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Everyone’s obsessed with cheaper tokens. Meanwhile, enterprise AI spend keeps going up. Chamath says costs are doubling every 45 days for ~5% productivity gains. Glean’s founder says the metric that actually matters is cost per successful task, not cost per token.

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BILLIONAIRE CHAMATH SAID HIS COMPANY'S AI TOKEN COSTS ARE DOUBLING EVERY 45 DAYS... BUT PRODUCTIVITY IS UP JUST 5%. "OUR TOKEN COSTS ARE DOUBLING EVERY 45 DAYS." "OUR UPSIDE IS ESSENTIALLY FLAT." "I SUSPECT THAT IF YOU CAN GET OUT NOW, YOU SHOULD GET OUT NOW." THAT'S A BIG WARNING FOR THE AI INDUSTRY.

BILLIONAIRE CHAMATH SAID HIS COMPANY'S AI TOKEN COSTS ARE DOUBLING EVERY 45 DAYS... BUT PRODUCTIVITY IS UP JUST 5%. "OUR TOKEN COSTS ARE DOUBLING EVERY 45 DAYS." "OUR UPSIDE IS ESSENTIALLY FLAT." "I SUSPECT THAT IF YOU CAN GET OUT NOW, YOU SHOULD GET OUT NOW." THAT'S A BIG WARNING FOR THE AI INDUSTRY.

Vivek Sen

111,275 Aufrufe • vor 1 Monat

🚩 Chamath Says His Company’s Token Costs are Doubling Every 45 Days With Only a 5% Productivity Improvement “I don't know how many other companies will actually go through this reckoning now, but the point is, everybody in the next three or four years will for sure go through it.”

🚩 Chamath Says His Company’s Token Costs are Doubling Every 45 Days With Only a 5% Productivity Improvement “I don't know how many other companies will actually go through this reckoning now, but the point is, everybody in the next three or four years will for sure go through it.”

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🎙️ Want a full breakdown on why cost per token is a key metric for AI infrastructure TCO? We’re operating in a power-constrained world. Demand for intelligence is scaling faster than infrastructure can keep up—so metrics like cost per GPU hour or FLOPs per dollar don’t tell the full story. When it comes to TCO, Cost per Token is the metric that captures end-to-end performance across GPUs, CPUs, networking, software, and ecosystem making it the key driver of real profitability and scalability in AI. If you’re not measuring efficiency at the token level, you’re missing what actually drives cost. Watch the deep-dive conversation with Dr. Gerro Prinsloo , Nader Khalil and Carter Abdallah, live on the NVIDIA YouTube channel.

🎙️ Want a full breakdown on why cost per token is a key metric for AI infrastructure TCO? We’re operating in a power-constrained world. Demand for intelligence is scaling faster than infrastructure can keep up—so metrics like cost per GPU hour or FLOPs per dollar don’t tell the full story. When it comes to TCO, Cost per Token is the metric that captures end-to-end performance across GPUs, CPUs, networking, software, and ecosystem making it the key driver of real profitability and scalability in AI. If you’re not measuring efficiency at the token level, you’re missing what actually drives cost. Watch the deep-dive conversation with Dr. Gerro Prinsloo , Nader Khalil and Carter Abdallah, live on the NVIDIA YouTube channel.

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Chamath reveals his company's AI token costs are doubling every 45 days but productivity is only up 5% "I sat down with my CTO today, I said how are we doing on token spend. And he said the most incredible thing, he said right now, our token costs are doubling every 45 days. I said well what is the downstream productivity? And he said maybe 5% max." "So my costs are doubling every 45 days, my upside is essentially flat. He said honestly, what we're finding out is that you need to use a lot more tokens to get to this next iteration of improvement because we've effectively already asymptoted." "We're going to take a step back and try to figure out what to do. I don't know how many other companies will actually go through this reckoning now, but the point is everybody in the next three or four years will for sure go through it." "I suspect that if you can get out now, you should get out now before all of that starts to seep into the water table. Because I think that's probably what allows you to get out at a huge price and raise a huge amount of money."

