How DeepStack settles a question · Part 12
Does the frontier model still command a price?
From Part 12: The Model Is Not the Price. 32 voices on 3 sides, attributed and dated; the DeepStack Call with its history; 5 dated tests that settle it; the results as they come in.
The DeepStack callMixed
A frontier model no longer commands a price per token for long. The lab still does, and only a prospectus says what that price is worth.
Our Call takes the side “The filing sets the price”.
Call history
- v1The price has left the modelConviction Moderate (3/5)Side: The filing sets the priceFirst call, with the story.
11 voices
The frontier is still paid
Reported revenue acceleration at the two leading model companies — an annualised run-rate said to go from USD 1 billion at end-2024 to USD 9 billion at end-2025 to almost USD 50 billion in May this year at Anthropic, with a similar trajectory at…
Tae Kim anticipates a close back-and-forth for model leadership between OpenAI and Anthropic over the next six months, expects another Anthropic model release before or around its IPO, and predicts both American frontier labs should do great once…
Tae Kim argues the earlier media consensus that OpenAI had fallen too far behind Anthropic was wrong, and that OpenAI pivoted resources to agentic coding after Anthropic's December lead, largely caught up by April, and arguably surpassed Anthropic…
Oguz Erkan says the concentration of the LLM market is still unknown: OpenAI and Anthropic take the lion's share of token dollars but their share of token volume has been declining, so the LLM market could be far more fragmented in 3-5 years, which…
Wyndo believes an always-on agent should run on the most capable model available, which is why they consider it fitting that ChatGPT's Dots runs on GPT-6 Astra.
Wyndo recommends trying open-weight models if a user keeps hitting usage limits on Claude or ChatGPT, or wants to lower the cost of certain tasks, since some work may run well on an open-weight model while saving the subscription for tasks where…
What actually fell is cost per completed job rather than cost per token: against Sol, Astra finishes Terminal-Bench 4.0 tasks at roughly 9% lower estimated API cost per task and OSWorld 2.0 tasks in about 47% less time, so the relevant demand…
They judge the switching-cost lever basically unavailable because the AI frontier is a Red Queen's Race at the model layer, with swapping between models easy down to task-by-task switching and everyone improving continuously.
They say a pretty small group uses AI rampantly for everything and a somewhat larger group uses ChatGPT regularly, meaning most people have not yet been awakened as customers, and they think OpenAI understands how to do it.
Criteo launched an Agentic Commerce Recommendation Service letting AI systems use Criteo's commerce intelligence to rank products, and OpenAI selected Criteo as its first advertising technology partner for ChatGPT Ads, with more than 2,000 brands…
Based on their capex sustainability model, Market Sentiment estimates that next year's ~$1.2T+ of AI capex should drive ~$2T of incremental revenue, which they say will only be a fraction of the total incremental revenue AI generates as a business…
10 voices
Open weights set the price
Chinese AI models captured a majority share of 57% to 67% of total token usage on the OpenRouter developer platform by September 2026, eroding OpenAI's token marketshare even as OpenAI subsidizes its new cheaper GPT-6.1 Sol model.
Anthropic is far ahead of OpenAI pre-IPO, both in model quality and ARR, and that lead should only accelerate with IPO proceeds heading into its November IPO.
OpenAI's price cut on its GPT model, combined with a reported tenfold jump in usage, looks like the beginning of a price war in AI services.
Steve says the AI story probably continues as long as token growth keeps rising, and identifies a price war between Anthropic, OpenAI and the Chinese models as the main risk that could change it.
China is gaining ground in AI, with Chinese models now accounting for 66% of token share.
Under 2% of tokens to a majority.
China is releasing open frontier models not despite state involvement, but because an open frontier is how you seed an ecosystem, win the developer base, and move the world's default tech stack onto a Chinese one, motivated by technological…
100,000 leads: $7 against $3,000.
Opus 5.5 is 60% cheaper than Astra, at $4 versus $10 per million input tokens.
So far, neither compute nor model advancements have been a zero-sum game: better, cheaper intelligence is accruing value to the entire ecosystem, with both older chips and models retaining substantial value well past the expiration dates the bears…
11 voices
The filing sets the price
Anthropic's expected ~$2 trillion IPO valuation is not justified by its numbers, given that it would need $1.2 trillion in annual revenue within 10 years (per Aswath Damodaran) to justify that valuation while the entire current AI products and…
Anthropic's customer concentration is a risk for its $2 trillion valuation: nearly a quarter of its 2025 revenue came from two customers and 47% of sales ran through Amazon and Google, which is an acceptable problem for a small company but not for…
Distillate Capital Partners LLC
Circular financing distorts the picture: hyperscalers and NVIDIA have committed roughly $180 billion to OpenAI and Anthropic, which pledge about $1.1 trillion of compute spending back to them against far smaller revenues, and $53 billion of…
Alphabet's reported 112% Google Cloud backlog growth is suspect because a new category of unknown size — TPU system sales contracts — was added to cloud backlog in the last six months, and one of the largest TPU customers is Anthropic, in which…
Aggregate purchase commitments, future leases, guarantees backing third-party debt, and various off-balance sheet potential liabilities across the hyperscalers total about $3 trillion, pointing toward a couple more years of record AI data center…
Warden Capital argues the AI investment cycle cannot earn a reasonable return absent AGI within a few years: at roughly $700 billion per year of investment, model providers would need about $1 trillion in annual end AI revenue by 2029, ramping…
Global AI spending is projected to reach 2.59 trillion dollars in 2026, and to achieve even a relatively low unlevered return on investment would require 207 billion dollars in after-tax income per year starting immediately, which the portfolio…
Although SpaceX reports AI infrastructure payback periods of less than one year, maintaining a one-year payback across the entire hypothetical 2027 buildout would require $1.9-2.28 trillion in annual compute payments, and if AI labs footed that…
OpenAI's combined annualized revenue with Anthropic reached $105 billion (OpenAI $40 billion, Anthropic $65 billion) in July 2026, which is nowhere near the figure needed to support the modeled 2027 buildout, and this understates the true gap since…
Anthropic looks likely to file for an IPO soon, and it will want to do that while token usage numbers are still near their peak, before the picture gets less flattering.
