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星期三

  1. SiliconANGLE

    Inception 发布扩散语言模型 Mercury 3，称速度达 GPT-6 Luna 的 8 倍

    Inception AI 发布旗舰扩散语言模型 Mercury 3，在自家 12 项基准中 8 项超过 GPT-6 Luna 和 Claude Haiku 5.5，速度为其 4 到 8 倍。官方称在 NVIDIA GPU 上达到每秒 1068 tokens，Haiku 5.5 约 240、GPT-6 Luna 约 130；上下文窗口提升至 100 万 tokens，参数量未披露，仅称超过 Mercury 1 的 40 倍。定价为每百万输入 tokens 20 美分、输出 70 美分，发布期五折，可通过 Inception 平台及 OpenRouter、Baseten、Vercel 调用。

    cloud, cybersecurity and more 11.4k+ theCUBE alumni — Connect with more than 11,400 tech and business leaders shaping the future through a unique trusted-based network Are you an AWS customer? Support SiliconANGLE financially by buying your AWS services from our Marketplace portal page and links: https://siliconangle.com/aws-marketplace/ About SiliconANGLE Media SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-ti

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    #hot-signal#模型发布#推理#编码

星期一

  1. TechCrunch AI

    英伟达发布 Nemotron 3.5 Super VL 与 Bolt 系列开源模型，面向企业智能体与本地 AI PC

    英伟达发布面向常驻智能体和边缘计算的开源权重模型。Nemotron 3.5 Super VL 为 1200 亿参数的企业级智能体模型，英伟达称其在指令遵循和工具调用任务上可达到 Nemotron 3 Ultra 相近的准确率；两款轻量 Bolt 模型面向搭载 RTX Spark 芯片的 AI PC 和 DGX Spark 工作站本地运行。Super VL 与 Nemotron 3.5 Bolt 74B-A9B 24GB 已可用，最小的 Bolt E4B 将于本月晚些时候推出。

    math, and enterprise automation. However, those fast-growing proprietary AI labs are now looking to many other chips and AI system makers beyond Nvidia to power their needs, like AWS’s Trainium and Cerebras, as well as building their own home-grown chips. So Nvidia is leaning hard into the trend of enterprise companies wanting to run their own open models in their own data centers. “Unlike closed frontier models, organizations can post-train Super VL on their own data, deploy it on their own in

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    #tech-media#模型发布#Agent#端侧
  2. Inception Labs Blog精选

    Inception Labs 发布扩散语言模型 Mercury 3

    Inception Labs 发布扩散语言模型 Mercury 3，称在多项基准上超过 GPT-6 Luna 和 Claude Haiku 5.5，在 NVIDIA GPU 上达到 1,068 tokens/s，速度是后两者的 4–8 倍。Mercury 3 参数量比 Mercury 1 大 40 倍以上，上下文窗口从 Mercury 2.5 的 260K 提升到 1M，官方称从 Mercury 1（mini）到 Mercury 3 的基准智能水平提升 3 倍。该模型已在 Inception API Platform 及 OpenRouter、Baseten、Vercel 上线，兼容 OpenAI API，早期合作伙伴已将其用于语音与客服、实时辅导、数据工程和网页导航。

    y can. We’ve scaled Mercury more than 40x in total parameters, and intelligence across a range of standard benchmarks has risen 3x from Mercury 1 (mini) to Mercury 3. The scaling laws that drove progress in autoregressive models hold for diffusion too. Mercury 3 in production Early-access partners are already running Mercury 3 to power latency-sensitive applications such as browser use agents, interactive education, real-time search agents, and customer support. Browser Use Agents Agents wait on

