This directive led to an unintended consequence this spring: some employees engaged in a competition dubbed \"tokenmaxxing,\" vying for spots on an internal leaderboard called \"Claudeonomics,\" which ranked the top 250 employees by token usage.<br><br>\nInternal data shows employees consumed 60.2 trillion tokens in a 30-day period, with the figure later climbing to 73.7 trillion, leading to the leaderboard being taken down. Some employees reportedly instructed AI agents to run multiple tasks simultaneously to artificially inflate token consumption.<br><br>\nMeta's Chief Technology Officer Andrew Bosworth warned in an April memo that \"nobody should be using AI just to use AI,\" stressing that \"Token usage is not a measure of impact in any sense.\" However, mere warnings proved insufficient to halt the rising costs.<br><br>\n<b>Systematic Response: The AI Gateway and Internal Tool Substitution</b><br><br>\nFaced with runaway spending, Meta is implementing a systematic cost-control mechanism.<br><br>\nAccording to the internal memo, Meta has built a central dashboard called \"AI Gateway\" for real-time monitoring of company-wide AI usage and expenditure, with plans to add automated alerts for abnormal consumption spikes. The company intends to roll out these control tools to a broader employee base in the coming weeks and establish a more structured token budget allocation system by 2027.<br><br>\nSimultaneously, Meta is pushing employees to shift from third-party AI tools to in-house solutions. Its new Applied AI Engineering department is tasking engineers with improving the internal coding assistant MetaCode (formerly Devmate), aiming to reduce reliance on Anthropic's Claude, which is currently the primary tool for Meta's engineers in coding work.<br><br>\nIt's noted that Meta is not completely blocking access to third-party models; employees can still use tools from OpenAI, Anthropic, and Google, but internal tools will be explicitly prioritized.<br><br>\n<b>Industry Echo: Major Tech Firms Hitting the Brakes</b><br><br>\nMeta is not alone. Token bill pressures are resonating across the tech industry.<br><br>\nReports indicate Amazon recently shut down an internal AI leaderboard because employees were performing unnecessary operations to \"boost scores,\" causing a sharp rise in compute costs. Amazon has also begun using a metric called \"standardized deployment\" to evaluate whether engineers regularly use AI to generate useful code, rather than simply measuring token consumption.<br><br>\nFurthermore, reports suggest Uber and ServiceNow exhausted their annual budgets for Anthropic tools early in 2026. ServiceNow is also monitoring daily employee usage to track and compress costs. Venture capital firms are setting AI usage caps for employees due to daily token fees often reaching thousands of dollars.<br><br>\nAgainst this backdrop, rumors of OpenAI's price cuts carry deeper significance.<br><br>\nReports state OpenAI is considering significant reductions in token fees charged to users, partly to get ahead of potential similar moves by Anthropic.<br><br>\nOpenAI's CEO Sam Altman recently acknowledged that AI usage costs are \"a huge problem\" and stated the company would \"help people get more value for less money.\"<br><br>\nThe timing of this statement is notable—OpenAI has confidentially filed for an IPO this week, and Anthropic is also on a countdown to its public listing. While price cuts can help win enterprise clients, they directly erode profit margins for both companies, which are currently losing billions due to the massive compute power required for their AI systems.<br><br>\n<b>Token Index Decline: What is the Market Repricing?</b><br><br>\nCapital markets are already feeling the chill.<br><br>\nThe Silicon Data LLM Token Spending Index has fallen for seven consecutive trading days as of June 11, marking its longest losing streak since January, with declines recorded in 11 of the past 12 days.<br><br>\nThis index measures the average payment level per million tokens used across the market. It more than doubled since December last year and continued climbing until May 2026 before sharply reversing course.<br><br>\nA macro strategist described this chart as \"the single most important chart in the entire market right now,\" warning that if token pricing continues to weaken, the trading logic for related investments from memory to broader hardware and data centers in this cycle could face an end.<br><br>\nWall Street interpretations vary. JPMorgan characterizes the current trend as a \"minimal speed bump,\" while Citadel points out that the core constraint for AI adoption has shifted from \"the most capable model\" to \"cost and scarcity,\" with users accelerating their migration to cheaper models.<br><br>\nBehind this divergence lies a more fundamental valuation question: Is the decline in token consumption a signal of peak AI demand, or the result of users rationally choosing lower-cost models? The answer will directly impact capital expenditure expectations and valuation logic for companies like Nvidia, cloud providers, and the entire AI hardware supply chain.<br><br>\n<b>A Turning Point for the Commercial Narrative</b><br><br>\nFrom a broader perspective, Meta's move to restrict AI usage reflects a deeper shift in the generative AI commercialization narrative.<br><br>\nOver the past three years, the AI industry has undergone a three-stage evolution: from subsidizing users to gain adoption, to monthly subscriptions hiding costs, to per-token billing triggering an enterprise bill crisis. Now, as the growth narrative of \"more token consumption is better\" reaches its limit, the industry faces not just a pricing decision, but a more fundamental challenge of business model reconstruction.<br><br>\nMeta is investing a massive annual capital expenditure, partly to expand AI infrastructure including data centers, AI chips, and talent recruitment. Simultaneously, the company faces pressure from investors to generate visible returns from its enormous AI investments—Meta has already launched paid subscription tiers in Facebook, Instagram, and WhatsApp and plans to charge businesses using its AI business agents.<br><br>\nHowever, if even Meta's internal AI usage costs have become unsustainable, the profitability prospects of its enterprise AI agent business also face scrutiny. For the entire industry, how to tell the next chapter of the commercialization story remains an unanswered question.