Chamath reveals his company's AI token costs are doubling every 45 days but productivity is only up 5% "I sat down with my CTO today, I said how are we doing on token spend. And he said the most incredible thing, he said right now, our token costs are doubling every 45 days. I said well what is the downstream productivity? And he said maybe 5% max." "So my costs are doubling every 45 days, my upside is essentially flat. He said honestly, what we're finding out is that you need to use a lot more tokens to get to this next iteration of improvement because we've effectively already asymptoted." "We're going to take a step back and try to figure out what to do. I don't know how many other companies will actually go through this reckoning now, but the point is everybody in the next three or four years will for sure go through it." "I suspect that if you can get out now, you should get out now before all of that starts to seep into the water table. Because I think that's probably what allows you to get out at a huge price and raise a huge amount of money."

dnap

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OpenAI says its new Jalapeño chip could dramatically cut the cost of AI. The company's VP of hardware Richard Ho says performance per watt is 1.8x to 4x better than existing chips - potentially translating into cheaper tokens for customers as it rolls into production

OpenAI says its new Jalapeño chip could dramatically cut the cost of AI. The company's VP of hardware Richard Ho says performance per watt is 1.8x to 4x better than existing chips - potentially translating into cheaper tokens for customers as it rolls into production

Bloomberg TV

60,423 Aufrufe • vor 1 Monat

Liquid AI (Liquid AI) CEO Ramin Hasani (Ramin) says: "We're bringing the cost of tokens to zero." "The axis was maximizing intelligence at all costs." Foundation models need to optimize across 3 axes: 1.) Intelligence and capability 2.) Efficiency and cost 3.) Substrate: where the intelligence actually runs "Efficiency is not an afterthought. Energy is not abundant." "If you maximize intelligence at all costs, that axis alone is not going to get you to the place that you want to go." "Efficiency and cost of intelligence as a first-class citizen, and not an afterthought." "Where does this intelligence system go? AI is majorly getting hosted in data centers, but you could also bring intelligence on phones, on laptops, on airplanes, on cars." "Imagine if it's not tokens that are actually important. It's just the outcome that actually matters." "Not just thinking about foundation models as the token machines that are generating money and revenue for the foundation model companies that are useless tokens, and getting them into the place where they can actually unlock true value for enterprises."

Liquid AI (Liquid AI) CEO Ramin Hasani (Ramin) says: "We're bringing the cost of tokens to zero." "The axis was maximizing intelligence at all costs." Foundation models need to optimize across 3 axes: 1.) Intelligence and capability 2.) Efficiency and cost 3.) Substrate: where the intelligence actually runs "Efficiency is not an afterthought. Energy is not abundant." "If you maximize intelligence at all costs, that axis alone is not going to get you to the place that you want to go." "Efficiency and cost of intelligence as a first-class citizen, and not an afterthought." "Where does this intelligence system go? AI is majorly getting hosted in data centers, but you could also bring intelligence on phones, on laptops, on airplanes, on cars." "Imagine if it's not tokens that are actually important. It's just the outcome that actually matters." "Not just thinking about foundation models as the token machines that are generating money and revenue for the foundation model companies that are useless tokens, and getting them into the place where they can actually unlock true value for enterprises."

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🚨 THE AI COST BUBBLE IS GETTING WORSE. Companies pushed employees to “tokenmaxx” and aggressively use AI tools to boost productivity scores, but agentic AI can consume up to 1,000x more tokens than normal AI queries. Now the same companies that hyped AI cost savings are discovering that heavy AI usage is actually exploding operating costs instead of reducing them.

🚨 THE AI COST BUBBLE IS GETTING WORSE. Companies pushed employees to “tokenmaxx” and aggressively use AI tools to boost productivity scores, but agentic AI can consume up to 1,000x more tokens than normal AI queries. Now the same companies that hyped AI cost savings are discovering that heavy AI usage is actually exploding operating costs instead of reducing them.

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Sam Altman says AI models will get exponentially more capable and cheaper per task History proves that as costs drop, demand explodes Even as models become efficient enough to run on our phones, the world's hunger for tokens will only increase "capitalism is doing its thing"

Sam Altman says AI models will get exponentially more capable and cheaper per task History proves that as costs drop, demand explodes Even as models become efficient enough to run on our phones, the world's hunger for tokens will only increase "capitalism is doing its thing"

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Gavin Baker: "Anthropic is roughly four times more capital efficient than OpenAI - they're growing really fast and they're not burning that much cash" this is him explaining why he thinks token efficiency decides who wins, why xAI has the lowest cost per token of anyone, and what a Tesla board member says is actually the most advanced AI in the world right now "an Anthropic model can give you a comparable quality answer to a Google model using half as many tokens - and each token is literally cost" "xAI has the lowest cost per token because they build data centers faster and at a lower cost than everyone, and they run GPUs at a higher utilization" Tesla board member Antonio Gracias: "Tesla actually is today the most advanced AI in the world - it does the most complex thing a human does, drive a car" bookmark & watch the full conversation ↓