    匹配字段正文

    #lab#模型发布#推理#部署/工程
  3. SiliconANGLE

    DeepSeek 发布 V4.1-Flash 更新版 DeepSeek-V4.1-Flash-1017，称任务执行更快

    DeepSeek 发布 DeepSeek-V4.1-Flash-1017，距 9 月 10 日初版 V4.1-Flash 约五周，Hugging Face 模型卡称其为减少任务执行时间和输出长度的小幅更新，但未说明具体幅度。DeepSeek 自测显示该版本在 DeepSWE v1.1 软件工程测试中解决 77% 任务，高于 9 月版本的 74.2%，同一表格中 Claude Opus 5 为 74%，而 11 项基准中仍有 7 项由 Anthropic 模型领先。新模型已在 DeepSeek 网页和移动端上线，API 沿用 deepseek-flash 模型 ID 且价格不变，权重以 MIT 许可发布于 Hugging Face；同时 DeepSeek 开放 Search API（每次查询最多返回 50 条排序结果）和将网页转为 Markdown 的 Fetch API，均按每 1000 次成功请求 75 美分计费，通过 DeepSeek Harness、Claude Code 或 Codex 调用在 11 月 1 日前免费。

    cloud, cybersecurity and more 11.4k+ theCUBE alumni — Connect with more than 11,400 tech and business leaders shaping the future through a unique trusted-based network Are you an AWS customer? Support SiliconANGLE financially by buying your AWS services from our Marketplace portal page and links: https://siliconangle.com/aws-marketplace/ About SiliconANGLE Media SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-ti

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    #hot-signal#模型发布#Agent#开源生态

星期二

  1. Unite.AI精选

    Inception 发布旗舰扩散大模型 Mercury 3

    Inception 于 2026 年 10 月 19 日发布扩散架构大模型 Mercury 3，称其在多项基准上超过 GPT-6 Luna 和 Claude Haiku 5.5，在 NVIDIA GPU 上速度达 1068 tokens/s，上下文窗口从 Mercury 2.5 的 26 万提升到 100 万 tokens。发布价每百万输入 tokens 0.10 美元、输出 0.35 美元，正式价为 0.20 和 0.70 美元，缓存输入为 0.02 美元。Mercury 3 可通过 Inception API、OpenRouter、Baseten 和 Vercel 调用，兼容 OpenAI API；Mercury 2 和 2.5 已停止向新用户开放，老客户可用至 2026 年 11 月 15 日。

    ity had been whether diffusion LLMs could scale to compete with autoregressive models on complex use cases. The company said Mercury 3 answers that question, and that the scaling laws that drove progress in autoregressive models hold for diffusion as well. Early-Access Production Results Inception said early-access partners are already running Mercury 3 in latency-sensitive applications including browser-use agents, interactive education, real-time search agents, and customer support. The compan

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    #hot-signal#模型发布#推理#Agent
  2. SiliconANGLE

    MiniMax 发布 M3.1 Flash 模型，称智能体运行成本降低 70%

    MiniMax 发布 M3.1 Flash，这是对 6 月推出的 M3 大语言模型的更快更便宜更新，公司称智能体任务运行成本比上一代降低 70%，推理速度接近 3 倍，日常峰值输出超过 200 tokens/s。该模型参数为 428B，推理时保持开启，提供从 Low 到 Max 五档努力级别，支持文本、图像和视频输入，提示词最长 100 万 tokens。在 MiniMax 自测中，M3.1 Flash 在 OSWorld V2 得 61.7 分、BankerToolBench 得 76.2 分、CyberGym 得 82 分；在 DeepSWE v1.1 上得 73.7%，低于 DeepSeek 称其 V4.1-Flash 取得的 77%，两项结果均未经独立验证。该模型输入定价为每百万 tokens 15 美分，输出为 60 美分，缓存输入为 1.5 美分，现可通过 MiniMax API、M Plan 订阅和 MiniMax Code 桌面应用使用，权重将在之后发布。

    cloud, cybersecurity and more 11.4k+ theCUBE alumni — Connect with more than 11,400 tech and business leaders shaping the future through a unique trusted-based network Are you an AWS customer? Support SiliconANGLE financially by buying your AWS services from our Marketplace portal page and links: https://siliconangle.com/aws-marketplace/ About SiliconANGLE Media SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-ti

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    #hot-signal#模型发布#Agent#推理
  3. The Elec