</p>\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"LU2360106780.USD":"BGF WORLD TECHNOLOGY \"A4\" (USD) INC","LU1551013425.SGD":"Allianz Income and Growth Cl AMg2 DIS H2-SGD","LU1489326972.SGD":"First Eagle Amundi International AHS-MD SGD-H","LU1035775433.USD":"AB SICAV I - AMERICAN GROWTH PORTFOLIO \"AD\" (USD) INC","IE00B5949003.HKD":"JANUS HENDERSON GLOBAL TECHNOLOGY AND INNOVATION \"A\" (HKD) ACC","LU0949170772.SGD":"Blackrock Global Equity Income A6 SGD-H","LU1003077747.HKD":"BGF GLOBAL EQUITY INCOME \"A6\" (HKDHDG) INC","LU0130103400.USD":"Natixis Harris Associates Global Equity RA USD","LU0265550946.USD":"BGF SYSTEMATIC GLOBAL ENHANCED EQUITY YIELD \"A5\" (USD) INC","LU2083900584.USD":"HSBC GIF US INCOME FOCUSED \"AM2\" (USD) INC","IE00BJJMRX11.SGD":"Janus Henderson Balanced A Acc SGD","LU0738911758.USD":"Blackrock Global Equity Income A6 USD","LU1127390331.HKD":"AB SICAV I - 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(META) is also restricting AI usage, highlighting a critical and often overlooked industry conflict: the very logic of AI commercialization is being challenged by the soaring costs it generates.\nAccording to reports, Meta sent an internal memo to approximately 6,000 employees this week, announcing it will set caps on employee token usage and build a real-time tracking platform to curb the exponential growth of internal AI costs.\nThe memo stated that Meta's internal AI usage alone is projected to cost tens of billions of dollars by 2026. This move comes after Meta previously encouraged employees to integrate AI tools into their daily workflows, a strategy it is now forced to abruptly reverse.\nConcurrently, reports indicate OpenAI is considering significant token price cuts to attract enterprise clients. Meanwhile, the Silicon Data LLM Token Spending Index, which reflects market willingness to pay for AI, has fallen for seven consecutive trading days—its longest losing streak since January this year.\nThese combined signals have rapidly heightened market skepticism about the sustainability of AI commercialization. For investors, the core question is no longer whether AI demand exists, but rather: when tech giants themselves start scrutinizing their token bills, how much profit margin remains for the large AI model providers?\nThe Uncontrolled Token Bill: Meta's Internal \"Spending Spree\"\nThe direct catalyst for Meta tightening AI usage was a frenzy of token consumption fueled by internal incentives.\nLast November, Meta explicitly told employees that demonstrating \"AI-driven work results\" would be a \"core performance requirement\" this year, with top performers receiving rewards. This directive led to an unintended consequence this spring: some employees engaged in a competition dubbed \"tokenmaxxing,\" vying for spots on an internal leaderboard called \"Claudeonomics,\" which ranked the top 250 employees by token usage.\nInternal data shows employees consumed 60.2 trillion tokens in a 30-day period, with the figure later climbing to 73.7 trillion, leading to the leaderboard being taken down. Some employees reportedly instructed AI agents to run multiple tasks simultaneously to artificially inflate token consumption.\nMeta's Chief Technology Officer Andrew Bosworth warned in an April memo that \"nobody should be using AI just to use AI,\" stressing that \"Token usage is not a measure of impact in any sense.\" However, mere warnings proved insufficient to halt the rising costs.\nSystematic Response: The AI Gateway and Internal Tool Substitution\nFaced with runaway spending, Meta is implementing a systematic cost-control mechanism.\nAccording to the internal memo, Meta has built a central dashboard called \"AI Gateway\" for real-time monitoring of company-wide AI usage and expenditure, with plans to add automated alerts for abnormal consumption spikes. The company intends to roll out these control tools to a broader employee base in the coming weeks and establish a more structured token budget allocation system by 2027.\nSimultaneously, Meta is pushing employees to shift from third-party AI tools to in-house solutions. Its new Applied AI Engineering department is tasking engineers with improving the internal coding assistant MetaCode (formerly Devmate), aiming to reduce reliance on Anthropic's Claude, which is currently the primary tool for Meta's engineers in coding work.\nIt's noted that Meta is not completely blocking access to third-party models; employees can still use tools from OpenAI, Anthropic, and Google, but internal tools will be explicitly prioritized.\nIndustry Echo: Major Tech Firms Hitting the Brakes\nMeta is not alone. Token bill pressures are resonating across the tech industry.\nReports indicate Amazon recently shut down an internal AI leaderboard because employees were performing unnecessary operations to \"boost scores,\" causing a sharp rise in compute costs. Amazon has also begun using a metric called \"standardized deployment\" to evaluate whether engineers regularly use AI to generate useful code, rather than simply measuring token consumption.\nFurthermore, reports suggest Uber and ServiceNow exhausted their annual budgets for Anthropic tools early in 2026. ServiceNow is also monitoring daily employee usage to track and compress costs. Venture capital firms are setting AI usage caps for employees due to daily token fees often reaching thousands of dollars.\nAgainst this backdrop, rumors of OpenAI's price cuts carry deeper significance.\nReports state OpenAI is considering significant reductions in token fees charged to users, partly to get ahead of potential similar moves by Anthropic.\nOpenAI's CEO Sam Altman recently acknowledged that AI usage costs are \"a huge problem\" and stated the company would \"help people get more value for less money.\"\nThe timing of this statement is notable—OpenAI has confidentially filed for an IPO this week, and Anthropic is also on a countdown to its public listing. While price cuts can help win enterprise clients, they directly erode profit margins for both companies, which are currently losing billions due to the massive compute power required for their AI systems.\nToken Index Decline: What is the Market Repricing?\nCapital markets are already feeling the chill.