Anthropic is increasing the amount of information that enterprise customers can send to Claude in a single prompt, part of an effort to attract more developers to the company’s popular AI coding models.
For Anthropic’s API customers, the company’s Claude Sonnet 4 AI model now has a 1 million token context window — meaning the AI can handle requests as long as 750,000 words, more than the entire “Lord of the Rings” trilogy, or 75,000 lines of code. That’s roughly five times Claude’s previous limit (200,000 tokens), and more than double the 400,000 token context window offered by OpenAI’s GPT-5.
Long context will also be available for Claude Sonnet 4 through Anthropic’s cloud partners, including on Amazon Bedrock and Google Cloud’s Vertex AI.
Anthropic has built one of the largest enterprise businesses among AI model developers, largely by selling Claude to AI coding platforms such as Microsoft’s GitHub Copilot, Windsurf, and Anysphere’s Cursor. While Claude has become the model of choice among developers, GPT-5 may threaten Anthropic’s dominance with its competitive pricing and strong coding performance. Anysphere CEO Michael Truell even helped OpenAI announce the launch of GPT-5, which is now the default AI model for new users in Cursor.
Anthropic’s product lead for the Claude platform, Brad Abrams, told TechCrunch in an interview that he expects AI coding platforms to get a “lot of benefit” from this update. When asked if GPT-5 put a dent in Claude’s API usage, Abrams downplayed the concern, saying he’s “really happy with the API business and the way it’s been growing.”
Whereas OpenAI generates most of its revenue from consumer subscriptions to ChatGPT, Anthropic’s business centers around selling AI models to enterprises through an API. That’s made AI coding platforms a key customer for Anthropic and could be why the company is throwing in some new perks to attract users in the face of GPT-5.
Last week, Anthropic unveiled an updated version of its largest AI model, Claude Opus 4.1, which pushed the company’s AI coding capabilities a bit further.
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Generally speaking, AI models tend to perform better on all tasks when they have more context, but especially for software engineering problems. For example, if you ask an AI model to spin up a new feature for your app, it’s likely to do a better job if it can see the entire project, rather than just a small section.
Abrams also told TechCrunch that Claude’s large context window helps it perform better at long agentic coding tasks, in which the AI model is autonomously working on a problem for minutes or hours. With a large context window, Claude can remember all its previous steps in long-horizon tasks.
But some companies have taken large context windows to an extreme, claiming their AI models can process massive prompts. Google offers a 2 million token context window for Gemini 2.5 Pro, and Meta offers a 10 million token context window for Llama 4 Scout.
Some studies suggest there’s a limit to how effective large context windows can be; AI models are not great at processing those massive prompts. Abrams said that Anthropic’s research team focused on increasing not just the context window for Claude, but also the “effective context window,” suggesting that its AI can understand most of the information it’s given. However, he declined to reveal Anthropic’s exact techniques.
When prompts to Claude Sonnet 4 are over 200,000 tokens, Anthropic will charge more to API users, at $6 per million input tokens and $22.50 per million output tokens (up from $3 per million input tokens and $15 per million output tokens).
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