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Ramp's July file still has Anthropic ahead on business adoption, and the month's gain went its way too. The catch-up story rests on a list price and a data-retention notice.
The Investor · Invest desk
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Ramp's model-level percentages can be worked backwards into something the release does not state: the relative size of the two books. Fable 5 took 11.4% of Anthropic's model dollars [5] while generating about 75% of what GPT-5.6 Sol generated [7], and Sol accounted for 23% of OpenAI's model dollars [6]. That implies Anthropic's total model-attributed spend across Ramp's businesses runs about 1.5 times OpenAI's [17]. Apply the same arithmetic to tokens, using the two-to-one price gap Ramp cites [8], and Anthropic is ahead there too, by roughly 1.6 times [18]. Both ratios sit near the reported second-quarter revenue gap of $11.6 billion to $6.7 billion, or 1.7 to 1 [13][19].
So the leader on Ramp is losing at the margin, not at the level. And the margin moved for reasons that have little to do with which model is better. Ramp economist Ara Kharazian credits Sol's standing with developers, and attributes Fable 5's weak uptake to price plus data retention requirements imposed by regulators [3]. Fable 5 lists at about $10 per million tokens, twice Sol [8], and Anthropic drew complaints after telling Fable users it must hold their data for a month, according to TechCrunch [9]. A price and a retention clause are both things a vendor can change. A capability gap is not.
The catch-up carries a bill on OpenAI's side. A $12.3 billion second-quarter operating loss on $6.7 billion of revenue [13][14] implies roughly $19 billion of operating cost, or $2.84 spent for every dollar booked [16]. Anthropic recorded a small adjusted operating profit over the same period, according to SiliconAngle [14]. OpenAI's own account of the turn is internal and unaudited: CFO Sarah Friar told employees that July annualised recurring revenue had already passed the full second-quarter total, crediting the GPT-5.6 series, an enterprise agent called ChatGPT Work, and Codex [15].
There is one more limit on what this data can bear. Ramp sees only companies that run expenses through Ramp, which leaves out large enterprises on other spend-management platforms [12]. What it measures well is mid-market buying behaviour, and that behaviour is getting less loyal rather than more: paid AI adoption reached nearly 56% of tracked businesses in July from just over 50% in March, with momentum behind both vendors cooling as buyers try cheaper and open-source options [10]. A book that reprices this fast is not a vendor bet in any useful sense of the word.
Ranked by verification strength, evidence, and original report placement.
OpenAI CFO Sarah Friar told employees that annualized recurring revenue in July had already exceeded the company's full second-quarter total, crediting the GPT-5.6 model series, an enterprise agent called ChatGPT Work, and its Codex coding tool.
As of July, 43.5% of the more than 70,000 U.S. businesses tracked by Ramp paid for Anthropic subscriptions or tokens, up 1.1 percentage points from the prior month, while OpenAI reached 39.7%, gaining 0.23 percentage points.
Ramp economist Ara Kharazian posted on X that "GPT-5.6 Sol is really good, increasingly the choice for developers" and that "Fable 5, meanwhile, disappointed both in adoption and real-world application given price plus data retention requirements imposed by regulators."
Over the past month, Fable 5 accounted for only 6% of tokens businesses purchased from Anthropic and 11.4% of dollars spent on Anthropic models, according to Ramp.
OpenAI's GPT-5.6 Sol made up 25% of OpenAI tokens and 23% of OpenAI model spend among Ramp-tracked businesses.
In dollar terms, Fable 5 generated roughly 75% as much model-attributed spending as GPT-5.6 Sol in July, according to Ramp.
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Evidence-backed comparisons of source perspectives and observed adoption signals. Read the methodology
Which Builder, Operator, and Investor concerns the observed source mix emphasized—not a truth score.
Evidence, demonstrated adoption, hype gap, incentives, and confidence are assessed independently, each on its own current evidence. How these are measured.
One outlet relaying one vendor panel
All figures trace to a single publisher summarizing Ramp's panel plus secondhand reporting from TechCrunch, CNBC, WSJ, and SiliconAngle; no primary filing, Ramp report, or Anthropic/OpenAI document is in the cluster. The quantitative disclosures are specific and internally consistent, which lifts the score, but the central catch-up assertion is not backed by any published Q3 series and is contradicted by the one month of data shown.
Broad paid usage, thin uptake of the newest model
Adoption is unusually well quantified for this kind of story: nearly 56% of 70,000-plus tracked businesses pay for AI, 43.5% pay Anthropic and 39.7% pay OpenAI, and within-vendor model mixes are disclosed on both token and dollar bases. The panel is real spend, not intent. It is held below the top band because it covers only Ramp customers and because the newest models are still a minority of each vendor's mix.
Catch-up framing overstates the disclosed data
The framing ('OpenAI is gaining') runs ahead of what the cluster shows: Anthropic remains 3.8 points ahead on penetration, gained about 4.8 times more share in the month reported, and leads on implied panel spend, while the causal explanation rests on a list price and a retention notice rather than any measured capability or migration. The gap is moderate rather than severe because the underlying numbers are disclosed in the same article and the panel caveat is stated.
Vendor-panel data plus company self-reporting
The scoreboard comes from Ramp, a spend-management vendor whose economist publicly benefits from his panel being treated as the market's read on AI adoption, and the counterweight to Anthropic's revenue lead is an internal remark from OpenAI's CFO citing OpenAI's own products. Both are interested parties; neither is disinterested measurement, and the financial figures arrive through third-party outlets rather than filings.
Solid numbers, shaky conclusion
Confidence is moderate-low: the individual data points are precise, checkable, and arithmetically consistent, so the adoption picture can be relied on for the Ramp panel. The story's actual thesis, that OpenAI is catching up and that price was the lever, depends on an unpublished Q3 series, a single publisher, and secondhand financials, and one month of contrary movement sits inside the same article.
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1 article · August 26, 2026