\nThe Silicon Data LLM Token Spending Index has fallen for seven consecutive trading days as of June 11, marking its longest losing streak since January, with declines recorded in 11 of the past 12 days.\nThis index measures the average payment level per million tokens used across the market. It more than doubled since December last year and continued climbing until May 2026 before sharply reversing course.\nA macro strategist described this chart as \"the single most important chart in the entire market right now,\" warning that if token pricing continues to weaken, the trading logic for related investments from memory to broader hardware and data centers in this cycle could face an end.\nWall Street interpretations vary. JPMorgan characterizes the current trend as a \"minimal speed bump,\" while Citadel points out that the core constraint for AI adoption has shifted from \"the most capable model\" to \"cost and scarcity,\" with users accelerating their migration to cheaper models.\nBehind this divergence lies a more fundamental valuation question: Is the decline in token consumption a signal of peak AI demand, or the result of users rationally choosing lower-cost models? The answer will directly impact capital expenditure expectations and valuation logic for companies like Nvidia, cloud providers, and the entire AI hardware supply chain.\nA Turning Point for the Commercial Narrative\nFrom a broader perspective, Meta's move to restrict AI usage reflects a deeper shift in the generative AI commercialization narrative.\nOver the past three years, the AI industry has undergone a three-stage evolution: from subsidizing users to gain adoption, to monthly subscriptions hiding costs, to per-token billing triggering an enterprise bill crisis. Now, as the growth narrative of \"more token consumption is better\" reaches its limit, the industry faces not just a pricing decision, but a more fundamental challenge of business model reconstruction.\nMeta is investing a massive annual capital expenditure, partly to expand AI infrastructure including data centers, AI chips, and talent recruitment. Simultaneously, the company faces pressure from investors to generate visible returns from its enormous AI investments—Meta has already launched paid subscription tiers in Facebook, Instagram, and WhatsApp and plans to charge businesses using its AI business agents.\nHowever, if even Meta's internal AI usage costs have become unsustainable, the profitability prospects of its enterprise AI agent business also face scrutiny. For the entire industry, how to tell the next chapter of the commercialization story remains an unanswered question.","news_type":1,"symbols_score_info":{"AZYY":1,"AMZW":1,"AMZN":1,"AMZU":1,"METD":1,"FBYY":1,"FBL":1,"AMZY":1,"METU":1,"METW":1,"FBY":1,"AMZZ":1,"META":1,"USAW.SI":1,"AMZD":1,"AMZP":1}},"isVote":1,"tweetType":1,"viewCount":17,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":575124719849616,"gmtCreate":1781419564311,"gmtModify":1781427246953,"author":{"id":"4135831911794872","authorId":"4135831911794872","name":"AT69","avatar":"https://community-static.tradeup.com/news/default-avatar.jpg","crmLevel":13,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4135831911794872","idStr":"4135831911794872"},"themes":[],"title":"","htmlText":"Zuckerberg...monkey see..monkey do","listText":"Zuckerberg...monkey see..monkey do","text":"Zuckerberg...monkey see..monkey do","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/575124719849616","repostId":"1140497679","repostType":2,"repost":{"id":"1140497679","kind":"news","weMediaInfo":{"introduction":"Global Stock Market Deep Analysis","home_visible":1,"media_name":"Deep News","id":"1039043262","head_image":"https://community-static.tradeup.com/news/8296859682db4b478146245e72de1922"},"pubTimestamp":1781351372,"share":"https://ttm.financial/m/news/1140497679?lang=en_US&edition=fundamental","pubTime":"2026-06-13 19:49","market":"other","language":"en","title":"Following Amazon, Meta Imposes Limits on AI Usage. As Tech Giants Reel from Token Costs, Should AI Model Leaders Focus on Profit Margins?","url":"https://stock-news.laohu8.com/highlight/detail?id=1140497679","media":"Deep News","summary":"After Amazon.com (AMZN), Meta Platforms, Inc. (META) is also restricting AI usage, highlighting a critical and often overlooked industry conflict: the very logic of AI commercialization is being...","content":"<p>After <b>Amazon.com</b> (<b>AMZN</b>), <b>Meta Platforms, Inc.</b> (<b>META</b>) is also restricting AI usage, highlighting a critical and often overlooked industry conflict: the very logic of AI commercialization is being challenged by the soaring costs it generates.<br><br>\nAccording to reports, Meta sent an internal memo to approximately 6,000 employees this week, announcing it will set caps on employee token usage and build a real-time tracking platform to curb the exponential growth of internal AI costs.<br><br>\nThe memo stated that Meta's internal AI usage alone is projected to cost tens of billions of dollars by 2026. This move comes after Meta previously encouraged employees to integrate AI tools into their daily workflows, a strategy it is now forced to abruptly reverse.<br><br>\nConcurrently, reports indicate OpenAI is considering significant token price cuts to attract enterprise clients. Meanwhile, the Silicon Data LLM Token Spending Index, which reflects market willingness to pay for AI, has fallen for seven consecutive trading days—its longest losing streak since January this year.<br><br>\nThese combined signals have rapidly heightened market skepticism about the sustainability of AI commercialization. For investors, the core question is no longer whether AI demand exists, but rather: when tech giants themselves start scrutinizing their token bills, how much profit margin remains for the large AI model providers?<br><br>\n<b>The Uncontrolled Token Bill: Meta's Internal \"Spending Spree\"</b><br><br>\nThe direct catalyst for Meta tightening AI usage was a frenzy of token consumption fueled by internal incentives.<br><br>\nLast November, Meta explicitly told employees that demonstrating \"AI-driven work results\" would be a \"core performance requirement\" this year, with top performers receiving rewards. This directive led to an unintended consequence this spring: some employees engaged in a competition dubbed \"tokenmaxxing,\" vying for spots on an internal leaderboard called \"Claudeonomics,\" which ranked the top 250 employees by token usage.