The Pentagon's deadline for Anthropic was 5PM on February 24, 2026, set by Secretary Pete Hegseth, requiring unrestricted use of Claude for all legal purposes.
I Pay $200. I Use $12,500 in Tokens. AI Costs Crashed 850x and Subscriptions are Dead. | GMP EP03
AI token costs have crashed 850x since 2020 — what cost $60 per million tokens now costs 6 cents — and one host is burning $12,500 worth of tokens a month on a $200 subscription.
Mar 9, 2026
1:19:09
Difficulty: Intermediate
Played
God Mode Podcast
I Pay $200. I Use $12,500 in Tokens. AI Costs Crashed 850x and Subscriptions are Dead. | GMP EP03
AI token costs have crashed 850x since 2020 — what cost $60 per million tokens now costs 6 cents — and one host is burning $12,500 worth of tokens a month on a $200 subscription.
Mar 9, 2026
1:19:09
Difficulty: Intermediate
Played
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This episode
Cast
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Anthropic CEO discussed for missing the Pentagon deadline and for his EA philosophy and views on AI governance.
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OpenAI CEO who tweeted the Pentagon deal by 11PM on the same day Anthropic missed its deadline; described as fully capitalist in strategy.
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Discussed for investing $500M of FTX customer funds in Anthropic at a 13.5% stake that would now be worth ~$30B — and as a cautionary EA case study.
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Anthropic co-founder and COO, sister of Dario Amodei; her husband co-founded Open Philanthropy, deepening EA ties to Anthropic.
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Former Apple designer reportedly partnering with Sam Altman on an AI device; speculated by hosts to potentially ship with Claude Code pre-installed.
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Facebook co-founder and Open Philanthropy funder; a major early backer of Anthropic and central node in the EA-Anthropic network.
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US Secretary of Defense who gave Anthropic CEO Dario Amodei a hard 5PM deadline to accept unrestricted military AI use, triggering the contract drama.
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Central to the episode: Anthropic's Pentagon contract refusal, its EA-aligned culture, Claude's market rise, and its pricing strategy are the dominant threads.
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Discussed as the beneficiary of Anthropic's Pentagon contract rejection and as a capitalist-first counterpart to Anthropic's EA-driven model.
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AI video generation startup growing explosively to 4.5M videos/day and on track for $1B ARR — contrasted with Icon.com's collapse.
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AI meeting/cheating app startup that misrepresented its ARR to TechCrunch, has pivoted multiple times, and is seen as emblematic of the AI hype cycle deflating.
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AI avatar startup funded by Peter Thiel and OpenAI that spent $12M on its domain and reportedly went bankrupt, cited as a cautionary mismanagement tale.
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Sam Bankman-Fried's collapsed crypto exchange; its $500M Anthropic investment using customer funds is central to the EA-Anthropic origin story.
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EA's largest philanthropic fund and one of Anthropic's earliest major backers; co-founded by Dustin Moskovitz and Dario Amodei's college roommate.
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Chip and RAM manufacturer up 250% in the past year, discussed as a key AI infrastructure beneficiary due to chip manufacturing demand.
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Memory storage company whose stock rose roughly 20x in a year, driven by AI infrastructure demand — cited as a missed-but-obvious investment.
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Anthropic's AI model, praised as best-in-class for developers; reached #1 in the App Store after the Pentagon story broke.
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Anthropic's agentic coding tool; accounts for 4% of GitHub commits and is projected to reach 20%; also discussed as the most-starred GitHub repo framework.
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Discussed as a 'sleeping giant' offering significantly cheaper token pricing than OpenAI or Anthropic, quietly gaining market share via free tiers.
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Vibe-coding tool discussed as an early-mover in AI-assisted app development whose improvements largely derive from underlying model advances at Anthropic.
This episode
Claims & Sources
2 / 20 cited (10%)
Factual claims made this episode, and whether a source was named.
Sam Altman announced via tweet by 11PM on February 27 that OpenAI had struck a deal with the Pentagon, the same evening Anthropic missed its deadline.