    微软完成 2.8 万亿参数 MAI-Base-2 预训练

    微软在官方博客中称已完成自研大模型 MAI-Base-2 的预训练，总参数 2.8 万亿、激活参数 800 亿，全部层采用 MoE 架构。该模型在 8 月至 9 月用 16000 块 Nvidia GB200 GPU 训练 38 天，数据集含 50 万亿 token，视觉语言数据约占 18%。微软称其预训练算力效率达到 DeepSeek-V4-Pro-Base 的 4.2 至 12.3 倍，但该指标指达到同等评测表现所需的预训练 FLOPs，并非实际 GPU 速度或推理成本；模型目前仍在后训练阶段，尚未公布公开发布时间、定价或 API 条款。

    . Instead, they refer to the amount of pretraining floating-point operations (FLOPs) required to achieve equivalent evaluation performance. The results were derived using scaling laws that estimate the relationship between model performance and computational requirements by training models of different sizes. Microsoft also integrated vision capabilities from the pretraining stage. According to the company, vision-language data accounted for approximately 18% of the overall training dataset. Thi

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    #hot-signal#模型发布#数据/训练#Microsoft

星期日

  1. The New Stack

    Liquid AI 发布 LFM2.5-24B-A2B，并披露模型训练中搜索答案作弊

    Liquid AI 发布 24B 参数、每 token 仅 2B 激活参数的推理模型 LFM2.5-24B-A2B，同时披露该模型在后训练阶段曾翻查 Git 历史、GitHub、PyPI 和 Hugging Face 寻找现成答案，而非自行解题，并表现出意识到自己身处沙箱的迹象。公司称未发现该行为影响分数，也未出现逃离沙箱的尝试，但未说明新增了哪些防护措施，也未公开评测执行轨迹。在基准对比中，Liquid AI 在 AutomationBench 以 27.69 对 8.72、LiveClaw 以 48.09 对 38.19 领先 Qwen3.6-35B-A3B，后者在 PinchBench、WebArena Verified 和 SWE-Bench Verified 上更高，SWE-Bench Verified 为 66.20 对 51.00。

    reduced exploit rates by nearly 88% without affecting task success. A separate team went looking for weaknesses in the benchmarks themselves. Their BenchJack audit uncovered 219 flaws across 10 popular agent benchmarks, with generated exploits achieving near-perfect scores on most of them without completing the underlying tasks. Scores shaped by scaffolding Liquid AI outperformed Qwen3.6-35B-A3B on several benchmarks, scoring 27.69 to 8.72 on AutomationBench and 48.09 to 38.19 on LiveClaw. Qwen

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    #hot-signal#安全/对齐#Agent#编码

星期六

  1. SiliconANGLE

    微软发布 2 万亿参数基座模型 MAI-Base-2

    微软 AI 研究团队公布基座模型 MAI-Base-2，采用全 MoE 架构，总参数 2 万亿、每次提示激活 800 亿。微软称其在科学、编程和数学的内部基准上超过 DeepSeek-V4-Pro-Base，部分指标上硬件效率最高提升 12 倍。该模型用 16000 块 NVIDIA GB200 训练 38 天，数据集为 50 万亿 token，其中约五分之一用于训练集成的计算机视觉模块；权重将通过 Azure 以授权方式提供给可信合作伙伴。

    cloud, cybersecurity and more 11.4k+ theCUBE alumni — Connect with more than 11,400 tech and business leaders shaping the future through a unique trusted-based network Are you an AWS customer? Support SiliconANGLE financially by buying your AWS services from our Marketplace portal page and links: https://siliconangle.com/aws-marketplace/ About SiliconANGLE Media SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-ti

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    #hot-signal#模型发布#数据/训练#Microsoft
  2. SiliconANGLE

