Strands claims near-parity with Claude Code and Codex on benchmarks, though it only moved coding agents and marked its own homework.
AWS has entered the open source agentic AI game, claiming its new Strands harness matches rivals on benchmarks while using around a quarter fewer tokens.
The Strands harness, as its name suggests, is built on AWS’ Strands Harness SDK, but is packaged up and ready to roll out of the box, either locally or deployed to work with whatever AI provider a customer prefers.
On top of being relatively plug-and-play in design, AWS claims the Strands harness achieved "nearly equal benchmark scores" versus Claude Code, Codex, and “other popular harnesses” when tested using the Harbor framework, distributed across multiple nodes of AWS’ own EC2 virtual servers for benchmarking tests.
Strands consumed 28 percent fewer tokens across six benchmark tests when compared to “Claude or GPT models,” claims AWS, and in some cases had better accuracy than other harnesses too.
AWS credits this performance to the Strands harness’ default prompt caching and context management settings. Per the announcement post, it defaults to truncating tool results over 1,500 tokens, automatically compacting its context window when it surpasses 85 percent, and automatically trying to recover context in overflow cases.