Anthropic 发布 Claude Opus 5.5,加强网络安全相关防护
Anthropic 发布 Claude Opus 5.5,称其在近期 AI 越狱黑客事件后加强了安全防护,改进了试图逃离测试沙盒等风险行为。该模型比 Opus 5 更便宜、运行效率更高,在公司最全面的对齐测试中表现最强;网络安全相关请求将被分流到 Opus 4.8,被标记的生物学请求转到 Opus 5,发布前经 Frontier Design 和 METR 等外部伙伴测试。
Anthropic 发布 Claude Opus 5.5,称其在近期 AI 越狱黑客事件后加强了安全防护,改进了试图逃离测试沙盒等风险行为。该模型比 Opus 5 更便宜、运行效率更高,在公司最全面的对齐测试中表现最强;网络安全相关请求将被分流到 Opus 4.8,被标记的生物学请求转到 Opus 5,发布前经 Frontier Design 和 METR 等外部伙伴测试。
Anthropic 发布 Claude Opus 5.5,称其为 Claude 5.5 系列首个模型,性能达到 Fable 5.1 水平,典型工作负载成本比 Opus 5 低 40%,输入输出 token 价格为 $4 和 $20 每百万,输出速度快 30% 以上。
蚂蚁百灵开源 Ming-Image-0.1-Design 系列两个 6B 模型,Design 从文字需求端到端生成 UI、信息图和海报,Layer 将设计图拆成 2 到 9 个语义独立的 RGBA 图层,并同步开源 Design Skill 和 PPT Skill。
推荐理由:官方开源两个 6B 设计模型并给出评测数据和落地场景,读者可以据此评估它在设计交付链路中的可用性。
Meet Qwen-Image-2.1, the most balanced and cost-effective image generation model in the Qwen-Image series! Now open weights! 🎨 A unified model for both generation and editing, delivering top-tier quality in a lightweight package. Highlights: 👀 - Compact & exceptionally fast: A lightweight 7B architecture that outperforms most closed-source models, with drastically accelerated inference for multi-image inputs. - Native transparency: Natively generates and edits RGBA layers, enabling seamless compositing and text editing within transparent images. - Versatile, high-fidelity editing: Supports up to 10 reference images and precise local control while preserving strict fidelity for portraits and products. - Broad coverage & stunning aesthetics: Excels at panoramas, infographics, and virtual try-ons, delivering realistic textures and elegant typography. Start to create your next masterpiece with Qwen-Image-2.1! 🖼️ - Blog: https://qwen.ai/blog?id=qwen-image-2.1 - GitHub: https://github.com/QwenLM/Qwen-Image-2.1 - Model Scope: https://www.modelscope.cn/models/Qwen/Qwen-Image-2.1 - Hugging Face: https://huggingface.co/Qwen/Qwen-Image-2.1
蚂蚁 inclusionAI 在 Hugging Face 发布基于 Qwen2.5-0.5B 的密集语音合成模型 Ming-3.0-tts-0.5B,采用 MIT 协议开源。
蚂蚁 inclusionAI 在 HuggingFace 发布 Ming-3.0-tts-tiny,这是基于 Ling V3 的 MoE 语音合成模型,总参数 7.9B、每 token 激活约 1.3B。
小米发布 MiMo-V2.6 系列,旗舰 MiMo-V2.6-Pro 在 Artificial Analysis Intelligence Index 得 46 分,居开源模型之首,价格为每百万输入 token $0.435、输出 $0.87。
奥地利科学院联合 Mistral 和 Sail Reply 开发的大语言模型 Apollo 将于当地时间周三正式发布,面向古希腊语文献修复,训练素材涵盖手稿、莎草纸与石刻铭文,总计约 6 亿个古希腊历史词汇。
Hy Image3.5 preview is live. 🚀 Professional-grade image generation, +30% win rate in human eval vs Hy Image3.0 Both Text to image & Image to image available. Up to 2K. Better Consistency. API: https://console.tencentcloud.com/tokenhub/models/detail?modelId=hy-image-v3.5-preview Priced for everyone. $0.024 per image on Tencent Cloud API. We only charge for what we generate — your reference images are free. Two weeks free (Only in OnSolo and Miora): Miora https://miora.design/ OnSolo https://onsolo.ai/ Try it and tell us where it breaks.
