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星期四

  1. Sakana AI:Blog

    Sakana AI 发布 Fugu-Ultra v1.1 并推出兼容 Claude Code 的接口

    Sakana AI 发布编排引擎 Fugu-Ultra v1.1,通过动态编排最新前沿模型,性能较 v1.0 最高提升 7.9 分,在 ProgramBench 和 Terminal Bench 2.1 上表现尤为突出,价格与 v1.0 相同。同时推出兼容 Claude Code 的接口,开发者可在 Claude Code 中直接调用 Fugu 的多智能体编排能力,入口为 https://console.sakana.ai/get-started。

    r models, we pushed performance up by as much as 7.9 points. We are now beating leading models like Fable 5 in complex coding and reasoning tasks, without even having Fable in our agent pool. Collective intelligence is the future! Fugu-Ultra v1.1: The Frontier Keeps Moving Fugu-Ultra is now upgraded to incorporate the latest frontier models. Our latest Fugu-Ultra v1.1 delivers stronger performance across every benchmark we track. This orchestration upgrade resulted in gains of up to 7.9 points o

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  2. Black Forest Labs Blog精选

    Black Forest Labs 发布多模态基础模型 FLUX 3,开启早期访问

    Black Forest Labs 发布多模态基础模型 FLUX 3 并开启 Early Access,该模型基于 Self-Flow 在统一架构中同时学习图像、视频和音频,可单次生成最长 20 秒带原生音频的视频,并支持文生视频、图生视频、视频生视频、关键帧过渡和多语言对话等能力。早期评测中 FLUX 3 在最高 69% 的对比中优于 Grok Imagine Video,对 Runway Gen-4.5 和 Luma Ray 3.2 的偏好比例分别为 77% 和 93%,官方称结果仍属初步。后续将陆续开放 FLUX 3 Video、FLUX 3 Image 的 API 与私有权重,以及 FLUX 3 Dev 的开源权重,FLUX 3 Image 的早期访问将在接下来几周开放。

    FLUX 3 - Real World Models: Towards Multimodal Flow Models as the Backbone of Visual Intelligence.

    on for controlled transitions between defined moments; Multilingual dialogue; A broad range of visual styles and aspect ratios, extending far beyond conventional cinematic output; Agentic chaining of individual clips into longer, multi-shot sequences; High style diversity -- FLUX 3 Video easily handles ranges of styles from candid camcorder footage to animation and cinematics; Strong typography generation and animated designs For the preliminary analysis below, we generated 10-second text-to-vid

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星期三

  1. Google DeepMind精选

    Google DeepMind 发布 Gemini 3.5 Flash Cyber 网络安全模型

    Google DeepMind 发布 Gemini 3.5 Flash Cyber,这是基于 3.5 Flash 微调的轻量网络安全模型,用于快速发现、验证和修补漏洞。该模型以限量试点形式通过 CodeMender 向政府和可信合作伙伴开放,后续逐步扩大范围。在 V8 JavaScript 引擎测试中,它发现 55 个已确认的独立问题,高于主线 3.5 Flash 的 47 个和 Claude Opus 4.6 的 36 个,其中 10 个为另外两个模型未发现的问题。

    Graphic featuring the text "Gemini 3.5 Flash Cyber" alongside a colorful star logo and a blurred blue shield on a light blue background.

    Flynn Share Google has invested in cybersecurity for years, pioneering automated vulnerability discovery to secure the world’s codebases. Tools like CodeMender , our code security agent, can automatically find and fix critical software vulnerabilities. But as AI agents become more capable at finding vulnerabilities faster than defenders can fix them, addressing this global threat requires a highly capable, affordable, and scalable approach. Today, we’re expanding our longtime efforts to better p

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星期二

  1. Google DeepMind

    Google DeepMind 发布 Gemini 3.6 Flash、3.5 Flash-Lite 与 3.5 Flash Cyber

    Google DeepMind 发布 Gemini 3.6 Flash、3.5 Flash-Lite 和面向安全漏洞的 3.5 Flash Cyber。3.6 Flash 在 Artificial Analysis Index 上输出 token 比 3.5 Flash 少 17%,定价为每百万输入 token 1.50 美元、每百万输出 token 7.50 美元,并配备 CBRN 与网络攻击滥用的 Frontier Safety 防护。3.5 Flash-Lite 以 350 output tokens/s 运行,定价每百万输入 token 0.3 美元、每百万输出 token 2.5 美元,在 Terminal-Bench 2.1 上从 3.1 Flash-Lite 的 31% 提升至 54%;3.5 Flash Cyber 基于 3.5 Flash 微调,将通过 CodeMender 以限量试点形式仅向政府和可信伙伴开放。3.6 Flash 与 3.5 Flash-Lite 即日起可用,Gemini 3.5 Pro 正在与伙伴测试,Gemini 4 已启动预训练。

