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Replit Says It Has Stopped Working With Anthropic

Martin HollowayPublished 55m ago3 min readBased on 14 sources
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Replit Says It Has Stopped Working With Anthropic
Photo by Village Global / CC BY 2.0

Replit CEO and co-founder Amjad Masad said onstage at TechCrunch Disrupt 2026 that Replit is no longer working with Anthropic. The remark was reported on Oct. 16, 2026, the same day Masad appeared on the Disrupt Stage TechCrunch.

Masad pointed to three factors: cost, partnership and performance. Discussing Replit's current AI partners, he added, "I think ChatGPT is better now." Replit announced a partnership with OpenAI in August 2026.

A disputed break

That claim is contested in the same report. A person familiar with the Anthropic-Replit partnership, speaking anonymously, told TechCrunch the partnership was still in place. Neither account gave further detail on contract status, API usage, or deployment timelines.

How Replit used Claude

Until recently, Claude, Anthropic's family of AI models, was central to Replit's system. Under its partnership with Anthropic, Replit used Claude models to run its platform. A September 2026 Replit blog post named Anthropic's Claude Fable 5 and Claude Fable 5.1 as models running in Replit Agent's production environment. Agent is Replit's tool that turns plain-language requests into code.

That dependence built up over time. Replit integrated Claude into Agent for natural-language-to-code work, an integration Anthropic later said drove 10X revenue growth for Replit. Replit used Claude 3.5 Sonnet's computer use and UI navigation capabilities, the ability to operate on-screen controls, to develop a feature that evaluates apps. In its Claude 4 announcement, Anthropic said Replit reported improved precision and dramatic advancements for complex changes across multiple files.

Replit's setup extends beyond one lab. Replit announced a partnership bringing vibe coding, describing software in plain words and letting AI write it, to Microsoft Azure. It was among the first to evaluate Anthropic on Azure Databricks through the Mosaic AI gateway, a shared entry point for testing models. Replit uses Claude on Google Cloud's Vertex AI, Google's platform for running models, and on Google Cloud's Agent Platform to build and deploy software applications. Its AI adoption writing cites Anthropic's Building effective agents as a practical vocabulary for agent architecture including tools, retrieval, memory and evaluation.

A shift toward business customers

The reported switch comes alongside a change in Replit's customer mix. Masad said enterprise was 2% of Replit's revenue last year and 15% this year is enterprise contracts. He said more than 50% of Replit's revenue is B2B. Replit says it has more than 50 million creators.

Masad's planned Disrupt topic was his view of the future of programming and Replit's role in it. In a separate Disrupt session, he described that future as "self-driving companies" where AI agents handle day-to-day tasks TechCrunch. Masad has previously described Replit's advantage over Anthropic as its nimbleness and focus as a smaller company.

The broader context here is procurement leverage more than a single-vendor dispute. For teams running coding platforms, model choice is now a routing decision across price per token, inference latency or response delay, context handling, tool-use reliability, and test scores on multi-file edits. A platform with a growing enterprise base can push harder on all five, and can justify retuning prompts, harnesses and guardrails if another lab offers better unit economics or steadier throughput.

In my view, shorter allegiances are becoming normal. A September reference to Fable 5 and 5.1 in Agent does not settle October deployment, just as an August partnership announcement does not by itself explain October performance claims. When typing plain-language requests becomes the way software gets built, the company that controls distribution to developers and business buyers can swap the underlying model without asking users to change habits. That ability makes multi-model operation practical at scale, and it should keep pricing and partnership terms open to change.