跳到正文
今天10月30日周五3 条
10月29日周四
  1. Arena.ai61

    Arena 公布近 9K 个智能体会话的实测结果:OpenAI 的 GPT-6.1 Terra (Max) 在 Agent Arena 排名第 8,净提升 +10.6%,单任务中位成本 $0.62,重塑 Pareto 前沿。

    引用Arena.ai@arena

    Real-world results are in: GPT-6.1 Terra (Max) by @OpenAI just landed #14 in the Code Arena: WebDev with 1671 pts, delivering Pareto level results! That’s +151 pts over GPT-5.6 Terra, now at #56. At a median cost of $0.40 per task, GPT-6.1 Terra costs 28% less than GPT-5.6 Terra ($0.56 per task), reshaping the Pareto frontier. Compared to other models in the family, GPT-6.1 Terra (Max) is incredibly efficient: - 81 pts below #4 GPT-6.1 Sol (1752 pts), at 75% lower median cost per task. - Just 6 pts below #11 GPT-6 Sol (1677 pts), at 76% lower median cost per task Congrats to the @OpenAI team on this release!

  2. Rohan Paul68

    一项新预印本测试了 15 个 LLM 检测临床试验论文中植入方法学错误的能力,模型得分 53% 到 96%,而未受训练的人类审稿人平均仅 27%。在 58 项 2026 年发表的新试验上结果仍成立,Claude Opus 5.5 最高达 99%;人类仅 7% 的情况下能发现文本与表格矛盾,每篇审稿需 5 到 8.5 小时,AI 只需 1.4 到 16.3 分钟。

    引用Ruslan Rust@rust_ruslan

    Lots of debate this week on whether journals should ban AI in peer review. We actually tested this in our new preprint, and the results were pretty clear to me. For context, I've reviewed for most of the big journals and evaluated 1,000 human reviews as an editor. I love to read and evaluate science. TLDR: From now on I won't do any peer review without AI. For clinical trials, I'd even call human-only review dangerous 🧵

  3. Google64

    Google 发布 Gemini 4 Carbon 的早期预览,该模型以 59 分位列 Artificial Analysis Intelligence Index v5 第一,比 Gemini 4 Argon 高 9 分,在复杂推理、知识和科学任务上领先。引用的 Artificial Analysis 评测称其编码智能体仅次于 Claude Opus 5.5,定价 $4/$20 per 1M tokens 与 Argon 标准价一致,目前仅向部分用户开放,尚未公开可用。