    Jul 21, 2026 Our newest Gemini models deliver the efficiency, latency, and reliability to build AI agents at scale. Tulsee Doshi Senior Director, Product Management, on behalf of the Gemini team Developers and customers building production AI agents need higher token efficiency, lower latency, and more reliable performance. Our Flash series of models is built to meet the sweet spot of efficiency and quality to enable scaling agentic workflows. Building on Gemini 3.5 Flash, we’re introducing new

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星期一

  1. Sakana AI:Blog

    Sakana AI 发布 Fugu-Cyber 编排模型,CyberGym 成功率达 86.9%

    Sakana AI 发布 Fugu 编排模型的更新版 Fugu-Cyber,作为新 API endpoint 上线,在 CyberGym 上成功率达 86.9%,在 CTI-REALM 上达 72.1%,与 GPT-5.5-Cyber、Mythos-Preview 等网络安全前沿模型相当。它延续多智能体系统形态,通过单一 endpoint 动态编排专用智能体完成多步任务。该 API 面向 Token Plan 开放,用户需提交访问申请并说明用途,经人工审核后获批。

    hmarks, matching cyber-focused frontier models like GPT-5.5-Cyber and Mythos Preview. Together, these benchmarks test the core pillars of enterprise defense: CyberGym evaluates an agent’s ability to analyze complex codebases to verify real-world vulnerabilities, while CTI-REALM measures its capacity to translate raw threat intelligence reports into working detection rules. Like our original Fugu orchestration model, Fugu-Cyber is a multi-agent system that behaves like a single model. You send a

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  2. Recode China AI精选

    Kimi K3为何被称为最不像“中国模型”的中国AI模型

    月之暗面于7月16日发布旗舰模型 Kimi K3,作者认为其核心定位是以高性能和高定价直接竞争全球顶尖专有模型,而非充当廉价替代品。K3拥有2.8 trillion参数和1M上下文窗口,在 Frontend Code Arena 获得1,679分,并采用 KDA、AttnRes及默认开启的思考模式。其价格为每百万输入 token $3、每百万输出 token $15,开放权重计划于7月27日提供。

    Tony Peng's avatar

    Intelligence Conference in Shanghai where Chinese President Xi Jinping called for greater open-source collaboration. What makes K3 an unusual release though is not the coding and agentic performance, nor the efficiency optimization in training and inference. It’s the positioning. In my opinion K3 is an ambitious, even risky attempt to get rid of the old stereotype of Chinese models as a cheap alternative. Instead it is a high-end, premium model built to fight the world’s best proprietary fronti

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星期四

  1. xAI News精选

    xAI 发布 Grok 4.5,主打编码与智能体任务

    xAI 发布 Grok 4.5,称其为最强模型,专为编码、智能体任务和知识工作打造,并与 Cursor 联合训练。在 Datacurve 的 DeepSWE 基准上,Grok 4.5 得分 62.0%,高于 Opus 4.8 的 55.75%,低于 Fable 的 66.1% 和 GPT 5.5 的 64.31%。模型在数万块 NVIDIA GB300 GPU 上训练,推理速度 80 TPS,定价为每百万输入 token 2 美元、每百万输出 token 6 美元,并已成为 Grok Build 的默认模型。

    Today, we're launching Grok 4.5 , SpaceXAI's smartest model built to excel at coding, agentic tasks, and knowledge work. It's our strongest model ever and was trained alongside Cursor . Real-world engineering excellence Grok 4.5 was trained on datasets spanning knowledge in coding, science, engineering, and math. With both intelligent and efficient reasoning, Grok 4.5 excels at real engineering tasks and exceeds comparable leading models at these tasks. 0% 20% 40% 60% DeepSWE score (pass@1) 66.1

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星期三

  1. Hugging Face精选

    Thinking Machines 推出原生多模态开放模型 Inkling

    Thinking Machines 推出 Inkling,一款原生接收文本、图像和音频的开放权重 MoE 模型,拥有 975B 总参数、41B 激活参数和 1M 上下文窗口。其 bf16 与 NVFP4 检查点分别需要 2 TB 和 600 GB VRAM,并已获 Transformers、SGLang、vLLM 和 llama.cpp 支持。

    hatting with the model, and set it up with your favorite MCPs, pass in images or files conveniently and more! Llama cpp also ships with a built-in UI that supports tools, mcp, and agentic workloads. Checkout Inkling running at 1-bit precision in the llama app: Inkling GGUFs are also runnable in Unsloth Studio with dynamic 1-bit GGUFs which retain 74.2% of top-1% accuracy whilst being 86% smaller. Use Cases Agentic coding with Pi Pi is a minimal coding agent harness you can use with different lan