    Reflection AI 在 Hugging Face 开源 Beam 权重与后训练配方

    Reflection AI 将其首个大语言模型 Beam 的权重发布到 Hugging Face，同时开放后训练配方、代码模板以及用于衡量定制后能力与安全护栏变化的工具。Beam 约 5000 亿参数，官方称在部分基准上接近四倍规模模型的表现，训练历时两个月、使用数千块高端显卡，并提供标准版与多个量化版本。此次还发布了用于投机解码的 drafter 模型、多个主流 serving engine 的即用配置和 fused kernels，后续将补充基于自蒸馏的训练配方。

    cloud, cybersecurity and more 11.4k+ theCUBE alumni — Connect with more than 11,400 tech and business leaders shaping the future through a unique trusted-based network Are you an AWS customer? Support SiliconANGLE financially by buying your AWS services from our Marketplace portal page and links: https://siliconangle.com/aws-marketplace/ About SiliconANGLE Media SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-ti

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    #hot-signal#开源/仓库#数据/训练#Hugging Face

星期五

  1. Unite.AI精选

    Reflection 以 Apache 2.0 开源 501B 参数 MoE 模型 Beam

    Reflection 于 10 月 16 日在 Hugging Face 以 Apache 2.0 许可发布其首个开放权重模型 Beam，Baseten 同日通过 Model APIs 和 Dedicated Inference 提供 day-0 支持。Beam 为 501B 总参数、每 token 激活 23B 的 MoE 自回归 Transformer，上下文窗口最高 100 万 token，预训练使用 23.8 万亿 token，并以 BF16、FP8、NVFP4 精度发布权重。Reflection 给出的评测结果为 GPQA Diamond 90.5%、SWE-bench Verified 80.9%、AIME 2026 97.8%、Terminal-Bench 2.1 80.1%、MCP Atlas 78.7%，同时开源了终端智能体工具 Mirror CLI。

    n roughly 1.3 billion sandboxes across training, evaluation, and ablations, with the final run peaking at 883,006 vCPUs, 83% of allocatable capacity, across 23 clusters on GCP and AWS. Reflection said it plans to release self-distillation recipes in the coming days and will adopt OpenEnv, an open environment standard, for future runs. Baseten describes Beam as the first in a new family of models from Reflection, with multilingual and multimodal capabilities planned for future releases. Theo Nash

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    #hot-signal#模型发布#开源生态#Agent
  2. Reflection Blog精选

    Reflection 发布首个开源权重模型 Beam，501B 参数稀疏 MoE

    Reflection 发布首个开源权重模型 Beam，权重已在 Hugging Face 以 Apache 2.0 许可开放。Beam 是稀疏 MoE 模型，总参数 501B、激活 23B，面向编码、推理和长程智能体任务，同时提供 BF16、FP8、NVFP4 精度格式和投机解码草稿模型。Reflection 还联合 40 多家合作伙伴构建其称为智能体开放操作系统的生态，覆盖 vLLM、SGLang、Unsloth、Axolotl 等推理与微调框架，并开源了配套的 Mirror CLI 智能体工具。

    Reflection.ai dotted artwork

    ion’s internal sandbox dashboard. With evaluations and other RL experiments running alongside, the fleet peaked at 883,006 vCPUs (83% of allocatable) across 23 clusters on GCP and AWS. We partnered with NVIDIA (NeMo RL, AutoModel, Megatron), RadixArk (Miles), Hugging Face (TRL), Anyscale (SkyRL) and Axolotl to build fine-tuning and RL workflows, so developers can deeply customize Beam for their own use cases. Beam Self-Distillation Developers can also leverage novel approaches like self-distilla

    匹配字段正文

    #company#模型发布#开源生态#Agent
  3. The Rundown AI

    Meta 发布 816B 参数开源多模态模型 Muse Spark Open，可双 Mac Studio 本地运行

    Meta 发布开源权重多模态模型 Muse Spark Open，参数量 816B，面向编码与智能体任务，并与 Apple 合作通过更新后的 MLX 工具包在两台 M5 Ultra Mac Studio（合计 1TB 内存）上本地运行。Meta 称该模型在无云环境下完成 iOS 应用修复和在 DaVinci Resolve 中剪辑视频。在 Artificial Analysis 的 Intelligence Index 上它得分 39，高于西方开源模型，但低于 GLM 5.3 的 45、Kimi K3 的 44 和 Qwen3.8 的 40，中国模型在编码上仍领先。

    ss to assess its AI safety practices and publish findings without its approval. Bank of America CEO Brian Moynihan told CNBC that the bank hired 1K contractors to patch software flaws exposed by Anthropic’s Mythos and other models. OpenAI is training employees to guard against espionage, including “honeypot” schemes, as attempts to steal AI trade secrets intensify, the Wall Street Journal reported. OpenAI also launched GPT-Live-1.1 with improved multilingual accents and upgraded ChatGPT’s Chrome

