GPT-6 Astra makes major gains in the Artificial Analysis Coding Agent Index

OpenAI's GPT-6 Astra scores 67 on the Artificial Analysis Coding Agent Index, matching Fable 5 at less than half the cost, and scores 61 on the Intelligence Index, equal to GPT-5.6 Sol but with a 2.5x price increase to $10/$50 per million input/output tokens. The model uses one third of the tokens of GPT-5.6 Sol in the Codex harness and reduces hallucination rate from 92% to 51% at max effort, according to Artificial Analysis.

All articles /articles September 3, 2026 GPT-6 Astra makes significant gains in the Artificial Analysis Coding Agent Index, scoring equal to Fable 5 at lower cost. In the Intelligence Index, it uses fewer tokens than GPT-5.6 Sol for similar performance, but this is outweighed by higher prices Pricing is 2.5x GPT-5.6 Sol’s current prices across the board, up from $4/$20 to $10/$50 per million input/output tokens, with the same 90% discount for cache reads and 25% premium for cache writes. We see distinct stories across our two flagship Indices. In the Artificial Analysis Coding Agent Index, GPT-6 Astra equals Fable 5 at less than half the cost, driven by significant token efficiency gains. In the Artificial Analysis Intelligence Index, GPT-6 Astra is more token efficient than its predecessor for similar performance, but this is offset by the price increase. Artificial Analysis Coding Agent Index - key takeaways: ➤ Rivals top models: In Codex, GPT-6 Astra scores 67 in the Index - approximately equal to Claude Opus 5 and Fable 5 in Claude Code, and Muse Spark 1.3 in Muse Code. Fable 5.1 in Claude Code leads the Index with a score of 70. ➤ 70% more token efficient than GPT-5.6 Sol: GPT-6 Astra sees a substantial improvement in token efficiency, using one third of the tokens compared to GPT-5.6 Sol max in the Codex harness, and one fifth of the tokens of Claude Opus 5 xhigh . Various effort levels of the model occupy the Pareto frontier of token efficiency. ➤ Leads Coding Agent Index cost efficiency frontier: At max effort, GPT-6 Astra costs about the same as GPT-5.6 Sol max while scoring 2 points higher on the Index. Per task, the model is less than half the cost of Claude Fable 5, for the same score. Artificial Analysis Intelligence Index - key takeaways: ➤ Sits beside GPT-5.6 Sol in Intelligence: GPT-6 Astra scores equal to GPT-5.6 Sol in the Index at 61. This is 5 points lower than Claude Fable 5.1 max with fallback . The model also trails Meta’s newly released Muse Spark 1.3 max . ➤ ~10% fewer output tokens, offset by price increase: GPT-6 Astra defines a new Pareto frontier for Intelligence Index vs Output Tokens per Task - with a ~10% reduction in token use at max effort compared to GPT-5.6 Sol. However, due to the 2.5x increase in price, the model is 75% more expensive per task than its predecessor at max effort. ➤ Hallucinates half as much as GPT-5.6 Sol: GPT-6 Astra sees a large jump in AA-Omniscience, our knowledge and hallucination benchmark. This is driven by a significant decrease in hallucination rate from 92% to 51% at max effort. Unlike some models, this improvement does not come at the cost of accuracy - Astra increased accuracy by 4 points at the same time. ➤ ~80 point gain in AA-Briefcase Elo: GPT-6 Astra improves ~80 points in AA-Briefcase, our frontier long-horizon knowledge work evaluation. Models are tested on multi-week projects, with many linked tasks and thousands of source files. Astra sees a significant increase in both rubric scores and Analytical Quality Elo in AA-Briefcase compared to its predecessor. In the other direction, we observe a reduction in Presentation Quality Elo, where GPT-5.6 Sol max still leads all models. ➤ Mixed progress on other evaluations: The model sees a 6 point gain in Humanity’s Last Exam, a long-standing evaluation with emphasis on mathematics, science, and humanities. This is offset by a drop of ~80 Elo points in GDPval-AA v2 - a benchmark we adapted from OpenAI’s dataset measuring economically valuable tasks across 44 occupations. We also observe 2-3 point regressions on other evaluations across a mix of capabilities, including reductions in τ³-Banking customer support , SciCode Python problems in a scientific domain , and AA-LCR long context reasoning over large documents . Coding Agent Index cost improvements are driven by token efficiency, with a ~3x token reduction at max effort compared to GPT-5.6 Sol max . GPT-6 Astra is on the Pareto frontier for Coding Agent Index vs Cost per Task, with its max effort setting costing about the same as GPT-5.6 Sol max while scoring 2 points higher in the Index. GPT-6 Astra defines a new Pareto frontier for Intelligence Index vs Output Tokens per Task - with a ~10% reduction in output tokens at max effort compared to GPT-5.6 Sol. GPT-6 Astra is 75% more expensive than GPT-5.6 Sol at max effort, and largely sits behind its predecessor on the Intelligence Index vs Cost per Task frontier. This is driven by a 2.5x increase in price, partially offset by a reduction in token use. GPT-6 Astra sees a large jump in AA-Omniscience, driven by a significant decrease in hallucination rate from 92% to 51% at max effort, alongside a modest increase in accuracy. The model shows mixed progress in agentic knowledge work - improving ~80 points in AA-Briefcase, but regressing a similar amount in GDPval-AA v2. In AA-Briefcase, Astra sees a significant increase in both rubric scores and Analytical Quality Elo, but a reduction in Presentation Quality Elo. Breakdown of the individual evaluations in the Artificial Analysis Intelligence Index v4.1.1. Compare GPT-6 Astra with other leading models at: www.artificialanalysis.ai http://www.artificialanalysis.ai Read the latest Muse Spark 1.3: Meta reaches the frontier Independent analysis and benchmarks of Meta's Muse Spark 1.3 September 2, 2026 Google has released Gemini 3.8 Flash, its fourth Flash model in under four months Gemini 3.8 Flash scores 59 on the Artificial Analysis Intelligence Index and reaches the Intelligence vs. Cost per Task Pareto frontier September 2, 2026 Claude Fable 5.1 tops the Artificial Analysis Intelligence Index Anthropic's new frontier model scores 66 at max effort and leads on agentic knowledge work, but the 75% cache read price cut only partly offsets higher token usage September 1, 2026