The Pentagon government contract signed with OpenAI is worth $200 million per year.
Claude was the number one app in the App Store in the week Anthropic refused the Pentagon contract.
ChatGPT downloads dropped by approximately 250% in the same period Claude surged to #1 in the App Store.
Sam Bankman-Fried invested $500 million in Anthropic in April 2022 using FTX customer funds, receiving a 13.5% equity stake that has since diluted to approximately 8%.
SBF's 8% diluted Anthropic stake would be worth approximately $30 billion at Anthropic's current valuation — enough to repay FTX creditors roughly three times over.
Anthropic is currently valued at approximately $380 billion and is consistently valued at roughly half of OpenAI's valuation.
AI token prices have fallen 850 times since 2020, from $60 per million tokens for GPT-3 DaVinci to 6 cents for open-source Llama 4.
OpenAI's frontier model token price dropped from $30 per million in Q1 2023 to $0.50 today; Anthropic's from $15 to $1; Google's from $7 to $0.07.
Ben pays $200/month for Claude Max but consumes roughly 500 million tokens per month — equivalent to approximately $12,500 at API pricing.
Claude Code accounts for approximately 4% of all GitHub commits and is projected to reach 20% by end of 2025.
Icon.com spent $12 million on its domain name, was funded by Peter Thiel and OpenAI, and has apparently gone bankrupt.
Higgs Field grew from 15 million users to generating 4.5 million videos per day and is on track for $1 billion in ARR.
Cluely founder Roy publicly told TechCrunch the company was doing $7 million ARR when it was actually around $4–5 million, later issuing a public retraction.
GPT-5.4 scored 75% on the OSWorld computer-use benchmark, up from 47%, surpassing the human baseline.
A Mac Mini running a quantised 32-billion-parameter Llama model takes 34 seconds to write a 400-word section, while Claude Sonnet in the cloud completes the same task in 7 seconds.
SanDisk's stock rose from a low of approximately $30 to $600 — roughly a 20x gain — within the past year, driven by AI memory demand.
Samsung stock is up approximately 250% in the past year due to AI chip and RAM manufacturing demand.
Copper is up approximately 20% in the past year and is at an all-time high, breaking into price discovery mode.
TL;DR
Three AI practitioners dissect the week's biggest stories: Anthropic's rejection of a Pentagon surveillance contract (and OpenAI's same-day swoop to claim it), the deep ties between effective altruism and Anthropic's decision-making, and a jaw-dropping chart showing AI token costs have fallen 850x since 2020. They also debate whether running AI locally on a Mac Studio makes sense (verdict: not yet), the collapse of AI avatar startup Icon.com versus Higgs Field's explosive growth, and GPT-5.4's surprising computer-use benchmark. Key takeaway: plan your AI system architecture before you build it, or you'll rebuild it from scratch.
#AI government contracts
#Anthropic ethics
#effective altruism
#token cost deflation
#open-source AI models
#AI hardware local inference
#Claude Code agentic AI
#GPT-5.4 benchmarks
#AI subscription economics
#AI video generation
#SaaS competition AI era
#AI productivity debate
#chip demand investing
#AI avatar startups
#Pentagon AI deal
#Anthropic
#OpenAI
#Claude
#government contract
#Pentagon
#token cost
#AI pricing
#open source AI
#Claude Code
#GPT-5.4
#AI hardware
#Mac Studio
#Higgs Field
#SanDisk
#Samsung
#vibe coding
#AI agents
#subscription model
#Gemini
2 minute taster
The 850x Token Price Crash That Changes Everything
AI token costs have fallen 850 times since 2020. What cost $60 per million tokens with GPT-3 now costs 6 cents with open-source Llama 4. It's not just cheaper — the models are dramatically smarter. Every industry bottleneck unlocked by intelligence is now also being unlocked by near-zero cost.