Gavin Baker: "Anthropic is roughly four times more capital efficient than OpenAI - they're growing really fast and they're not burning that much cash" this is him explaining why he thinks token efficiency decides who wins, why xAI has the lowest cost per token of anyone, and what a Tesla board member says is actually the most advanced AI in the world right now "an Anthropic model can give you a comparable quality answer to a Google model using half as many tokens - and each token is literally cost" "xAI has the lowest cost per token because they build data centers faster and at a lower cost than everyone, and they run GPUs at a higher utilization" Tesla board member Antonio Gracias: "Tesla actually is today the most advanced AI in the world - it does the most complex thing a human does, drive a car" bookmark & watch the full conversation ↓

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⚡️ JUST IN: MUSK LAUNCHES GROK 4.5, CALLING IT "OPUS-CLASS" AI MODEL Musk just released Grok 4.5 on Grok Build, Cursor, and the SpaceXAI Console, calling it an "Opus-class" AI model. He says it is faster, more token-efficient and lower cost, with EU access expected by mid-July. Built on a 1.5 TRILLION parameter foundation model, it drops the same day as OpenAI's GPT-5.6. API pricing is $2 per million input tokens and $6 per million output tokens.

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A client accidentally spent $500M in one month on Claude. $16.6M per day. No usage controls. Chamath Palihapitiya on The All-In Podcast EP275: a Fortune-level company failed to set token limits. The bill arrived at end of month. A separate Fortune 20 company is 6 months into a $1B AI-driven OPEX reduction program. $200M in tokens spent. Minimal results. Microsoft is already canceling Claude enterprise licenses. David Sacks calls it a "meme" forming - that token spend is wasteful and the market is overcorrecting. For enterprise AI buyers: the companies building spend-control and measurable-ROI infrastructure now are positioned to capture budget as the backlash unfolds. Full enterprise spend breakdown and what it means for AI vendor pricing power on The All-In Podcast: Source: All-In Podcast -

A client accidentally spent $500M in one month on Claude. $16.6M per day. No usage controls. Chamath Palihapitiya on The All-In Podcast EP275: a Fortune-level company failed to set token limits. The bill arrived at end of month. A separate Fortune 20 company is 6 months into a $1B AI-driven OPEX reduction program. $200M in tokens spent. Minimal results. Microsoft is already canceling Claude enterprise licenses. David Sacks calls it a "meme" forming - that token spend is wasteful and the market is overcorrecting. For enterprise AI buyers: the companies building spend-control and measurable-ROI infrastructure now are positioned to capture budget as the backlash unfolds. Full enterprise spend breakdown and what it means for AI vendor pricing power on The All-In Podcast: Source: All-In Podcast -

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Introducing Entelligence AI Model Router, dynamic turn based routing trained on engineering tasks that cuts costs by over 50% Automatically route every coding turn to the model with the best balance of quality, latency, and cost. Escalate to frontier models when they’re actually needed Balanced mode reduces spend by 46% per session Eco mode helps teams save > 76%

Introducing Entelligence AI Model Router, dynamic turn based routing trained on engineering tasks that cuts costs by over 50% Automatically route every coding turn to the model with the best balance of quality, latency, and cost. Escalate to frontier models when they’re actually needed Balanced mode reduces spend by 46% per session Eco mode helps teams save > 76%

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10 repos that cut your ai agent token bill by up to 80% 1. microsoft/LLMLingua → cuts prompt size by up to 95% compresses prompts before the api call. 20x compression. published at EMNLP + ACL. near-zero quality loss. 6,100 stars 2. mem0ai/mem0 → replaces full conversation history in context stores what matters. retrieves only what's needed. 10,000 token history → 200 token memory. per agent. 54,800 stars 3. BerriAI/litellm → routes each call to the cheapest model simple task → haiku. complex task → sonnet. tracks cost per agent, per call, per day. 45,700 stars 4. run-llama/llama_index → replaces sending full documents rag: 100-page doc → 3 relevant chunks → same answer. 98% fewer tokens per query. 49,100 stars 5. chroma-core/chroma → replaces keyword search in full context vector store. finds the closest match. feeds only that. 50-200 tokens per query instead of thousands. 27,800 stars 6. letta-ai/letta → replaces infinite context window crashes paged memory for agents. loads only relevant memory. stops your agent from hitting limits and retrying. 22,400 stars 7. guidance-ai/guidance → cuts output token bloat by 30-50% structured generation. constrains model output natively. no more 100-token prompts to get json back. 21,400 stars 8. Aider-AI/aider → replaces pasting entire codebases builds a repo map. sends only files relevant to the task. not your whole project. just what the agent needs. 44,300 stars 9. openai/tiktoken → count tokens before you send know the exact cost before the api call happens. not after the bill arrives. 18,100 stars 10. simonw/ttok → hard cap on what gets sent cli tool: count tokens, truncate to budget limit. pipe any text in. get truncated output back. 389 stars most agents are expensive not because the model is expensive. because nobody checked what was being sent to it.