    引用Artificial Analysis@ArtificialAnlys

    Google’s Gemini 4 Carbon is the new #1 on the Artificial Analysis Intelligence Index v5, and second only to Claude Opus 5.5 on the Artificial Analysis Coding Agent Index Gemini 4 Carbon scores 59 on Intelligence Index v5, driven by leading performance in complex reasoning, knowledge, and scientific tasks. It also has large gains in coding and knowledge work, particularly when compared to other Gemini models, but it is not leading in all these areas. As with launch of Gemini 4 Argon, Gemini 4 Carbon is being rolled out to selected users and is not yet publicly available. Google is offering a 50% launch discount, with no confirmed end date. All our charts and figures use standard pricing for both Gemini 4 Carbon and Argon. Key results for Gemini 4 Carbon with high reasoning: ➤ Gemini 4 Carbon leads the Intelligence Index v5, with the #1 score in 4 of the 9 Index evaluations: HLE-Diamond, Terminal-Bench-Science, AA-Omniscience, AutomationBench-AA. Carbon makes substantial gains elsewhere but is not leading in coding and knowledge work ➤ Behind only Claude Opus 5.5 on coding agents: With Antigravity CLI, Gemini 4 Carbon (high) scores 59 only 3 points behind Claude Code with Claude Opus 5.5 (max, 62) on the Artificial Analysis Coding Agent Index. Carbon ranks second on both Terminal-Bench 4.0 (64%) and FrontierCode v1.1 (51%), behind Claude Opus 5.5 (max) at 56%. Google has historically underperformed in this area and so this improvement stands out ➤ Improved agentic knowledge work, but not yet leading: On AA-Briefcase, Gemini 4 Carbon (high) scores 1609 Elo, a 126-point improvement over Gemini 4 Argon (high, 1483), but still behind models including Grok 4.7 (xhigh, 1638), Muse Wonder (max, 1659) and Kimi K3.1 Pro (1678). The largest gain comes from Presentation, up 293 Elo to 1598, alongside a 120-point improvement in Analytical Quality to 1671 ➤ Lower Cost per Task than Claude Opus 5.5 for comparable overall intelligence: Gemini 4 Carbon costs $7.76 per Intelligence Index task, ~23% less than Claude Opus 5.5 (max, $10.04) but ~1.2x GPT-6 Astra (max, $6.25). It uses 123k output tokens per task, 29% fewer than Claude Opus 5.5 (max, 173k). At the same $4/$20 standard pricing, its Cost per Task is in line with Gemini 4 Argon ($7.68), while scoring 9 points higher on the Intelligence Index ➤ Leading AA-Omniscience v1.1 score, with low hallucination: Gemini 4 Carbon scores 54 on our recently updated AA-Omniscience v1.1, 6 points ahead of Claude Opus 5.5 (max, 48) and 8 points ahead of Gemini 4 Argon (46). Accuracy (% correct) rises 10 points over Argon to 58%, while its hallucination rate rises from 4% to 11%. This is still the second lowest of any model, behind only Argon, compared with 50% for both Claude Opus 5.5 (max) and GPT-6 Astra (max) Key model details: ➤ Context Window: 1M tokens ➤ Multimodality: Text, image, video, and speech input, with text output ➤ Pricing: $4/$20 per 1M input/output tokens, the same as Gemini 4 Argon’s standard pricing, with a 50% discount. Cached input tokens receive a 95% discount ($0.20 per 1M) Congratulations to the @GoogleDeepMind team!

  4. Arena.ai68

    Arena 宣布 Gemini 4 Carbon (High) 首次上榜:Text Arena 第一(1528 分),Agent Arena 第二(+16.2% 净提升),Code Arena: WebDev 第四(1768 分)。

    引用Arena.ai@arena

    Exciting news: Gemini 4 Carbon (High) from @GoogleDeepMind just made a huge debut on Arena, landing #1 in Text Arena, #2 in Agent Arena, and #4 in Code Arena: WebDev. Back at the top, Gemini 4 Carbon delivers frontier intelligence and reshapes the Pareto frontier across three arenas. In Agent Arena, Gemini 4 Carbon ranks #2 with a +16.2% net improvement across +21.9K real-world agentic sessions from our global community, surpassing top models GPT-6 Astra and Fable-5.1. At $1.80 median cost per task, Gemini 4 Carbon (High) costs 72% less than the #1 ranked Claude Opus 5.5 (Max). Its standouts by key signals: - #1 Steerability (+18.6%): can the model course-correct when you push back? - #2 Praise vs Complaint (+37.9%): implicit sentiment in users' reactions - #3 Confirmed Success (+18.7%): explicit “yes, that worked” from users In Code Arena: WebDev, Carbon scored 1768 pts landing #4: - Just 2 pts below #3 Claude Sonnet 5.5 (xHigh), at 1770 pts - 89 pts above #11 Gemini 4 Argon (High), at 1679 pts By category, it ranks #3 in Gaming and Simulations, and #5 in Brand & Marketing. In Text Arena, Gemini 4 Carbon (High) is the new #1 with 1528 pts, now ahead of Gemini 4 Argon (High) at #2 with 1520 pts. Congrats to the @GoogleDeepMind team on this huge milestone!