<br><br>\nInternal data shows employees consumed 60.2 trillion tokens in a 30-day period, with the figure later climbing to 73.7 trillion, leading to the leaderboard being taken down. Some employees reportedly instructed AI agents to run multiple tasks simultaneously to artificially inflate token consumption.<br><br>\nMeta's Chief Technology Officer Andrew Bosworth warned in an April memo that \"nobody should be using AI just to use AI,\" stressing that \"Token usage is not a measure of impact in any sense.\" However, mere warnings proved insufficient to halt the rising costs.<br><br>\n<b>Systematic Response: The AI Gateway and Internal Tool Substitution</b><br><br>\nFaced with runaway spending, Meta is implementing a systematic cost-control mechanism.<br><br>\nAccording to the internal memo, Meta has built a central dashboard called \"AI Gateway\" for real-time monitoring of company-wide AI usage and expenditure, with plans to add automated alerts for abnormal consumption spikes. The company intends to roll out these control tools to a broader employee base in the coming weeks and establish a more structured token budget allocation system by 2027.<br><br>\nSimultaneously, Meta is pushing employees to shift from third-party AI tools to in-house solutions. Its new Applied AI Engineering department is tasking engineers with improving the internal coding assistant MetaCode (formerly Devmate), aiming to reduce reliance on Anthropic's Claude, which is currently the primary tool for Meta's engineers in coding work.<br><br>\nIt's noted that Meta is not completely blocking access to third-party models; employees can still use tools from OpenAI, Anthropic, and Google, but internal tools will be explicitly prioritized.<br><br>\n<b>Industry Echo: Major Tech Firms Hitting the Brakes</b><br><br>\nMeta is not alone. Token bill pressures are resonating across the tech industry.<br><br>\nReports indicate Amazon recently shut down an internal AI leaderboard because employees were performing unnecessary operations to \"boost scores,\" causing a sharp rise in compute costs. Amazon has also begun using a metric called \"standardized deployment\" to evaluate whether engineers regularly use AI to generate useful code, rather than simply measuring token consumption.<br><br>\nFurthermore, reports suggest Uber and ServiceNow exhausted their annual budgets for Anthropic tools early in 2026. ServiceNow is also monitoring daily employee usage to track and compress costs. Venture capital firms are setting AI usage caps for employees due to daily token fees often reaching thousands of dollars.<br><br>\nAgainst this backdrop, rumors of OpenAI's price cuts carry deeper significance.<br><br>\nReports state OpenAI is considering significant reductions in token fees charged to users, partly to get ahead of potential similar moves by Anthropic.<br><br>\nOpenAI's CEO Sam Altman recently acknowledged that AI usage costs are \"a huge problem\" and stated the company would \"help people get more value for less money.\"<br><br>\nThe timing of this statement is notable—OpenAI has confidentially filed for an IPO this week, and Anthropic is also on a countdown to its public listing. While price cuts can help win enterprise clients, they directly erode profit margins for both companies, which are currently losing billions due to the massive compute power required for their AI systems.<br><br>\n<b>Token Index Decline: What is the Market Repricing?</b><br><br>\nCapital markets are already feeling the chill.<br><br>\nThe Silicon Data LLM Token Spending Index has fallen for seven consecutive trading days as of June 11, marking its longest losing streak since January, with declines recorded in 11 of the past 12 days.<br><br>\nThis index measures the average payment level per million tokens used across the market. It more than doubled since December last year and continued climbing until May 2026 before sharply reversing course.<br><br>\nA macro strategist described this chart as \"the single most important chart in the entire market right now,\" warning that if token pricing continues to weaken, the trading logic for related investments from memory to broader hardware and data centers in this cycle could face an end.<br><br>\nWall Street interpretations vary. JPMorgan characterizes the current trend as a \"minimal speed bump,\" while Citadel points out that the core constraint for AI adoption has shifted from \"the most capable model\" to \"cost and scarcity,\" with users accelerating their migration to cheaper models.<br><br>\nBehind this divergence lies a more fundamental valuation question: Is the decline in token consumption a signal of peak AI demand, or the result of users rationally choosing lower-cost models? The answer will directly impact capital expenditure expectations and valuation logic for companies like Nvidia, cloud providers, and the entire AI hardware supply chain.<br><br>\n<b>A Turning Point for the Commercial Narrative</b><br><br>\nFrom a broader perspective, Meta's move to restrict AI usage reflects a deeper shift in the generative AI commercialization narrative.<br><br>\nOver the past three years, the AI industry has undergone a three-stage evolution: from subsidizing users to gain adoption, to monthly subscriptions hiding costs, to per-token billing triggering an enterprise bill crisis. Now, as the growth narrative of \"more token consumption is better\" reaches its limit, the industry faces not just a pricing decision, but a more fundamental challenge of business model reconstruction.<br><br>\nMeta is investing a massive annual capital expenditure, partly to expand AI infrastructure including data centers, AI chips, and talent recruitment. Simultaneously, the company faces pressure from investors to generate visible returns from its enormous AI investments—Meta has already launched paid subscription tiers in Facebook, Instagram, and WhatsApp and plans to charge businesses using its AI business agents.<br><br>\nHowever, if even Meta's internal AI usage costs have become unsustainable, the profitability prospects of its enterprise AI agent business also face scrutiny. For the entire industry, how to tell the next chapter of the commercialization story remains an unanswered question.</p>","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>Following Amazon, Meta Imposes Limits on AI Usage. 