10 repos that cut your ai agent token bill by up to 80% 1. microsoft/LLMLingua → cuts prompt size by up to 95% compresses prompts before the api call. 20x compression. published at EMNLP + ACL. near-zero quality loss. 6,100 stars 2. mem0ai/mem0 → replaces full conversation history in context stores what matters. retrieves only what's needed. 10,000 token history → 200 token memory. per agent. 54,800 stars 3. BerriAI/litellm → routes each call to the cheapest model simple task → haiku. complex task → sonnet. tracks cost per agent, per call, per day. 45,700 stars 4. run-llama/llama_index → replaces sending full documents rag: 100-page doc → 3 relevant chunks → same answer. 98% fewer tokens per query. 49,100 stars 5. chroma-core/chroma → replaces keyword search in full context vector store. finds the closest match. feeds only that. 50-200 tokens per query instead of thousands. 27,800 stars 6. letta-ai/letta → replaces infinite context window crashes paged memory for agents. loads only relevant memory. stops your agent from hitting limits and retrying. 22,400 stars 7. guidance-ai/guidance → cuts output token bloat by 30-50% structured generation. constrains model output natively. no more 100-token prompts to get json back. 21,400 stars 8. Aider-AI/aider → replaces pasting entire codebases builds a repo map. sends only files relevant to the task. not your whole project. just what the agent needs. 44,300 stars 9. openai/tiktoken → count tokens before you send know the exact cost before the api call happens. not after the bill arrives. 18,100 stars 10. simonw/ttok → hard cap on what gets sent cli tool: count tokens, truncate to budget limit. pipe any text in. get truncated output back. 389 stars most agents are expensive not because the model is expensive. because nobody checked what was being sent to it.

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RFK Jr: “What we’re finding is that it’s actually cheaper, counter intuitively, to eat well than it is to eat processed food.” “The meals that are now terrible, that are given to our military, cost $18 a day per soldier.” “We’re changing the military right now.” “We’re going into 20 bases with Chef Robert Irvine.” “He’s feeding them fresh whole foods for $10 a day.” “So you don’t need to spend more money.” “You just need to be smarter.” “We’re going to make sure there is fresh food in every jurisdiction.”

RFK Jr: “What we’re finding is that it’s actually cheaper, counter intuitively, to eat well than it is to eat processed food.” “The meals that are now terrible, that are given to our military, cost $18 a day per soldier.” “We’re changing the military right now.” “We’re going into 20 bases with Chef Robert Irvine.” “He’s feeding them fresh whole foods for $10 a day.” “So you don’t need to spend more money.” “You just need to be smarter.” “We’re going to make sure there is fresh food in every jurisdiction.”

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a16z's David George says the real economy has barely begun adopting AI, while the top 1% in one dataset already spend $7,000 per employee per month: "Part of the thing that we're monitoring, which makes us extremely bullish about AI, is just actual diffusion into the real economy." "The median company in the US is spending $12 per employee on AI per month. The top 1% of the dataset that we've seen is spending $7,000 per employee on AI per month." "Not only have we had limited diffusion beyond coding, but if you just look at the shape of who is consuming tokens and actually getting real value out of AI today, we're super early. The most cutting-edge banks are probably doing 1% of headcount cost on AI tools." "The reason this makes me very bullish is these are the fastest-growing companies we've ever seen, of all time. They're adding more revenue per month than the mega-cap tech companies." "And yet it's probably on the back of adoption of 10 million users, maybe 20, maybe 30 max. And I think it's going to transform the way we do a lot of work." David George

a16z

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Most Web3 wallets are full of dust. Small balances that are not worth swapping one by one, and not worth the time it takes to check whether each token is real, legit and even swappable. Dustswap does that check for you. It surfaces the tokens that actually hold value and sweeps them into one useful token in a single transaction. Up to 10 tokens per transaction, and up to 20 with the @baseapp wallet. Do not let your dust sit there doing nothing.

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