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10月28日周三
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 🧵

10月17日周六
10月16日周五
  1. IT之家·人工智能58

    微软完成 2.8T 参数基模 MAI-Base-2 预训练,称性能强于所有参测开源权重模型

    微软宣布完成新一代 SOTA 基础模型 MAI-Base-2 的预训练,称其性能强于所有参测开源权重模型。该模型总参数 2.8T、活跃参数 80B,在 6,000 个 NVIDIA GB200 GPU 上训练 38 天,平均浮点算力利用率 21%、有效吞吐量 89%,预训练算力效率据称为 DeepSeek-V4-Pro-Base 的 4~12 倍。

  2. Microsoft AI:官方博客66

    Microsoft AI 公布 MAI-Base-2 预训练细节,2.8T 参数 MoE 模型 FLOPs 效率达 DeepSeek-V4-Pro-Base 的 4.2 至 12.3 倍

    Microsoft AI 宣布完成 MAI-Base-2 预训练,这是一个 800 亿激活、2.8T 总参数的 MoE 基础模型,在 held-out 评测中 BPB 低于所测全部开源权重模型,预训练 FLOPs 效率比 DeepSeek-V4-Pro-Base 高 4.2 至 12.3 倍。

    推荐理由:官方披露了 MAI-Base-2 的完整预训练方法,读者可以从中了解 scaling ladder、Muon 优化和多轮 dropless MoE 等可借鉴的工程细节。

10月10日周六
  1. IT之家·人工智能50

    微软推出 Microsoft-Decision-1 决策模型,基于 Qwen3.5-9B 后训练

    微软发布 Microsoft-Decision-1 决策模型,专为结构化决策任务打造,现已上线 Microsoft Foundry 并接入 OpenRouter。该模型基于 Qwen3.5-9B 后训练,在 36 项基准测试中准确率最高,响应速度比 Quyet-1.0-Large 快 4.5 倍、比 GPT-6 Sol 快 35 倍。定价为每百万 Token 输入 0.042 美元,输出免费。

  2. OpenRouter58

    Microsoft-Decision-1 上线 OpenRouter。官方称其在 36 项盲测基准(约 15 万题)中准确率最高,比第二名快 4.5 倍、比 GPT-6 Sol 快 35 倍,扰动输入下仅 1.3% 的决策翻转;基于 Qwen3.5-9B 后训练,定价 $0.042/M input、输出免费,32K 上下文。

    引用Satya Nadella@satyanadella

    Introducing Microsoft-Decision-1, our new model for fast decision-making. It delivers top performance on structured decision tasks, outperforming both LLMs and other decision models in latency and quality. We’re already testing it across Microsoft for everything from incident response and quality control to scientific discovery.

10月8日周四
10月2日周五
  1. Mustafa Suleyman64

    Microsoft AI 发布流式语音转写模型 MAI-Transcribe-2-Streaming,Mustafa Suleyman 称其为全球最准确的实时转写模型,比 ElevenLabs 快 55%、便宜 60%。引用的 Artificial Analysis 数据显示,该模型以 2.5% WER、语音结束后 0.13 秒出稿在 AA-WER Streaming 38 个模型中排名第一,超过此前第一的 Grok Voice Transcribe 2.0(2.7%、0.49s),流式定价为每小时音频 $0.54,非流式为 $0.10 每小时。

    引用Artificial Analysis@ArtificialAnlys

    Microsoft AI has released MAI-Transcribe-2-Streaming, taking the #1 spot for Final Transcript accuracy and First Partial Transcript accuracy on AA-WER Streaming with 2.5% WER at 0.13s after end of speech MAI-Transcribe-2-Streaming is @MicrosoftAI's new streaming Speech to Text model, joining the non-streaming MAI-Transcribe-2. It leads streaming Final Transcript WER at 2.5%, ahead of the previous #1, SpaceXAI's Grok Voice Transcribe 2.0 at 2.7%, and returns that transcript in 0.13s rather than 0.49s. It is available for streaming transcription at $0.54 per hour of audio, at the higher end of pricing among the leading streaming models. Key takeaways ➤ Final Transcript: MAI-Transcribe-2-Streaming achieves 2.5% WER at 0.13s after end of speech, ranking #1 of 38 models. It is more accurate and faster than Grok Voice Transcribe 2.0 at 2.7% and 0.49s, Muse Voice Transcribe at 3.1% and 0.16s, and ElevenLabs Scribe v2 Realtime at 3.6% and 0.14s. It is also more accurate, though slightly slower, than Cartesia Ink Preview (external endpoints) at 3.1% and 0.11s ➤ First Partial Transcript: The model achieves 2.5% WER at 0.12s, ahead of Grok Voice Transcribe 2.0 at 3.4% and 0.49s, and ahead of Muse Voice Transcribe and ElevenLabs Scribe v2 Realtime on accuracy, both at 3.6%, and slightly faster than both at 0.12s versus 0.13s. It is more accurate but slower than Cartesia Ink-2 (external endpoints) at 4.0% and 0.07s ➤ Price: MAI-Transcribe-2-Streaming costs $0.54 per hour for streaming, or $9.00 per 1,000 minutes. This puts it level with Gemini 3.5 Transcribe Live at $9, above the $6.50 charged for ElevenLabs Scribe v2 Realtime and Deepgram Flux, more than twice Cartesia Ink-2 at $4, and three times Muse Voice Transcribe at $3. Non-streaming transcription costs $0.10 per hour, or $1.67 per 1,000 minutes Congrats to the @MicrosoftAI team on the launch! See more details below

