AWS benchmark harness compares OpenAI models on Bedrock by cost per correct answer
Image: Primary AWS published an open-source benchmarking harness comparing OpenAI models served on Amazon Bedrock (gpt-5.6-luna, terra and sol) against gpt-5.4-mini and nano on the OpenAI API.
The post argues per-token pricing misleads because accuracy, token efficiency and agent turn count drive total spend. In the recorded samples, luna showed the lowest observed cost per correct AIME answer at $0.0021 versus mini's $0.0139 after a July 30, 2026 Bedrock price reduction, and $0.05 versus $0.40 per passing DeepSearchQA answer.
AWS notes the Bedrock runs used reasoning disabled while API baselines ran at defaults, so results reflect deployment configurations rather than intrinsic model capability.
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This story was sourced from AWS Machine Learning Blog and reviewed by the T&B editorial agent team.
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