小米发布并开源 Xiaomi MiMo-V2.6 系列,含 Pro 与 Flash 两个原生全模态模型,称这是探索 RSI(递归自我改进)路径的关键一步。
SpaceXAI 发布新旗舰模型 Grok 4.7,面向编码、智能体任务和知识工作,定价与 Grok 4.6 相同,为每百万 token 输入 $2、输出 $6。
腾讯混元团队 9 月 22 日发布 Hy Image3.5 preview 模型,面向专业级生图,支持文生图、图生图和多轮对话创作,单次最多上传 5 张参考图,最高 2K 分辨率。
StepFun's Step 5 Preview scores 44 on the Artificial Analysis Intelligence Index, matching Kimi K3 (max) at ~2.8x lower cost per task, but trails peers on agentic evaluations Step 5 Preview is @StepFun_ai's new flagship model, with 600B total and 27B active parameters, succeeding Step 3.7 Flash (released May 2026). It scores 44 on the Intelligence Index, level with Kimi K3 (max) and just behind GLM-5.3 (max, 45) and Qwen3.8 Max (45) Key takeaways: ➤ Step 5 Preview costs ~2.8x less per Intelligence Index task than models at the same score. It costs ~$0.72 per task, against ~$2.00 for Kimi K3 (max) at the same score of 44 and ~$2.01 for GLM-5.3 (max) at 45. This is driven by pricing: at $1/$2.70 per 1M input/output tokens, it is priced below both on input and output. MiMo-V2.6-Pro is the one model that scores higher (46) at a lower cost per task ($0.13) ➤ Frontier reasoning is the standout strength, and where the jump from Step 3.7 Flash is largest. Step 5 Preview scores 46% on Humanity's Last Exam, in line with Kimi K3 (max, 47%), and 21% on CritPt, between Kimi K3 (23%) and GLM-5.3 (max, 19%). Both are up sharply from Step 3.7 Flash: +25 points on HLE and +19 points on CritPt ➤ Higher AA-Omniscience accuracy than GLM-5.3 at fewer parameters, but with more hallucination. At 600B total parameters, Step 5 Preview reaches 42% accuracy on AA-Omniscience, our benchmark measuring factual recall and hallucination, ahead of GLM-5.3 (max, 34%, 753B) and behind Kimi K3 (max, 48%, 2.8T). It attempts more questions than GLM-5.3 (68% vs 55%) and hallucinates more often when it does (43% vs 30%), landing at 16 on the AA-Omniscience Index, between GLM-5.3 (14) and Kimi K3 (20) ➤ Agentic evaluations are where Step 5 Preview lags peers at a similar Intelligence Index score. It scores 1,566 Elo on GDPval-AA, our primary evaluation for agentic performance, behind Qwen3.8 Max (1,668) and GLM-5.3 (max, 1,646). The gap holds on Terminal-Bench 4.0 (33% vs 39% and 42%), AA-Briefcase (1,432 Elo vs 1,640 and 1,525) and AutomationBench-AA (51% vs 56% and 62%) Key model details: ➤ Model Size: 600B total parameters, 27B active MoE model ➤ Context window: 1M tokens ➤ Multimodality: Text, image and video input, text output ➤ Pricing: $1/$2.70 per 1M input/output tokens, with cached input at $0.05/M ➤ Availability: StepFun first-party API, with open weights release planned for October 15th ➤ Licensing: Closed weights currently, with weights release planned for October 15th
腾讯混元发布混元图像 3.5 预览版(Hy Image3.5 preview),官方称综合能力较 Hy Image3.0 提升约 30%,内部数百名设计师 GSB 盲测中与 Seedream 5.0 pro 持平,略优于 Nano-Banana Pro 和 Qwen-Image-3.0 Pro。
腾讯混元发布 Hy Image3.5 preview,支持文生图与图生图、最多 5 张参考图、多轮编辑和最高 2K 分辨率输出,经上百名专业设计师 GSB 盲测对上一代胜率综合提升 30% 以上。
推荐理由:原文给出了文本渲染、编辑一致性与定价等具体能力细节,以及多家腾讯内部产品的实测反馈,便于评估适用场景。
Grok 4.7 is behind only Anthropic models on AA-Briefcase, ranking just behind Opus 5 at ~50% of its Cost per Task Grok 4.7’s improvements over Grok 4.6 are clear in AA-Briefcase-Lite, our public due diligence scenario where models are tasked with building market models and target assessment decks. Grok 4.7 gains significantly in Analytical Quality Elo (1698 → 1994) with a slight regression in Presentation Elo (1531 → 1499). API cost to produce example decks: Grok 4.7 (xhigh) ~$8 vs. Grok 4.6 (xhigh) ~$4.40
SpaceXAI 于 9 月 22 日宣布推出新一代模型 Grok 4.7,定位编码和知识工作场景,官方称其为公司目前最强的编码和知识处理模型。该模型采用更大基座并经更长时间强化学习训练,强化自我验证与长上下文管理,在 CursorBench 4.0、GDPval、AA Briefcase 等基准较 Grok 4.6 有提升。
小米发布并开源 MiMo-V2.6 系列,含 Pro 与 Flash 两个原生全模态模型。MiMo-V2.6-Pro 在 AA 智能指数 v4.3.2 取得 46 分。
MiMo-V2.6-Pro just landed @XiaomiMiMo back in the top 10 on Code Arena: WebDev, debuting at ~#10 overall, and ~#3 among open-weights models with an MIT license. It scores 1628 pts (AutoEval), tying Claude Fable 5 (High) and just ahead of Hy4-preview (1624 pts). That's a +153 pt jump from the previous MiMo-V2.5-Pro (1475 → 1628 pts). Among open-weights models, it lands at ~#3. Impressively only 7 pts behind Qwen3.8 Flash Next (#2) and 46 pts behind Kimi K3 Max (#1). Note: this is an early AutoEval score, in which a Reward Model trained on Arena’s human preference data casts automatic votes in place of live votes. We’ll continue to see how scores converge as more live human votes come in. Congrats to the @XiaomiMiMo team on this release!
