Artificial Analysis：GPT-6 Astra 的 token 效率领先同级
在智能前沿附近的模型里，GPT-6 Astra 的 token 消耗几乎最低，而 Claude Fable 5.1、Gemini 3.8 Flash 最费 token。
GPT-6 Astra is more token efficient than almost every other model near the intelligence frontier, with Claude Fable 5.1 and Gemini 3.8 Flash using the most tokens of models scoring at least 25 on our Index.
Anthropic’s Claude Fable 5.1 and Opus 5 lead AA-Briefcase, followed by GPT-6 Astra and Muse Spark 1.3. GPT-6 Astra shows a substantial gain above GPT-5.6 Sol of ~85 Elo points. AA-Briefcase is our frontier in-house evaluation with a private held-out test set. The evaluation tests models on realistic agentic knowledge work tasks in complex projects built by industry experts. Models are evaluated on multi-week knowledge work projects, each with many linked tasks and thousands of input source files. AA-Briefcase combines rubric and pairwise grading to evaluate verifiable task success, analytical quality, and presentation quality, giving a holistic view of overall agentic capability in knowledge work.
OpenAI leads GDP.pdf with GPT-6 Astra at 33.2% and GPT-5.6 Sol at 28.2%, followed by Claude Fable 5.1 at 26.2%. Created by @HelloSurgeAI, GDP.pdf evaluates single-turn professional document reasoning across 100 PDFs and ten domains. Models must synthesize evidence distributed across 4,592 pages, including text, tables, charts, footnotes, and exclusions. Responses are graded against 1,275 expert-authored atomic criteria; the headline All-pass Rate credits a task only when every criterion is satisfied.