  5. Arena.ai69

    Arena 宣布 Google DeepMind 的 Gemini 4 Carbon (High) 登上 Agent Arena、Code Arena: WebDev 和 Text Arena 的帕累托前沿。在 Agent Arena 中它排名第 2,净提升 +16.2%,每任务中位成本 $1.80,比排名第 1 的 Claude Opus 5.5 (Max) 低 72%。详情见 https://arena.ai/leaderboard/agent/pareto

    引用Arena.ai@arena

    Gemini 4 Carbon (High) by @GoogleDeepMind landed on the Pareto frontier in Agent Arena, Code Arena: WebDev, and Text Arena! In Agent Arena, it ranks #2 with +16.2% net improvement at $1.80 median cost per task. This is 72% less than #1 Claude Opus 5.5 (Max). Dive into the Agent Arena Pareto, and see where Gemini 4 Carbon (high) landed on the Pareto frontier for Code Arena: WebDev and Text at https://arena.ai/leaderboard/agent/pareto

  6. Karina62

    Karina Nguyen 团队推出 BallotBench 实时基准,9 个前沿 AI Agent 从发布当天至 11 月 3 日选举日竞猜 2026 美国中期选举结果。

    引用Thoughtful@thoughtfullab

    Can AI forecast elections better than experts and prediction markets? We built BallotBench to find out: a live benchmark where 9 frontier AI agents compete to predict the 2026 US midterms, from today through Election Day, Nov 3. Follow along → http://ballotbench.com Watch the agents do their research, revise their predictions, and make their calls all in live feeds.

10月28日周三
  1. Cognition 模型 / Devin 博客57

    Cognition 发布编码基准 FrontierCode 2.0,Opus 5.5 以 45.5% 居首

    Cognition 发布新一代编码基准 FrontierCode 2.0,通过扩大任务范围、提高合并标准和引入 thoroughness 类评分标准,来评测智能体在提示不完备时的真实工程能力。任务取自多 55% 的仓库,参考解决方案平均多改 67% 的文件和 89% 的代码行;Opus 5.5 以 45.5% 得分居首,基准远未饱和。

  2. Ai2 / Allen Institute for AI64

    Ai2 发布 Old Ideas, Novel Problems 研究与 benchmark,揭示 LLM 新颖性裁判不稳定

    Ai2 发布研究 Old Ideas, Novel Problems、配套 benchmark、数据、代码和自动化流水线,测试 LLM 作为研究想法新颖性裁判的可靠性。

    推荐理由:原文给出了跨六个 LLM 裁判的敏感性实验数据,读者可据此判断现有新颖性评估在 AI 生成想法上的可靠性边界。

10月27日周二
  1. Mustafa Suleyman57

    Microsoft AI CEO Mustafa Suleyman 宣布 MAI-Image 现居全球图像编辑模型第二,称再次超越 Google、Meta、xAI 和 GPT-Image-2.5-Flare,可在 MAI Playground 试用。引用的 Artificial Analysis 分析称 MAI-Image-2.7-Preview 在 AA-Image-Editing v2.1 榜单排名第二,7 项编辑动作全面高于 MAI-Image-2.6,其中 4 项排名第一,最大提升为 Composition & Framing(+57 Elo),目前仅支持图像编辑,文生图功能即将推出。

    引用Artificial Analysis@ArtificialAnlys

    Microsoft's MAI-Image-2.7-Preview takes #2 on AA-Image-Editing v2.1, close behind OpenAI's GPT Image 2.5 Sunburst (max) and a clear step up from MAI-Image-2.6 MAI-Image-2.7-Preview is Microsoft AI's newest image editing model, succeeding MAI-Image-2.6, released in August. In our testing, MAI-Image-2.7-Preview scores higher than MAI-Image-2.6 on all 7 editing actions we measure, and ranks #1 on 4 of them: Scene & Style Edit, Text or Symbol Edits, Reasoning-Based Edit, and Enhancement & Restoration. This new model improves on MAI-Image-2.6 with the biggest gains in Composition & Framing (+57 Elo), Text or Symbol Edits (+49) and Scene & Style Edit (+48). We see its best use cases to be in Live-Action Film, Consumer and Frontier edits, where it ranks #1. MAI-Image-2.7-Preview is available today in MAI Playground for image editing only, with text to image stated to be coming soon. Congratulations to @MicrosoftAI on the release! See below for our detailed analysis and example outputs of MAI-Image-2.7-Preview in the Artificial Analysis Image Arena 🧵