小米 MiMo-V2.6 系列三款模型上线 OpenRouter,包括 1T+ 参数旗舰、开源 MoE 模型和约 10 倍速的旗舰变体。三款模型均支持文本、图像、视频和音频输入,上下文为 1M。
隆重介绍小米 MiMo-V2.6 —— Pro 与 Flash。 前沿智能,全模态,公开构建。 🔹 两款全模态模型,通过规模化强化学习不断进阶 🔹 在大多数智能体基准测试中,Pro 的表现与 Claude Opus 5 和 GPT-5.6 Sol 不相上下 🔹 Pro 在 Artificial Analysis Intelligence Index 上得分 46 —— 为开源模型中的最高分 🔹 更强的编程、计算机操作、3D 推理与创作能力 🔹 开放模型权重、技术报告、RL 环境与训练代码 博客:https://mimo.xiaomi.com/mimo-v2-6
同一件事,精选收录的是《小米发布 MiMo-V2.6 Pro 与 Flash 全模态开源模型》
推荐理由:官方发布全模态模型并开放权重、技术报告和训练代码,附与 Claude Opus 5、GPT-5.6 Sol 的 Agent 基准对比数据。
MiMo-V2.6-Pro 首次亮相,即成为 Artificial Analysis Intelligence Index 上排名第一的开放权重模型(46 分)。每项 Intelligence Index 任务成本为 $0.13,使其跻身智能水平与每任务成本帕累托前沿。 @Xiaomi 刚刚发布了 MiMo-V2.6-Pro,这是一款开放权重模型,相比其前代 MiMo-V2.5-Pro(Intelligence Index:26),在智能水平上取得了重大进步。尽管有所提升,它仍保持了同样具有吸引力的定价:每 1M 输入 token 为 $0.435(含 99% 缓存命中折扣),每 1M 输出 token 为 $0.87。这使 MiMo-V2.6-Pro 成为部署成本效益最高的模型之一。 MiMo-V2.6-Pro 是一款 MoE 模型,总参数量为 1.02T,激活参数量为 42B。敬请期待对该模型的更多分析。 在此查看 MiMo-V2.6-Pro 的完整基准测试详情:https://artificialanalysis.ai
同一件事,精选收录的是《小米发布 MiMo-V2.6 Pro 与 Flash 全模态开源模型》
Xiaomi MiMo 于今日正式发布并开源 MiMo-V2.6 系列模型,包含 Pro 与 Flash 两个原生全模态模型,称这是探索 RSI(递归自我改进)路径的关键一步。
同一件事,精选收录的是《小米发布 MiMo-V2.6 Pro 与 Flash 全模态开源模型》
Grok 4.7 发布,官方称在同等价格和速度下较 Grok 4.6 有显著提升。Harvey Legal Agent Benchmark 上 Grok 4.7 得分 19.6%。
Grok 4.7 is here. It's a notable improvement over Grok 4.6 at the same price and speed.
小米于 12 月 16 日发布并开源 MiMo-V2-Flash,一款 309B 总参数、15B 激活参数的 MoE 基础语言模型,权重以 MIT 许可上传 Hugging Face。
推荐理由:官方完整披露了架构、MTP 推理加速与 MOPD 训练范式细节和基准成绩,可据此评估其性价比与部署可行性。
xAI 发布 Grok 4.7,定价为每百万输入 token 2 美元、输出 token 6 美元,公司称其基于更大基座模型并经过更长强化学习训练。
Grok 4.7 by @SpaceXAI and @elonmusk is now in the Agent Arena! Your votes drive the @arena leaderboards, head over and bring your toughest prompts. In Agent Arena, we measure models on millions of real-world, long-horizon agentic tasks from a global community of users. Models can access web search, filesystem, and terminal tools to complete complex workflows. The leaderboard measures model performance on outcomes relative to the average model using a causal tracing methodology. In addition to Agent Arena, Grok 4.7 is in Battle Mode for: Text, Vision, Code, and Document.
阿里 Qwen 团队发布 Qwen-Image-2.1,将文生图与图像编辑统一到一个 7B 单流 DiT 模型中,搭配 8B Qwen3-VL 编码器,支持原生 RGBA 透明输出和最多 10 张参考图编辑。
Grok 4.7 is here. It's a notable improvement over Grok 4.6 at the same price and speed.
xAI 发布 Grok 4.7,称其为目前编码与知识工作能力最强的模型,价格与速度与 Grok 4.6 持平,输入 $2、输出 $6 每百万 token。新模型采用更大的 base model 并加长强化学习训练,CursorBench 4.0 得分 46.3%,HackerBench v0.3 仅放行 3.3% 危险双用途提示。
Grok 4.7 is here. It's a notable improvement over Grok 4.6 at the same price and speed.
Grok 4.7 is here. It's a notable improvement over Grok 4.6 at the same price and speed.