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  2. Together AI Blog精选

    Together AI 首日上线 Thinking Machines Lab 新模型 Inkling

    Thinking Machines Lab 发布多模态混合专家模型 Inkling,Together AI 同日在其推理平台上线。Inkling 接受文本、图像和音频输入并输出文本,支持可调推理强度,总参数 975B、每 token 激活 40B、上下文窗口 1M tokens。Together AI 称其采用基于 FlashAttention-4 的注意力内核,通过 Serverless 单端点提供三种输入模态。

    to adjust how much reasoning the model applies based on the needs of each task. Its post-training also spans a wide range of capabilities, including scientific reasoning, coding, agentic workflows, forecasting, and calibrated prediction. Under the hood, Inkling introduces several architectural innovations beyond a conventional decoder-only Transformer, including query-conditioned relative attention, short causal convolutions throughout the model, and a mixture-of-experts architecture with a sha

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星期四

  1. Cognition 模型 / Devin 博客精选

    Cognition 发布 SWE-1.7 模型

    Cognition 发布 SWE-1.7,称其在更低成本下达到前沿级智能,并已在 Devin(Web、Desktop、CLI)中通过 Cerebras 以 1000 TPS 提供。该模型基于 Kimi K2.7 训练,Cognition 表示其额外训练收益挑战了后训练天花板的说法。文章还介绍了熵保持与训练稳定、跨三大洲多集群训练、数据质量筛选以及自压缩等训练方法。

    a ‘post-training ceiling’ and suggest that RL can push capabilities much further than previously believed. At Cognition, we have been formulating and refining principles for good agentic software engineering both in evaluation, with FrontierCode1,2, and now in training, with SWE-1.7. Our model is particularly optimized for longer-horizon asynchronous tasks, an important component of high-quality software engineering. SWE-1.7 is available today in Devin (Web, Desktop, and CLI) via Cerebras at 10

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星期三

  1. Mistral AI

    Mistral 发布 Robostral Navigate 单目相机导航模型

    Mistral AI 发布 Robostral Navigate,这是其首个面向具身导航的 8B 模型,仅用单个普通 RGB 相机和自然语言指令即可让机器人自主导航,在 R2R-CE validation unseen 上达到 76.6% 成功率,比最佳单相机方案高 9.7 个百分点,比使用深度或多相机的最佳系统高 4.5 个百分点。模型完全自研、不依赖现有开源 VLM,训练数据全部来自仿真,约 240 万条轨迹覆盖 35 万个场景,并采用基于 prefix-caching 的训练算法将训练 token 减少 22 倍。在监督训练后,模型通过 CISPO 在线强化学习进一步提升,成功率提高 3.2%。

    , so we are confident that more training and more experiments will continue to push this number up. What's Next Robostral Navigate is only the first step toward a unified embodied agent. We believe navigation is a foundational capability for general-purpose robotics. By combining large-scale simulation, efficient training, and strong grounding priors, Robostral Navigate demonstrates that state-of-the-art embodied navigation can be achieved with a compact model and a single RGB camera. Start your

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星期三

  1. Claude 应用发布说明精选

    Anthropic 发布 Claude Sonnet 5,主打智能体能力与成本效率

    Anthropic 发布 Claude Sonnet 5,称其为迄今最具智能体能力的 Sonnet 模型,在推理、工具使用、编码和知识工作方面较 Sonnet 4.6 有显著提升,性能接近 Opus 4.8 但价格更低。该模型现已在所有套餐中可用,定价为每百万输入 token 2 美元、每百万输出 token 10 美元,开发者可通过 Claude API 使用 claude-sonnet-5。

    Claude Sonnet 5 is built to be the most agentic Sonnet model yet. It can make plans, use tools like browsers and terminals, and run autonomously at a level that, just a few months ago, required larger and more expensive models. For many developers, the agentic AI era began with Sonnet-class models: Claude Sonnet 3.5, 3.6, and 3.7 were the first models that showed impressive skills in coding and tool use. More recently, though, the clearest gains in agentic capabilities have been in our Opus-clas