The AI trade's foundations are shaky because roughly seventy percent of the hyperscalers' AI revenue traces back to just two customers, OpenAI and Anthropic, both of which are burning enormous amounts of cash, so if either stumbles the entire…
7 voices
Voices that cross sides
OpenAI is in deep trouble in 2027 due to pressure in consumer AI from Meta and SpaceXAI, pressure from Chinese open-source models on cost and token marketshare, and being late to IPO while being overtaken in ARR and growth by Anthropic in…
Michael Spencer argues that in 2026 Chinese open-weight models are taking serious market share from incumbents like OpenAI and Anthropic, because the Chinese labs are only a few months behind the frontier and shortening release gaps mean even…
Cheaper intelligence lifts all; at the model layer no edge sticks.
Oracle's remaining performance obligations of $664 billion are concerning because roughly 50% come from OpenAI, a company burning massive cash, making Oracle over-reliant on OpenAI's solvency.
$70B of ARR at OpenAI; Huang's 80% of AI-native startups on open models.
Chinese models at 66% of tokens; Karp's never-IPO call on OpenAI.
The dollars with two labs, the volume leaving, fragmentation in 3-5 years.
Where they cross
Who answers whom.
The specific points where one voice meets another: the same evidence read two ways, or the same mechanism with a different sign.
Michael Spencer contradicts Tae Kim on evidence
Michael Spencer contradicts Tae Kim on evidence.
Michael Spencer contradicts Le Shrub on evidence
Michael Spencer contradicts Le Shrub on evidence.
Michael Spencer qualifies Wyndo on condition
Michael Spencer qualifies Wyndo on condition.
Michael Spencer qualifies Oguz Erkan on evidence
Michael Spencer qualifies Oguz Erkan on evidence.
Michael Spencer contradicts Le Shrub on premise
Michael Spencer contradicts Le Shrub on premise.
Michael Spencer qualifies Tae Kim on evidence
Michael Spencer qualifies Tae Kim on evidence.
David George qualifies Michael Spencer on mechanism
David George qualifies Michael Spencer on mechanism.
Michael Spencer qualifies Tae Kim on condition
Michael Spencer qualifies Tae Kim on condition.
David George qualifies Steve Eisman on mechanism
David George qualifies Steve Eisman on mechanism.
Michael Spencer contradicts Wyndo on evidence
Michael Spencer contradicts Wyndo on evidence.
Michael Spencer contradicts David George on mechanism
Michael Spencer contradicts David George on mechanism.
Kevin Gee contradicts David George on mechanism
Kevin Gee contradicts David George on mechanism.
Tae Kim contradicts Michael Spencer on premise
Tae Kim contradicts Michael Spencer on premise.
Michael Spencer qualifies David George on mechanism
Michael Spencer qualifies David George on mechanism.
Gaetano qualifies Oguz Erkan on condition
Gaetano qualifies Oguz Erkan on condition.
David George qualifies Michael Spencer on condition
David George qualifies Michael Spencer on condition.
Daniel Romero contradicts Market Sentiment on evidence
Daniel Romero contradicts Market Sentiment on evidence.
Longriver contradicts Warden Capital on evidence
Longriver contradicts Warden Capital on evidence.
Longriver contradicts First Pacific Advisors on evidence
Longriver contradicts First Pacific Advisors on evidence.
Longriver contradicts Distillate Capital Partners LLC on evidence
Longriver contradicts Distillate Capital Partners LLC on evidence.
Michael Burry qualifies Daniel Romero on evidence
Michael Burry qualifies Daniel Romero on evidence.
Michael Burry contradicts Market Sentiment on evidence
Michael Burry contradicts Market Sentiment on evidence.
Gaetano qualifies Mia Silverio on condition
Gaetano qualifies Mia Silverio on condition.
What settles it
The dated tests.
The tests the story set, each with its specification where the owner has written one; on the Docket, resolved on the Results page.