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As Tech Giants Reel from Token Costs, Should AI Model Leaders Focus on Profit Margins?\n</h2>\n\n<h4 class=\"meta\">\n\n\n<a class=\"head\" href=\"https://laohu8.com/wemedia/1039043262\">\n\n\n<div class=\"h-thumb\" style=\"background-image:url(https://community-static.tradeup.com/news/8296859682db4b478146245e72de1922);background-size:cover;\"></div>\n\n<div class=\"h-content\">\n<p class=\"h-name\">Deep News </p>\n<p class=\"h-time\">2026-06-13 19:49</p>\n</div>\n\n</a>\n\n\n</h4>\n\n</header>\n<article>\n<p>After <b>Amazon.com</b> (<b>AMZN</b>), <b>Meta Platforms, Inc.</b> (<b>META</b>) is also restricting AI usage, highlighting a critical and often overlooked industry conflict: the very logic of AI commercialization is being challenged by the soaring costs it generates.<br><br>\nAccording to reports, Meta sent an internal memo to approximately 6,000 employees this week, announcing it will set caps on employee token usage and build a real-time tracking platform to curb the exponential growth of internal AI costs.<br><br>\nThe memo stated that Meta's internal AI usage alone is projected to cost tens of billions of dollars by 2026. This move comes after Meta previously encouraged employees to integrate AI tools into their daily workflows, a strategy it is now forced to abruptly reverse.<br><br>\nConcurrently, reports indicate OpenAI is considering significant token price cuts to attract enterprise clients. Meanwhile, the Silicon Data LLM Token Spending Index, which reflects market willingness to pay for AI, has fallen for seven consecutive trading days—its longest losing streak since January this year.<br><br>\nThese combined signals have rapidly heightened market skepticism about the sustainability of AI commercialization. For investors, the core question is no longer whether AI demand exists, but rather: when tech giants themselves start scrutinizing their token bills, how much profit margin remains for the large AI model providers?<br><br>\n<b>The Uncontrolled Token Bill: Meta's Internal \"Spending Spree\"</b><br><br>\nThe direct catalyst for Meta tightening AI usage was a frenzy of token consumption fueled by internal incentives.<br><br>\nLast November, Meta explicitly told employees that demonstrating \"AI-driven work results\" would be a \"core performance requirement\" this year, with top performers receiving rewards. This directive led to an unintended consequence this spring: some employees engaged in a competition dubbed \"tokenmaxxing,\" vying for spots on an internal leaderboard called \"Claudeonomics,\" which ranked the top 250 employees by token usage.<br><br>\nInternal data shows employees consumed 60.2 trillion tokens in a 30-day period, with the figure later climbing to 73.7 trillion, leading to the leaderboard being taken down. Some employees reportedly instructed AI agents to run multiple tasks simultaneously to artificially inflate token consumption.<br><br>\nMeta's Chief Technology Officer Andrew Bosworth warned in an April memo that \"nobody should be using AI just to use AI,\" stressing that \"Token usage is not a measure of impact in any sense.\" However, mere warnings proved insufficient to halt the rising costs.<br><br>\n<b>Systematic Response: The AI Gateway and Internal Tool Substitution</b><br><br>\nFaced with runaway spending, Meta is implementing a systematic cost-control mechanism.<br><br>\nAccording to the internal memo, Meta has built a central dashboard called \"AI Gateway\" for real-time monitoring of company-wide AI usage and expenditure, with plans to add automated alerts for abnormal consumption spikes. The company intends to roll out these control tools to a broader employee base in the coming weeks and establish a more structured token budget allocation system by 2027.<br><br>\nSimultaneously, Meta is pushing employees to shift from third-party AI tools to in-house solutions. Its new Applied AI Engineering department is tasking engineers with improving the internal coding assistant MetaCode (formerly Devmate), aiming to reduce reliance on Anthropic's Claude, which is currently the primary tool for Meta's engineers in coding work.<br><br>\nIt's noted that Meta is not completely blocking access to third-party models; employees can still use tools from OpenAI, Anthropic, and Google, but internal tools will be explicitly prioritized.<br><br>\n<b>Industry Echo: Major Tech Firms Hitting the Brakes</b><br><br>\nMeta is not alone. Token bill pressures are resonating across the tech industry.<br><br>\nReports indicate Amazon recently shut down an internal AI leaderboard because employees were performing unnecessary operations to \"boost scores,\" causing a sharp rise in compute costs. Amazon has also begun using a metric called \"standardized deployment\" to evaluate whether engineers regularly use AI to generate useful code, rather than simply measuring token consumption.<br><br>\nFurthermore, reports suggest Uber and ServiceNow exhausted their annual budgets for Anthropic tools early in 2026. ServiceNow is also monitoring daily employee usage to track and compress costs. Venture capital firms are setting AI usage caps for employees due to daily token fees often reaching thousands of dollars.<br><br>\nAgainst this backdrop, rumors of OpenAI's price cuts carry deeper significance.<br><br>\nReports state OpenAI is considering significant reductions in token fees charged to users, partly to get ahead of potential similar moves by Anthropic.<br><br>\nOpenAI's CEO Sam Altman recently acknowledged that AI usage costs are \"a huge problem\" and stated the company would \"help people get more value for less money.\"<br><br>\nThe timing of this statement is notable—OpenAI has confidentially filed for an IPO this week, and Anthropic is also on a countdown to its public listing. While price cuts can help win enterprise clients, they directly erode profit margins for both companies, which are currently losing billions due to the massive compute power required for their AI systems.<br><br>\n<b>Token Index Decline: What is the Market Repricing?</b><br><br>\nCapital markets are already feeling the chill.<br><br>\nThe Silicon Data LLM Token Spending Index has fallen for seven consecutive trading days as of June 11, marking its longest losing streak since January, with declines recorded in 11 of the past 12 days.