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星期四

  1. Liquid AI 模型与工程博客

    Liquid AI 发布 LFM2.5-230M 端侧小模型

    Liquid AI 发布目前最小的模型 LFM2.5-230M,基于 LFM2 架构,预训练 19T tokens 并含 32K 上下文扩展阶段,Base 与后训练版本已在 Hugging Face 开放。官方称其在 Galaxy S25 Ultra 上解码速度 213 tok/s、Raspberry Pi 5 上 42 tok/s,并在 GPQA Diamond、MMLU-Pro、IFEval、BFCLv3/v4 等十项基准上与参数量两倍以上的模型竞争。该模型已适配 llama.cpp、MLX、vLLM、SGLang 和 ONNX,官方同时提示不适合高级数学、代码生成和创意写作等重推理任务。

    On this page Today, we're releasing LFM2.5-230M, our smallest model yet. It’s a fast, lightweight foundation for developers to fine-tune and deploy in agentic workflows. Built on the LFM2 architecture, it delivers exceptionally fast inference and runs everywhere, from cloud GPUs to low-cost CPUs (213 tok/s decode speed on Galaxy S25 Ultra, 42 tok/s on a Raspberry Pi 5). Despite its small size, it’s surprisingly capable at tool use and data extraction tasks. The base (LFM2.5-230M-Base) and post-t

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星期二

  1. Mistral AI

    Mistral 发布 OCR 4 文档解析模型,支持 170 种语言与自托管部署

    Mistral 发布 OCR 4,在提取文本之外返回边界框、块类型分类和逐页逐词置信度分数,支持 170 种语言、10 个语系,可运行在单个容器中实现完全自托管。官方称独立标注者在对比测试中平均 72% 的情况下更偏好 OCR 4,其在 OlmOCRBench 上取得 85.20 分,OmniDocBench 为 93.07 分,但官方也指出这两个基准在评分方式上存在已知局限。API 定价为每 1000 页 4 美元,Batch API 五折后为 2 美元,Document AI 为每 1000 页 5 美元,已通过 Mistral Studio、Amazon SageMaker、Microsoft Foundry 提供。

    Image

    osted deployments. It outperforms leading OCR systems in human evaluations and benchmarks while offering cost-efficient, high-throughput processing for enterprise search, RAG, and agentic workflows. Available via API or Document AI, it provides structured outputs for custom pipelines or no-code applications, with self-hosting options for data privacy. Today, we're releasing Mistral OCR 4, featuring bounding boxes, block classification, and inline confidence scores alongside extracted text. The m

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星期日

  1. Sakana AI:Blog精选

    Sakana AI 发布 Fugu 与 Fugu Ultra 多智能体编排模型

    Sakana AI 发布 Sakana Fugu,把多智能体编排系统做成一个基础模型,通过单一 OpenAI 兼容 API 调用,内部自行完成模型选择、任务委派、验证与结果整合。首发包含 Fugu 和 Fugu Ultra 两个版本,前者兼顾性能与低延迟,后者面向多步难题;官方称 Fugu Ultra 在工程、科学与推理基准上可与 Fable 5、Mythos Preview 比肩。其智能体池可替换,官方表示若某家供应商限制访问,Fugu 会动态绕开,并计划后续纳入开放模型与自家模型。

    We have released Fugu Max, optimized for cost/performance at the Pareto Frontier. We are excited to introduce Sakana Fugu, a new product from Sakana AI that delivers a full multi-agent orchestration system as a single foundation model. Fugu dynamically orchestrates the world’s best models to tackle complex, multi-step tasks, accessible through a single model API. The result is multi-agent intelligence delivering the very best frontier-level performance without any single-vendor dependency or th

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星期二

  1. Qwen Blog

    Qwen 发布 Qwen-Robot Suite 具身基础模型套件

    Qwen 团队发布 Qwen-Robot Suite,包含 Qwen-RobotNav、Qwen-RobotManip 和 Qwen-RobotWorld 三款面向物理世界智能的基础模型。Qwen-RobotNav 基于 Qwen3-VL,用 1560 万样本统一指令跟随、目标导航、目标跟踪与自动驾驶五类任务,在 VLN-CE RxR 上达 76.5% SR,并零样本部署到 Unitree Go2 四足机器人。Qwen-RobotManip 基于 Qwen3.5-4B VL 与 flow-matching DiT 动作头,用超过 38,100 小时开源数据训练,在 RoboChallenge Table30 v1 通用赛道取得第一。Qwen-RobotWorld 以自然语言作为统一动作接口,在 8.6M 视频文本对上联合训练 20 多种本体,在 EWMBench 等基准排名第一。

    nonical space, enabling cross-embodiment training at scale. World co-trains 20+ embodiments via a natural-language action interface under one world model. Together, they enable an agentic system where general intelligence translates directly into physical action. The Qwen family of multimodal foundation models has made remarkable progress in understanding the physical world. Qwen-VL can parse complex spatial relationships, identify objects in cluttered scenes, follow multi-step visual instructio

