Astra scores 67 on Artificial Analysis Coding Agent Index, near peers Claude Opus 5, Fable 5 and Muse Spark 1.3, but trails leader Fable 5.1's 70
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| Source: Techmeme | Original article
GPT-6 Astra scored 67 on the Artificial Analysis Coding Agent Index, matching Claude Opus 5, Fable 5 and Muse Spark 1.3, but lagging behind leader Fable 5.1’s 70.
OpenAI’s newest coding model, GPT‑6 Astra, posted a 67 on Artificial Analysis’s Coding Agent Index, placing it on par with Anthropic’s Claude Opus 5, Fable 5 and Muse Spark 1.3, but a few points shy of the current leader, Fable 5.1, which scored 70. The index aggregates performance across DeepSWE, Terminal‑Bench v2.1 and SWE‑Atlas‑QnA, measuring everything from code implementation to repository‑wide understanding.
Astra’s score is notable for the efficiency gains it delivers. Compared with OpenAI’s own GPT‑5.6 Sol, Astra consumes fewer tokens for comparable results, yet its pricing has risen to roughly 2.5 times Sol’s rates – from $4/$20 per million input/output tokens to $10/$50. Despite the higher per‑token cost, Astra’s per‑task expense is less than half that of Claude Fable 5 for an equivalent score, suggesting a trade‑off between raw price and token efficiency that could influence enterprise adoption decisions.
The benchmark matters because coding agents are increasingly central to developer workflows, and the index has become a de‑facto yardstick for productivity and cost‑effectiveness. Astra’s strong showing signals that OpenAI can compete on performance while offering a cheaper operational profile than some rivals, even as its pricing strategy remains under scrutiny.
Looking ahead, analysts will watch whether OpenAI adjusts Astra’s pricing to better align with its token efficiency, and how the model performs on the “messier” tasks that differentiate the leaderboard, such as internal database migrations where Astra already outpaces GPT‑5.6 Sol. Further releases from Artificial Analysis and upcoming OpenAI agent updates will likely reshape the competitive landscape, especially after the recent series of OpenAI‑agent incidents we covered earlier this month.
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