$200 Subscription, $12,500 in Actual Tokens — The Subscription Is Already Dead
Ben pays $200/month for Claude Max but burns roughly 500 million tokens a month — equivalent to $12,500 at API rates. AI providers priced subscriptions like a normal buffet, but developers are now taking entire restaurants' worth of food home. The OAuth crackdown from Anthropic and Google is the inevitable response.
Why Anthropic Walked Away From the Pentagon Deal
The Pentagon gave Anthropic a hard 5PM deadline to accept unrestricted military use of Claude. Dario was in meetings and missed it. By 11PM, Sam Altman had tweeted a done deal with OpenAI. What looked like a principled stance was also, at least partly, a scheduling failure — but the PR outcome for Anthropic was paradoxically positive.
Look closer
Three AI practitioners debate Anthropic's Pentagon contract rejection, OpenAI's government deal, effective altruism's grip on Anthropic, the 850x crash in token costs, and the real-world tradeoffs of running AI locally versus in the cloud.
Chapter list
- OAuth (Open Auth)
- An open standard authentication protocol that lets third-party apps access a user's account without sharing passwords — here, used to tap a paid AI subscription outside its intended platform.
- Pre-training
- The initial, large-scale phase of training an AI model on massive datasets before any fine-tuning or specialisation; likened in the episode to going to school before an exam.
- Post-training
- Fine-tuning steps applied after pre-training — including RLHF and instruction-tuning — to align a model's behaviour; compared to coaching after school.
- RLHF
- Reinforcement Learning from Human Feedback: a technique for fine-tuning AI models by rewarding outputs rated positively by human evaluators.
- Effective Altruism (EA)
- A philosophy that uses evidence and reasoning to determine the most impactful ways to benefit others — central to Anthropic's founding culture and funding network.
- Open Philanthropy
- A major EA-aligned philanthropic fund co-founded by Dustin Moskovitz; one of Anthropic's earliest and largest backers.
- Claude Constitution
- Anthropic's published set of principles that govern Claude's behaviour — a strict guideline the model is not supposed to deviate from, closely tied to EA philosophy.
- Claude Code (OpenCLO / OpenClaw)
- Anthropic's agentic coding assistant that operates in terminals and IDEs; also used in the episode to refer to the broader open-source framework for routing AI tasks.
- Vibe coding
- A colloquial term for rapidly prototyping software by prompting AI models iteratively, relying on the AI to write most of the code.
- Distillation
- A technique where a smaller 'student' model is trained to mimic the outputs of a larger 'teacher' model, making open-source models competitive by learning from frontier closed-source ones.
- Agentic AI
- AI systems that can autonomously plan, take actions, and call tools over multiple steps to complete complex tasks without constant human prompting.
- VPS (Virtual Private Server)
- A virtualised cloud server that acts like a dedicated machine, giving users more control over their data than shared hosting or consumer AI apps.
- ARR (Annual Recurring Revenue)
- A standardised metric for subscription businesses representing the annualised value of recurring revenue — used here to gauge Higgs Field's growth trajectory.
- ASIC
- Application-Specific Integrated Circuit: a chip designed for one specific task; here used loosely to refer to specialised AI accelerators in the cloud.
- TPU
- Tensor Processing Unit: Google's custom AI chip, giving Google a full-stack hardware advantage over Anthropic and OpenAI who rely on third-party silicon.
- OSWorld
- A benchmark that tests an AI agent's ability to navigate and operate a real computer desktop — GPT-5.4 reportedly surpassed the human baseline on this test.
- Moore's Law
- The observation that the number of transistors on a chip doubles roughly every two years, roughly halving cost — invoked here to frame the 850x drop in AI token prices.
- FUD
- Fear, Uncertainty, and Doubt: negative sentiment or disinformation spread about a product or company, often to damage reputation or suppress adoption.
- Loss leader
- A product sold below cost to attract customers and gain market share, with the expectation of profiting later — applied here to AI subscription pricing.
- Quant (QUANT model)
- A quantised version of a large language model compressed to run on consumer hardware with reduced memory requirements, at some cost to output quality.