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  2. xAI News精选

    xAI 发布 Grok Imagine Video 1.5,图生视频模型正式开放 API

    xAI 宣布 Grok Imagine Video 1.5 在 Imagine API 正式可用,模型名为 grok-imagine-video-1.5,同时 Video 1.5 Fast 已上线 grok.com/imagine 及 iOS、Android 应用。官方称这是其目前最好的图生视频模型,音效、环境音与对白在同一次生成中完成,语音更清晰、同步更好,画面运动与物理表现更稳定。Video 1.5 Fast 生成 6 秒 720p 视频约需 25 秒,此前模型需 40 秒以上;未来几天还将上线 Projects、多智能体并行和素材库搜索等功能。

    rolling out new features over the next few days to improve your creative workflow: Projects Organize your work into Projects that appear on the left sidebar. 0:00 / 0:00 Multiple agents Kick off multiple agents in parallel on your projects. Instead of waiting for one generation to finish before starting the next, you can run several prompts at once and let them work for you. 0:00 / 0:00 Search Find any image or video you've made by searching your library — no more scrolling to track down that o

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星期三

  1. Claude 应用发布说明精选

    Anthropic 发布 Claude Fable 5 与 Claude Mythos 5

    Anthropic 发布 Claude Fable 5,一款面向一般用途的 Mythos 级模型,在软件工程、知识工作、视觉、科学研究等基准上表现领先。同时推出 Claude Mythos 5,为同一底层模型但放宽部分安全限制,初期通过 Project Glasswing 向美国政府和网络安全伙伴开放。两款模型定价均为每百万输入 token 10 美元、每百万输出 token 50 美元,低于 Claude Mythos Preview 的一半。

    autonomy and reliability that exceeded previous benchmarks. But what excites us most is the direction it points: a future where developers can hand increasingly ambitious work to agents and trust the results across the software lifecycle.Mario Rodriguez Chief Product Officer These are the strongest results of any Claude model we've had the opportunity to test. Claude Fable 5 is a clear step forward on agentic coding and prototyping.Matt Colyer Director of Product, Developers Claude Fable 5's re

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星期二

  1. Cohere 产品与研究博客精选

    Cohere 开源发布智能体编码模型 North Mini Code

    Cohere 开源发布其首款智能体编码模型 North Mini Code,采用 MoE 架构,拥有 30B 总参数、3B 激活参数,并使用 Apache 2.0 许可证。Cohere 测试显示,其输出吞吐量最高为 Devstral Small 2 的 2.8x,inter-token latency 优势为 30%,Artificial Analysis Coding Index 得分为 33.4。模型权重已在 Hugging Face 提供 bf16、fp8 和 w4a16 版本,也可通过 OpenRouter、Model Vault 或 Cohere API 使用。

    Today we're launching North Mini Code open-source. A mixture-of-experts (MoE) model, North Mini Code is Cohere's first agentic coding model, and the inaugural member of our next generation of powerful models. At 30B total parameters with just 3B active, North Mini Code delivers strong software development performance without demanding extensive hardware to match. Efficient by design, it's built to run where you need it. Freely available under an Apache 2.0 license, North Mini Code advances Coher

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  2. Google DeepMind精选

    Gemini 3.5 Live Translate 发布,支持 70 多种语言近实时语音互译

    Google DeepMind 发布 Gemini 3.5 Live Translate,可自动识别 70 多种语言并持续生成近实时译音,同时保留说话者的语调、节奏和音高。该模型仅落后说话者数秒,支持嘈杂环境和多语言输入。它正向 Android、iOS 版 Google Translate 全球推送,Google Meet 将于本月面向部分企业 Workspace 客户开启私密预览。

    lation. Dive into the demo or more example code in the Gemini Cookbook. By utilizing the Gemini Live API, developer platforms like Agora , Fishjam , LiveKit , Pipecat , and Vision Agents enable developers to build and deploy voice translation apps with ease. These integrations handle the complex real-time media streaming infrastructure, so developers can focus on the user experience. Our partners at Grab are testing the model to enable multilingual communication in near real-time between drivers

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