<br><br>\nThis index measures the average payment level per million tokens used across the market. It more than doubled since December last year and continued climbing until May 2026 before sharply reversing course.<br><br>\nA macro strategist described this chart as \"the single most important chart in the entire market right now,\" warning that if token pricing continues to weaken, the trading logic for related investments from memory to broader hardware and data centers in this cycle could face an end.<br><br>\nWall Street interpretations vary. JPMorgan characterizes the current trend as a \"minimal speed bump,\" while Citadel points out that the core constraint for AI adoption has shifted from \"the most capable model\" to \"cost and scarcity,\" with users accelerating their migration to cheaper models.<br><br>\nBehind this divergence lies a more fundamental valuation question: Is the decline in token consumption a signal of peak AI demand, or the result of users rationally choosing lower-cost models? The answer will directly impact capital expenditure expectations and valuation logic for companies like Nvidia, cloud providers, and the entire AI hardware supply chain.<br><br>\n<b>A Turning Point for the Commercial Narrative</b><br><br>\nFrom a broader perspective, Meta's move to restrict AI usage reflects a deeper shift in the generative AI commercialization narrative.<br><br>\nOver the past three years, the AI industry has undergone a three-stage evolution: from subsidizing users to gain adoption, to monthly subscriptions hiding costs, to per-token billing triggering an enterprise bill crisis. Now, as the growth narrative of \"more token consumption is better\" reaches its limit, the industry faces not just a pricing decision, but a more fundamental challenge of business model reconstruction.<br><br>\nMeta is investing a massive annual capital expenditure, partly to expand AI infrastructure including data centers, AI chips, and talent recruitment. Simultaneously, the company faces pressure from investors to generate visible returns from its enormous AI investments—Meta has already launched paid subscription tiers in Facebook, Instagram, and WhatsApp and plans to charge businesses using its AI business agents.<br><br>\nHowever, if even Meta's internal AI usage costs have become unsustainable, the profitability prospects of its enterprise AI agent business also face scrutiny. For the entire industry, how to tell the next chapter of the commercialization story remains an unanswered question.</p>\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"LU2360106780.USD":"BGF WORLD TECHNOLOGY \"A4\" (USD) INC","LU1551013425.SGD":"Allianz Income and Growth Cl AMg2 DIS H2-SGD","LU1489326972.SGD":"First Eagle Amundi International AHS-MD SGD-H","LU1035775433.USD":"AB SICAV I - AMERICAN GROWTH PORTFOLIO \"AD\" (USD) INC","IE00B5949003.HKD":"JANUS HENDERSON GLOBAL TECHNOLOGY AND INNOVATION \"A\" (HKD) ACC","LU0949170772.SGD":"Blackrock Global Equity Income A6 SGD-H","LU1003077747.HKD":"BGF GLOBAL EQUITY INCOME \"A6\" (HKDHDG) INC","LU0130103400.USD":"Natixis Harris Associates Global Equity RA USD","LU0265550946.USD":"BGF SYSTEMATIC GLOBAL ENHANCED EQUITY YIELD \"A5\" (USD) INC","LU2083900584.USD":"HSBC GIF US INCOME FOCUSED \"AM2\" (USD) INC","IE00BJJMRX11.SGD":"Janus Henderson Balanced A Acc SGD","LU0738911758.USD":"Blackrock Global Equity Income A6 USD","LU1127390331.HKD":"AB SICAV I - 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(META) is also restricting AI usage, highlighting a critical and often overlooked industry conflict: the very logic of AI commercialization is being challenged by the soaring costs it generates.\nAccording to reports, Meta sent an internal memo to approximately 6,000 employees this week, announcing it will set caps on employee token usage and build a real-time tracking platform to curb the exponential growth of internal AI costs.\nThe memo stated that Meta's internal AI usage alone is projected to cost tens of billions of dollars by 2026. This move comes after Meta previously encouraged employees to integrate AI tools into their daily workflows, a strategy it is now forced to abruptly reverse.\nConcurrently, reports indicate OpenAI is considering significant token price cuts to attract enterprise clients. Meanwhile, the Silicon Data LLM Token Spending Index, which reflects market willingness to pay for AI, has fallen for seven consecutive trading days—its longest losing streak since January this year.\nThese combined signals have rapidly heightened market skepticism about the sustainability of AI commercialization. For investors, the core question is no longer whether AI demand exists, but rather: when tech giants themselves start scrutinizing their token bills, how much profit margin remains for the large AI model providers?\nThe Uncontrolled Token Bill: Meta's Internal \"Spending Spree\"\nThe direct catalyst for Meta tightening AI usage was a frenzy of token consumption fueled by internal incentives.\nLast November, Meta explicitly told employees that demonstrating \"AI-driven work results\" would be a \"core performance requirement\" this year, with top performers receiving rewards. This directive led to an unintended consequence this spring: some employees engaged in a competition dubbed \"tokenmaxxing,\" vying for spots on an internal leaderboard called \"Claudeonomics,\" which ranked the top 250 employees by token usage.\nInternal data shows employees consumed 60.2 trillion tokens in a 30-day period, with the figure later climbing to 73.7 trillion, leading to the leaderboard being taken down. Some employees reportedly instructed AI agents to run multiple tasks simultaneously to artificially inflate token consumption.\nMeta's Chief Technology Officer Andrew Bosworth warned in an April memo that \"nobody should be using AI just to use AI,\" stressing that \"Token usage is not a measure of impact in any sense.\" However, mere warnings proved insufficient to halt the rising costs.\nSystematic Response: The AI Gateway and Internal Tool Substitution\nFaced with runaway spending, Meta is implementing a systematic cost-control mechanism.\nAccording to the internal memo, Meta has built a central dashboard called \"AI Gateway\" for real-time monitoring of company-wide AI usage and expenditure, with plans to add automated alerts for abnormal consumption spikes. The company intends to roll out these control tools to a broader employee base in the coming weeks and establish a more structured token budget allocation system by 2027.