Who is on each side · Part 12

Does the frontier model still command a price?

32 investors who disagree about The Model Is Not the Price. Each voice is attributed and paraphrased, dated where the date is known, with a link where one exists.

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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.

The price has left the model · Conviction Moderate (3/5)

Our Call takes the side “The filing sets the price”.

Read the full call

11 voices

The frontier is still paid

  1. Longriver

    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…

    Source

  2. Tae Kim

    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…

    Source

  3. Tae Kim

    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…

    Source

  4. Oguz Erkan

    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…

    Source

  5. Wyndo

    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.

  6. Wyndo

    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…

    Source

  7. Ren

    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…

    Source

  8. David George

    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.

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  9. David George

    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.

    Source

  10. Gaetano

    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…

  11. Market Sentiment

    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…

    Source

10 voices

Open weights set the price

  1. Michael Spencer

    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.

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  2. Michael Spencer

    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.

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  3. Steve Eisman

    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.

    Source

  4. Steve Eisman

    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.

    Source

  5. Le Shrub

    China is gaining ground in AI, with Chinese models now accounting for 66% of token share.

    Source

  6. Massif Capital

    Under 2% of tokens to a majority.

  7. Kevin Gee

    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…

  8. Deborah Folloni

    100,000 leads: $7 against $3,000.

  9. Charlie Hills

    Opus 5.5 is 60% cheaper than Astra, at $4 versus $10 per million input tokens.

    Source

  10. David George

    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…

    Source

11 voices

The filing sets the price

  1. Mia Silverio

    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…

    Source

  2. Mia Silverio

    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…

    Source

  3. 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…

    Source

  4. Michael Burry

    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…

    Source

  5. Michael Burry

    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…

  6. Warden Capital

    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…

    Source

  7. First Pacific Advisors

    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…

    Source

  8. Daniel Romero

    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…

    Source

  9. Daniel Romero

    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…

    Source

  10. Steve Eisman

    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.

    Source

  11. Steve Eisman

    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…

    Source

7 voices

Voices that cross sides

  1. Michael Spencer

    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…

    Source

  2. Michael Spencer

    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…

    Source

  3. David George

    Cheaper intelligence lifts all; at the model layer no edge sticks.

    Source

  4. Steve Eisman

    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.

    Source

  5. Tae Kim

    $70B of ARR at OpenAI; Huang's 80% of AI-native startups on open models.

    Source

  6. Le Shrub

    Chinese models at 66% of tokens; Karp's never-IPO call on OpenAI.

    Source

  7. Oguz Erkan

    The dollars with two labs, the volume leaving, fragmentation in 3-5 years.

    Source

Notes

Not a disagreement.

Where two voices only seem to differ, or where the thread runs back to an earlier Part.

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.

What would settle it

The dated tests.

The same tests the story set, on the Docket; results land on the Results page.

  1. 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 Pending

  2. 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 Pending

  3. 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 Pending

  4. 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 Pending

  5. 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 Pending

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.