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OpenAI 发布 GPT-6.1 Sol,定价为 Astra 的五分之一

OpenAI launches GPT-6.1 Sol at one-fifth of Astra pricing

AI 导读

OpenAI 发布 GPT-6.1 Sol,在智能体编码、计算机使用和专业工作流上接近 GPT-6 Astra 的表现,标准输入输出 token 价格为 Astra 的五分之一。

推荐理由

原文给出 GPT-6.1 Sol 与 Astra、GPT-6 Sol 在多项基准上的分数和单价对比,可据此判断性价比变化。

正文 · 原文

OpenAI has released GPT‑6.1 Sol, an upgrade that brings near-GPT‑6 Astra performance to agentic coding, computer use and professional workflows at one-fifth of Astra’s standard input and output token prices. Cached input costs $0.10 per million tokens, 95% less than standard input and half the cached-input price of GPT‑6 Sol, giving agents that reuse context a much cheaper path to capable long-running work.

GPT-6.1 Sol is here.

Upgraded with stronger agentic coding and computer use, near-Astra performance, and cached input at a 95% discount to standard input pricing.

GPT-6.1 Sol is built for complex refactors, deep codebase investigations, and long-running agents across apps. pic.twitter.com/1XRVKHgISH

— OpenAI Developers (@OpenAIDevs) September 29, 2026

The largest gains appear in demanding software and business tasks. On DeepSWE v1.1, GPT‑6.1 Sol matched GPT‑6 Astra at roughly one-fifth of the cost and beat GPT‑6 Sol’s best score by 6.4 percentage points at lower reasoning effort and cost. On GDP.pdf, it scored above Opus 5.5 with fallbacks for less than half the cost per task across the tested settings, while approaching Astra’s performance at about one-fifth of the cost.

GPT-6.1 Sol: near-Astra intelligence for a fifth of the price.

It’s the most cost-efficient model for its performance available today. pic.twitter.com/hH8PnE2Oxk

— OpenAI (@OpenAI) September 29, 2026

GPT‑6.1 Sol also moved ahead of Opus 5.5 by 2.2 percentage points on AutomationBench at medium reasoning effort for roughly one-third of the cost. That result was 4.8 points above GPT‑6 Sol at the same setting. The benchmark covers end-to-end sales, marketing, operations, support, finance and HR workflows using 47 tools.

GPT-6.1 Sol is a significant upgrade over GPT-6 Sol across coding, computer use, and complex professional work—approaching GPT-6 Astra on several benchmarks at substantially lower cost. pic.twitter.com/vCOE2HGLYv

— OpenAI (@OpenAI) September 29, 2026

Computer use and scientific work show a similar cost-performance shift. On OSWorld 2.0’s offline set, the model beat GPT‑6 Sol by seven points at maximum effort for less than half the cost, landing within 2.1 points of Astra at roughly one-seventh of the cost per task. At maximum effort on Terminal-Bench Science, it more than doubled GPT‑6 Sol’s score and averaged $5.47 per task, compared with $23.21 for Opus 5.5 and $23.80 for Astra. Astra still led that test at 68.1% and remains OpenAI’s choice for the hardest scientific research tasks.

GPT 6.1 Sol in Codex continues to be the absolute goat for mobile app development pic.twitter.com/wvijHyvuCP

— Robin Ebers (@robinebers) September 30, 2026

Factual accuracy rose most at low reasoning effort, where the share of difficult answers containing an error fell from 11.4% to 7.7%. OpenAI also reports stronger adherence to user intent and safety limits. GPT‑6.1 Sol failed to disclose a broken search tool in 2.1% of deliberately challenging cases, down from 4.9% for GPT‑6 Sol, and made no observed attempt to bypass an automated safety reviewer.

GPT-6.1 Sol replaces GPT-6 Sol after just 7 days. It scores 1 point below GPT-6 Astra in the Intelligence Index at less than one quarter of the Cost per Task

Pricing matches GPT-6 Sol at $2/$10 per million input/output tokens, except that the cache read discount rises from 90%… pic.twitter.com/LcuAxgLSBj

— Artificial Analysis (@ArtificialAnlys) September 29, 2026

GPT‑6.1 Sol is now available to Plus, Pro, Business, Enterprise and Edu users in ChatGPT Work and Codex, but not yet in Chat. Developers can call it through the API as gpt-6.1-sol for $2 per million input tokens, $0.10 per million cached input tokens and $10 per million output tokens. OpenAI also plans a GPT‑6.1 Sol Ultrafast option in Codex with up to eight times faster token generation in the coming days.

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来源:TestingCatalog · testingcatalog.com