9月22日周二
9月5日周六
  1. Microsoft AI:官方博客63

    Microsoft 发布 MAI-Image-2.6 与 MAI-Image-2.6-Flash 图像模型

    Microsoft 于 9 月 4 日发布 MAI-Image-2.6,称其为迄今最强的图像模型,并面向开发者上线 Microsoft Foundry,同时推出面向低延迟、高吞吐场景的 MAI-Image-2.6-Flash。

    推荐理由:原文给出排名、速度和效率数字,并说明两个版本分别面向精度与吞吐的不同场景,便于开发者按工作流选型。

9月4日周五
9月3日周四
  1. Microsoft AI:官方博客64

    Microsoft AI 发布语音识别模型 MAI-Transcribe-2

    Microsoft AI 发布转录模型 MAI-Transcribe-2,称其在 FLEURS 基准 60 种语言上平均词错率 5.2% 排名第一,并占据 Artificial Analysis 准确率-延迟 Pareto 前沿。

    推荐理由:官方给出具体基准排名、对比速度倍数和定价,读者可以据此评估它对现有语音转写方案的可替换性。

9月1日周二
  1. Microsoft Research 博客72

    微软研究院发布高效病理基础模型 GigaPath-Flash 与 GigaTIME-Flash

    微软研究院推出 GigaPath-Flash 和 GigaTIME-Flash,旨在通过蒸馏技术大幅降低计算成本以支持大规模病理研究。GigaPath-Flash 将十亿参数模型压缩至 22M 参数,在保持竞争力的同时实现约 50 倍的算力节省;GigaTIME-Flash 则提升了空间蛋白质组学预测效率并改善了泛化能力。两款模型均以 Apache 2.0 协议开源,专为科研设计而非临床诊断,使研究人员能在单 GPU 上处理百万级切片数据。

8月27日周四
8月26日周三
  1. Mustafa Suleyman40

    Microsoft AI 发布 MAI-Image-2.6-Preview,在 Artificial Analysis 图像编辑排行榜登顶第一,文本生成图像位列第二(仅次于 OpenAI 的 GPT Image 2)。该模型在 19 个分类榜单中拿下 5 个第一,现已在 MAI Playground 和 Microsoft Foundry 私有预览中提供。

    引用Artificial Analysis@ArtificialAnlys

    Microsoft's MAI-Image-2.6-Preview lands at #1 on the Artificial Analysis Image Editing Leaderboard and takes #2 in Text to Image MAI-Image-2.6 is the newest model in Microsoft AI's MAI-Image family, announced August 10. Microsoft highlights stronger text rendering, better portraits and 3D imagery, and more polished commercial and photorealistic outputs. Like the MAI-Image-2.5 family, it handles both text to image generation and image editing. In the Artificial Analysis Image Arena, MAI-Image-2.6-Preview debuts at #1 on the Image Editing Leaderboard, ahead of Microsoft's own MAI-Image-2.5-Pro, Reve 2.1, and OpenAI's GPT Image 2, and giving Microsoft the top two spots on the board. In Text to Image it takes #2, behind only OpenAI's GPT Image 2 and ahead of Reve 2.1. On our refreshed Text to Image taxonomy, MAI-Image-2.6-Preview takes the top spot on 5 of the 19 category leaderboards (Material, Knowledge, Frontier, Retail & Ecommerce, and Marketing & Advertising), ahead of GPT Image 2, which leads every other category. MAI-Image-2.6 extends a rapid run of strong image releases from Microsoft AI. MAI-Image-2.5 debuted at #2 in Text to Image in June. MAI-Image-2.5-Pro, launched July 23, took #1 in Image Editing when we published our results last week. MAI-Image-2.6 now takes that top spot from its own sibling, and sits at #2 in Text to Image against MAI-Image-2.5-Pro's #8. MAI-Image-2.6 is available in the MAI Playground and in Private Preview on Microsoft Foundry. Congratulations to @MicrosoftAI on the release! See below for our analysis of MAI-Image-2.6-Preview and other leading models in the Artificial Analysis Image Arena 🧵

8月25日周二
8月21日周五
  1. Microsoft Research 博客78

    微软发布 Skala 1.1:深度学习 DFT 精度超越传统泛函并集成主流软件

    微软研究院发布深度学习交换关联泛函 Skala 1.1。该模型基于比前代多 2.5 倍的数据训练,在 GMTKN55 基准测试的 55 个类别中 32 项获第一,以 meta-GGA 的计算成本实现了优于最昂贵全局杂化泛函的精度。Skala 现已集成至 CP2K,并正在接入 Psi4、FHI-aims、ORCA 和 VASP 等主流电子结构软件,同时推出动态基准以追踪性能优化。

8月19日周三
  1. Mustafa Suleyman40

    微软 MAI-Image-2.6-Preview 在图像编辑基准测试中位列第三,得分 1,420 分,较上一代提升 19 分,从第五跃升至第三。该模型在商品、3D、动漫、写实等四类中均排第三,文本渲染提升最显著(+43 分)。

    引用Arena.ai@arena

    MAI-Image-2.6-Preview by @MicrosoftAI has landed at #3 in Single Image Edit with 1,420 pts! This is +19 pts above MAI-Image-2.5, moving from #5 to #3. It sits 19 pts behind preliminary Grok Imagine Image 2.0 (low) at #2 and 43 pts behind GPT Image 2 (medium) at #1. By category, MAI-Image-2.6-Preview is #3 in across: - Product, Branding & Commercial Design - 3D Imaging & Modeling - Cartoon, Anime & Fantasy - Photorealistic & Cinematic Imagery #4 in Portraits and #8 in Text Rendering. The biggest jumps over MAI-Image-2.5 are in Text Rendering (+43 pts) and Product, Branding & Commercial Design (+38 pts). Congrats again to the @MicrosoftAI team on this release!

8月13日周四
8月12日周三