Near AI Cloud Adds Claude Sonnet 5.5 For Advanced Coding
NEAR Protocol's AI Cloud has added Anthropic's Claude Sonnet 5.5 to its model lineup, offering developers access to one of the most capable coding-focused AI models available today without re
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AnonymousCryptoCompass newsroom
September 30, 2026
2 min read
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NEAR Protocol's AI Cloud has added Anthropic's Claude Sonnet 5.5 to its model lineup, offering developers access to one of the most capable coding-focused AI models available today without requiring any changes to existing API integrations.
A Sharp Jump in Coding Performance
The headline number is hard to ignore. Sonnet 5.5 scores 70.6% on Terminal-Bench 4.0, an agentic coding evaluation, compared to Sonnet 5's 10.3%. That improvement reflects a meaningful shift in how the model handles complex, multi-step coding and agentic workloads. On CursorBench, which tests models on tasks from real Cursor coding sessions, its best score is within about two points of Opus 5.5.
The model supports a 1 million token context window with both image and text input. That context length makes it well suited for large codebases and long-running agent workloads where continuity across many files and instructions matters.
Access and Pricing on NEAR AI Cloud
Developers on NEAR AI Cloud can reach the model through the platform's unified gateway, meaning teams already using NEAR's API infrastructure do not need to rebuild existing integrations to take advantage of the new model.
Sonnet 5.5 is priced the same as Sonnet 5 at $2 per million input tokens and $10 per million output tokens, but it typically needs far fewer tokens to do the same work, costing up to 30% less per task than its predecessor.The new Sonnet model generates output more than 30% faster than its predecessor.
Claude Sonnet 5.5 is now available on all platforms, including Amazon Web Services, Google Cloud, and Microsoft Azure. Its addition to NEAR's AI Cloud extends that reach into the blockchain-native developer ecosystem, where teams are increasingly building AI-powered agents and decentralised applications that require reliable, scalable inference.
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