\nSimultaneously, Meta is pushing employees to shift from third-party AI tools to in-house solutions. Its new Applied AI Engineering department is tasking engineers with improving the internal coding assistant MetaCode (formerly Devmate), aiming to reduce reliance on Anthropic's Claude, which is currently the primary tool for Meta's engineers in coding work.\nIt's noted that Meta is not completely blocking access to third-party models; employees can still use tools from OpenAI, Anthropic, and Google, but internal tools will be explicitly prioritized.\nIndustry Echo: Major Tech Firms Hitting the Brakes\nMeta is not alone. Token bill pressures are resonating across the tech industry.\nReports indicate Amazon recently shut down an internal AI leaderboard because employees were performing unnecessary operations to \"boost scores,\" causing a sharp rise in compute costs. Amazon has also begun using a metric called \"standardized deployment\" to evaluate whether engineers regularly use AI to generate useful code, rather than simply measuring token consumption.\nFurthermore, reports suggest Uber and ServiceNow exhausted their annual budgets for Anthropic tools early in 2026. ServiceNow is also monitoring daily employee usage to track and compress costs. Venture capital firms are setting AI usage caps for employees due to daily token fees often reaching thousands of dollars.\nAgainst this backdrop, rumors of OpenAI's price cuts carry deeper significance.\nReports state OpenAI is considering significant reductions in token fees charged to users, partly to get ahead of potential similar moves by Anthropic.\nOpenAI's CEO Sam Altman recently acknowledged that AI usage costs are \"a huge problem\" and stated the company would \"help people get more value for less money.\"\nThe timing of this statement is notable—OpenAI has confidentially filed for an IPO this week, and Anthropic is also on a countdown to its public listing. While price cuts can help win enterprise clients, they directly erode profit margins for both companies, which are currently losing billions due to the massive compute power required for their AI systems.\nToken Index Decline: What is the Market Repricing?\nCapital markets are already feeling the chill.\nThe Silicon Data LLM Token Spending Index has fallen for seven consecutive trading days as of June 11, marking its longest losing streak since January, with declines recorded in 11 of the past 12 days.\nThis index measures the average payment level per million tokens used across the market. It more than doubled since December last year and continued climbing until May 2026 before sharply reversing course.\nA macro strategist described this chart as \"the single most important chart in the entire market right now,\" warning that if token pricing continues to weaken, the trading logic for related investments from memory to broader hardware and data centers in this cycle could face an end.\nWall Street interpretations vary. JPMorgan characterizes the current trend as a \"minimal speed bump,\" while Citadel points out that the core constraint for AI adoption has shifted from \"the most capable model\" to \"cost and scarcity,\" with users accelerating their migration to cheaper models.\nBehind this divergence lies a more fundamental valuation question: Is the decline in token consumption a signal of peak AI demand, or the result of users rationally choosing lower-cost models? The answer will directly impact capital expenditure expectations and valuation logic for companies like Nvidia, cloud providers, and the entire AI hardware supply chain.\nA Turning Point for the Commercial Narrative\nFrom a broader perspective, Meta's move to restrict AI usage reflects a deeper shift in the generative AI commercialization narrative.\nOver the past three years, the AI industry has undergone a three-stage evolution: from subsidizing users to gain adoption, to monthly subscriptions hiding costs, to per-token billing triggering an enterprise bill crisis. Now, as the growth narrative of \"more token consumption is better\" reaches its limit, the industry faces not just a pricing decision, but a more fundamental challenge of business model reconstruction.\nMeta is investing a massive annual capital expenditure, partly to expand AI infrastructure including data centers, AI chips, and talent recruitment. Simultaneously, the company faces pressure from investors to generate visible returns from its enormous AI investments—Meta has already launched paid subscription tiers in Facebook, Instagram, and WhatsApp and plans to charge businesses using its AI business agents.\nHowever, if even Meta's internal AI usage costs have become unsustainable, the profitability prospects of its enterprise AI agent business also face scrutiny. For the entire industry, how to tell the next chapter of the commercialization story remains an unanswered question.","news_type":1,"symbols_score_info":{"AZYY":1,"AMZW":1,"AMZN":1,"AMZU":1,"METD":1,"FBYY":1,"FBL":1,"AMZY":1,"METU":1,"METW":1,"FBY":1,"AMZZ":1,"META":1,"USAW.SI":1,"AMZD":1,"AMZP":1}},"isVote":1,"tweetType":1,"viewCount":59,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":573833561872072,"gmtCreate":1781104382513,"gmtModify":1781104385688,"author":{"id":"4135831911794872","authorId":"4135831911794872","name":"AT69","avatar":"https://community-static.tradeup.com/news/default-avatar.jpg","crmLevel":13,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4135831911794872","idStr":"4135831911794872"},"themes":[],"title":"","htmlText":"<a href=\"https://ttm.financial/S/META\">$Meta Platforms, Inc.(META)$&nbsp;</a> Seems quite hopeless..let it crash another 50%","listText":"<a href=\"https://ttm.financial/S/META\">$Meta Platforms, Inc.(META)$&nbsp;</a> Seems quite hopeless..let it crash another 50%","text":"$Meta Platforms, Inc.(META)$ Seems quite hopeless..let it crash another 50%","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/573833561872072","isVote":1,"tweetType":1,"viewCount":270,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":570850439562848,"gmtCreate":1780399526703,"gmtModify":1780401092345,"author":{"id":"4135831911794872","authorId":"4135831911794872","name":"AT69","avatar":"https://community-static.tradeup.com/news/default-avatar.jpg","crmLevel":13,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4135831911794872","idStr":"4135831911794872"},"themes":[],"title":"","htmlText":"<a href=\"https://ttm.financial/S/META\">$Meta Platforms, Inc.