Alphabet, Microsoft and Meta report, and the Fed decides the same day: whether the TPU system sales inside Google Cloud's backlog get a size, and whether Cloud growth holds near the second quarter's 82% without them.
Part 12: The Model Is Not the Price Pendingp12-t01
- Question
- Did Alphabet, in its third-quarter 2026 results of October 28, 2026 (the earnings release, the 10-Q or the call), state a size for the TPU system sales contracts inside Google Cloud's backlog?
- Source
- Alphabet Q3 2026 earnings release, call transcript and Form 10-Q (SEC EDGAR, CIK 1652044)
- Rule
- Confirmed if the release, the 10-Q or the call transcript gives a dollar amount, or a share of the Cloud backlog, for TPU system sales contracts or for the Anthropic contracts; refuted if the quarter is reported with no such figure. Google Cloud's growth rate is read alongside (the Part watches whether it holds near the second quarter's 82% without those contracts) but does not decide the test.
- If the source is late, revised or silent
- A size given only as a range wider than two to one, or given for a period other than the backlog at quarter end, is inconclusive, reviewed by the owner. A report delayed past November 15, 2026 is inconclusive.
Amazon reports: it does not break Anthropic out, so the test is what AWS discloses about its largest customers, against Silverio's October 5 count of 47% of Anthropic's sales through Amazon and Google.
Part 12: The Model Is Not the Price Pendingp12-t02
- Question
- Did Amazon, in its third-quarter 2026 results of October 29, 2026 (the earnings release, the 10-Q or the call), disclose a customer or a group of customers at 10% or more of AWS revenue, or quantify Anthropic's share of AWS sales?
- Source
- Amazon Q3 2026 earnings release, call transcript and Form 10-Q (SEC EDGAR, CIK 1018724)
- Rule
- Confirmed if the concentration note of the 10-Q, the release or the call names a customer or a group of customers at 10% or more of AWS revenue, or states Anthropic's share of AWS sales; refuted if the quarter is reported with no such disclosure. The figure is read against Silverio's October 5 count of 47% of Anthropic's sales running through Amazon and Google.
- If the source is late, revised or silent
- A concentration disclosure given only for Amazon as a whole, without an AWS figure, is inconclusive, reviewed by the owner. A report delayed past November 15, 2026 is inconclusive.
Anthropic's listing, Part 10's test as the Docket states it: a registration statement with audited revenue, net loss and customer concentration public on EDGAR, or shares trading; a confidential draft without an EDGAR filing is inconclusive.
Part 12: The Model Is Not the Price Pendingp12-t03
Specification pending
Nvidia reports: whether it names the labs among its largest customers, against Eisman's September 21 count of roughly 70% of the hyperscalers' AI revenue from the two.
Part 12: The Model Is Not the Price Pendingp12-t04
- Question
- Did Nvidia, in its third-quarter fiscal 2027 results of November 18, 2026 (the earnings release, the 10-Q or the call), name OpenAI or Anthropic as a customer at 10% or more of revenue, or state the two labs' share of its revenue?
- Source
- Nvidia Q3 FY2027 earnings release, call transcript and Form 10-Q (SEC EDGAR, CIK 1045810)
- Rule
- Confirmed if the concentration note of the 10-Q, the release or the call names either lab as a direct or indirect customer at 10% or more of revenue, or states a share of revenue for the two labs together; refuted if the customers at 10% or more are described without naming either lab and no share for the labs is given. The figure is read against Eisman's September 21 count of roughly 70% of the hyperscalers' AI revenue coming from the two labs.
- If the source is late, revised or silent
- A disclosure that names a lab only as an indirect end customer without a share is inconclusive, reviewed by the owner. A report delayed past December 15, 2026 is inconclusive.
- When it files
The prospectus: the gross margin on inference, customer concentration against Silverio's October 5 count of a quarter from two customers, and revenue tied to investors against Distillate's July 15 count of $180 billion committed and $1.1 trillion pledged back.
Part 12: The Model Is Not the Price Pendingp12-t05
Specification pending
Sources (16)
- AI Supremacy - Gemini-4 Argon and the OpenRouter token count
- Longriver Investment Partners - Q2 2026 letter
- Prof G Markets - Anthropic wants $2 trillion anyway
- Distillate Capital Partners - Q2 2026 letter
- Capitalist Letters - Booking Holdings deep dive, the token dollars
- a16z - OpenAI understands something important and rare
- AI Supremacy - The era of personal super-intelligent agents
- Apollo - Chinese models vs. frontier models
- Shrubstack - Uncomfortable truths
- Potential Multibaggers - Vercel's open-model count
- a16z - State of Markets II
- First Pacific Advisors - Q2 2026 letter
- Warden Capital - Q2 2026 letter
- Market Sentiment - The next great AI trade is everything that isn't AI
- HyperTech Invest - The math behind the next AI rally
- AI Supremacy - A guide to Grok Bot 2026, the listing delay
Market data are as of the dates cited. Voices are paraphrased from public writing and attributed by name.
Analysis and opinion, not investment advice. Voices are paraphrased from public writing and attributed by name; DeepStack shows no score, ranking or accuracy for any person. Every question, one page each.