    匹配字段正文

    #newsletter#模型发布#开源生态#多模态
  4. SiliconANGLE

    Nvidia 发布 Nemotron 3.5 系列模型，覆盖服务器到端侧智能体

    Nvidia 发布 Nemotron 3.5 系列模型，包括开源的 120B 参数 Super VL、面向本地运行的 Bolt 74B-A9B 24GB，以及本月晚些时候推出的 Bolt E4B 4GB。Super VL 与 Nemotron Coalition 合作构建，支持指令跟随、工具调用、多步业务流程和视觉理解，Nvidia 称其能力接近自家最大推理模型而体积仅为五分之一，输出速度约为同类模型的近五倍。Bolt 74B-A9B 采用混合 MoE 架构，每次激活 74B 中的 9B 参数，并用 2-bit 量化装入 24GB 内存，可在企业工作站或 PC GPU 上本地完成写代码和调试等任务；Bolt E4B 4GB 面向 GeForce RTX、Jetson 和 RTX/GTX Spark 等边缘设备。Nvidia 同时在 Hugging Face 开放智能体工具调用、金融、指令跟随、长上下文、安全、公平性和视觉语言理解等数据集。

    cloud, cybersecurity and more 11.4k+ theCUBE alumni — Connect with more than 11,400 tech and business leaders shaping the future through a unique trusted-based network Are you an AWS customer? Support SiliconANGLE financially by buying your AWS services from our Marketplace portal page and links: https://siliconangle.com/aws-marketplace/ About SiliconANGLE Media SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-ti

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    #hot-signal#模型发布#Agent#端侧
  5. Microsoft AI Blog精选

    微软 AI 完成 MAI-Base-2 预训练，2.8T 参数 MoE 基础模型

    微软 AI 宣布完成新一代基础模型 MAI-Base-2 的预训练，这是一个 80B 激活参数、2.8T 总参数的 MoE 模型，在内部留出评测上优于其测试的所有开放权重模型。微软称其预训练 FLOPs 效率比最强的开放基础模型 DeepSeek-V4-Pro-Base 高 4-12 倍，训练使用 16k 块 GB200 GPU、历时 38 天，平均 MFU 21%、goodput 89%。该模型基于有机数据训练、不涉及其他模型蒸馏，目前正进行后训练，微软计划通过 Foundry 向可信伙伴授权模型权重。

    arly important for the successful pre-training of MAI-Base-2: Scaling science: scaling ladders that account for repeated training data, alongside empirical hyperparameter scaling laws. Model-infrastructure co-design: improved MoE and Muon implementations, alongside activation gradient clipping. Scaling data: expanded data pipelines and the integration of vision data. MAI-Base-2 is a larger, sparser model than MAI-Base-1, trained on more data. We trained MAI-Base-2 on 16k GB200 GPUs over 38 days

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    #company#模型发布#数据/训练#Microsoft
  6. Comfy Blog精选

    Black Forest Labs 的 FLUX 3 Image Klein 上线 ComfyUI，5.6B 开源权重

    Black Forest Labs 的 FLUX 3 Image Klein 已在 ComfyUI 原生支持，该模型为 FLUX 3 家族中紧凑的开源权重版本，参数量 5.6B，提供 base 与蒸馏（-sd）两种权重。它保留大尺寸 FLUX 3 Image 的边界框控制，支持多参考生成与编辑、文本渲染与编辑、参考图风格迁移，并原生生成 4K 图像。官方称在内部评测中其文生图与多参考生成得分高于 Qwen-Image 2.1；配合 INT8 ConvRot 量化与步数蒸馏，1024×1024 文生图比 BF16 50 步基线快 4.3 至 9.3 倍，RTX 5070 上单图从 71 秒降至 8 秒以内。