(META)$&nbsp;</a> zuckerberg better buck up..else they may drop out from Mag 7 soon..","listText":"<a href=\"https://ttm.financial/S/META\">$Meta Platforms, Inc.(META)$&nbsp;</a> zuckerberg better buck up..else they may drop out from Mag 7 soon..","text":"$Meta Platforms, Inc.(META)$ zuckerberg better buck up..else they may drop out from Mag 7 soon..","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":4,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/570850439562848","isVote":1,"tweetType":1,"viewCount":434,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":562059431735416,"gmtCreate":1778253239519,"gmtModify":1778254702403,"author":{"id":"4135831911794872","authorId":"4135831911794872","name":"AT69","avatar":"https://community-static.tradeup.com/news/default-avatar.jpg","crmLevel":13,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4135831911794872","idStr":"4135831911794872"},"themes":[],"title":"","htmlText":"<a href=\"https://ttm.financial/S/META\">$Meta Platforms, Inc.(META)$&nbsp;</a> Mark zuckerberg only have himself to blame..let the price plunge another 50%","listText":"<a href=\"https://ttm.financial/S/META\">$Meta Platforms, Inc.(META)$&nbsp;</a> Mark zuckerberg only have himself to blame..let the price plunge another 50%","text":"$Meta Platforms, Inc.(META)$ Mark zuckerberg only have himself to blame..let the price plunge another 50%","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":3,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/562059431735416","isVote":1,"tweetType":1,"viewCount":923,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":562057435521656,"gmtCreate":1778252846643,"gmtModify":1778252849650,"author":{"id":"4135831911794872","authorId":"4135831911794872","name":"AT69","avatar":"https://community-static.tradeup.com/news/default-avatar.jpg","crmLevel":13,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4135831911794872","idStr":"4135831911794872"},"themes":[],"title":"","htmlText":"<a href=\"https://ttm.financial/S/META\">$Meta Platforms, Inc.(META)$&nbsp;</a> Looks like everyone is dumping this stock..","listText":"<a href=\"https://ttm.financial/S/META\">$Meta Platforms, Inc.(META)$&nbsp;</a> Looks like everyone is dumping this stock..","text":"$Meta Platforms, Inc.(META)$ Looks like everyone is dumping this stock..","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/562057435521656","isVote":1,"tweetType":1,"viewCount":641,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":529548091040736,"gmtCreate":1770305765424,"gmtModify":1770305768882,"author":{"id":"4135831911794872","authorId":"4135831911794872","name":"AT69","avatar":"https://community-static.tradeup.com/news/default-avatar.jpg","crmLevel":13,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4135831911794872","idStr":"4135831911794872"},"themes":[],"title":"","htmlText":"<a href=\"https://ttm.financial/S/GOOG\">$Alphabet(GOOG)$&nbsp;</a>Are we seeing start of market meltdown ?&nbsp;","listText":"<a href=\"https://ttm.financial/S/GOOG\">$Alphabet(GOOG)$&nbsp;</a>Are we seeing start of market meltdown ?&nbsp;","text":"$Alphabet(GOOG)$ Are we seeing start of market meltdown ?","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/529548091040736","isVote":1,"tweetType":1,"viewCount":1341,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":529545639826768,"gmtCreate":1770305178889,"gmtModify":1770305182452,"author":{"id":"4135831911794872","authorId":"4135831911794872","name":"AT69","avatar":"https://community-static.tradeup.com/news/default-avatar.jpg","crmLevel":13,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4135831911794872","idStr":"4135831911794872"},"themes":[],"title":"","htmlText":"<a href=\"https://ttm.financial/S/MSFT\">$Microsoft(MSFT)$&nbsp;</a> Markets plunging everyday..hope the selldown will end soon","listText":"<a href=\"https://ttm.financial/S/MSFT\">$Microsoft(MSFT)$&nbsp;</a> Markets plunging everyday..hope the selldown will end soon","text":"$Microsoft(MSFT)$ Markets plunging everyday..hope the selldown will end soon","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/529545639826768","isVote":1,"tweetType":1,"viewCount":1001,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":529189959504552,"gmtCreate":1770218933352,"gmtModify":1770218936735,"author":{"id":"4135831911794872","authorId":"4135831911794872","name":"AT69","avatar":"https://community-static.tradeup.com/news/default-avatar.jpg","crmLevel":13,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4135831911794872","idStr":"4135831911794872"},"themes":[],"title":"","htmlText":"<a href=\"https://ttm.financial/S/MSFT\">$Microsoft(MSFT)$&nbsp;</a> Those who short the stock are scrambling to cover their positions","listText":"<a href=\"https://ttm.financial/S/MSFT\">$Microsoft(MSFT)$&nbsp;</a> Those who short the stock are scrambling to cover their positions","text":"$Microsoft(MSFT)$ Those who short the stock are scrambling to cover their positions","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":8,"commentSize":1,"repostSize":2,"link":"https://ttm.financial/post/529189959504552","isVote":1,"tweetType":1,"viewCount":1870,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":521721971736888,"gmtCreate":1768408646413,"gmtModify":1768408649863,"author":{"id":"4135831911794872","authorId":"4135831911794872","name":"AT69","avatar":"https://community-static.tradeup.com/news/default-avatar.jpg","crmLevel":13,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4135831911794872","idStr":"4135831911794872"},"themes":[],"title":"","htmlText":"<a href=\"https://ttm.financial/S/META\">$Meta Platforms, Inc.(META)$&nbsp;</a> Maybe meta will slip to 500","listText":"<a href=\"https://ttm.financial/S/META\">$Meta Platforms, Inc.(META)$&nbsp;</a> Maybe meta will slip to 500","text":"$Meta Platforms, Inc.(META)$ Maybe meta will slip to 500","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":4,"repostSize":0,"link":"https://ttm.financial/post/521721971736888","isVote":1,"tweetType":1,"viewCount":2283,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0}],"defaultTab":"followers","isTTM":true}