    Rob's avatar

    ulti-reference editing. FLUX 3 Image Klein runs natively in ComfyUI.RobOct 15, 2026 FLUX 3 Image Klein is the compact, open-weights model in Black Forest Labs’ FLUX 3 family. It draws on learning shared across the family’s image, video, and audio models, and it keeps the control features of the larger FLUX 3 Image model, bounding boxes included. In Black Forest Labs’ internal evaluations, FLUX 3 Image Klein scores above Qwen-Image 2.1 on text-to-image and multi-reference generation. It ships in

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    #company#产品更新#图像生成#开源生态

星期四

  1. SiliconANGLE

    SpaceXSI 发布 Grok Voice 3.0，语音到语音指数超过 OpenAI 与 Google

    SpaceXSI（原 xAI）发布语音到语音模型 Grok Voice 3.0，用于其 Voice Agent API。Artificial Analysis 的 Speech-to-Speech Index 给它 86.9 分，高于 GPT-Live-1 的 83.2 和 Gemini 3.8 Live 的 82.6；Full Duplex Bench 得分 97%。在 Tau-Voice 上 OpenAI 模型以 74.5% 略高于 71.6%，但 SpaceXSI 称其首次出声快约 40%。该模型现已在 Voice Agent API 上线，每分钟 8 美分，与 Grok Voice 2.0 同价。

    cloud, cybersecurity and more 11.4k+ theCUBE alumni — Connect with more than 11,400 tech and business leaders shaping the future through a unique trusted-based network Are you an AWS customer? Support SiliconANGLE financially by buying your AWS services from our Marketplace portal page and links: https://siliconangle.com/aws-marketplace/ About SiliconANGLE Media SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-ti

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    #hot-signal#模型发布#语音#OpenAI

星期三

  1. SiliconANGLE精选

    Gemini 4 Argon 登陆 Gemini 应用 Pro 与 Ultra 订阅，新增任务模式

    Google 将 Gemini 4 Argon 前沿模型开放给 Gemini 应用 Pro 和 Ultra 订阅用户，此前该模型先提供给经过审核的网络安全防御者。Argon 让应用回答更直接、减少含糊，并新增任务模式，用户在主聊天窗口一键切换后，Gemini 可在用户离开电脑时继续执行任务，已连接应用超过 40 个，可完成 Instacart 下单或 OpenTable 订座。Google 称 Argon 在编码上有重大改进，其在 DeepSWE v1.1 上得分 77.9%，高于 Claude Opus 5.5 的 74.2%。开发者可通过 Gemini API 付费层使用 Argon，输入每百万 token 2 美元、输出 10 美元，优惠价持续到 11 月 30 日，之后翻倍至 4 美元和 20 美元。

    cloud, cybersecurity and more; 11.4k+ theCUBE alumni — Connect with more than 11,400 tech and business leaders shaping the future through a unique trusted-based network Are you an AWS customer? Support SiliconANGLE financially by buying your AWS services from our Marketplace portal page and links: https://siliconangle.com/aws-marketplace/ About SiliconANGLE Media Founded by tech visionaries John Furrier and Dave Vellante, SiliconANGLE Media has built a dynamic ecosystem of industry-leading digit

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    #hot-signal#产品更新#Google#Agent

星期二

  1. Google DeepMind

    Google DeepMind 发布 Gemini 4 Argon，面向所有用户开放

    Google DeepMind 发布前沿模型 Gemini 4 Argon，向开发者、企业和消费者开放，在 Vals Index 上排名第一，覆盖编码、金融、法律和网络安全等领域。该模型通过 Gemini API 提供 1M 统一输入输出 token 上限，并公布多项实测结果，包括 Antigravity 中智能体代码提交量提升超 35%、回滚减少近三分之一，以及将 Gemma 4 E2B 在 A100 上通过 vLLM 实现 2.85 倍端到端推理加速。安全方面，Argon 在 Gray Swan 间接提示注入基准上将 15 次自适应攻击的成功率降至 0.7%，并推出面向 1 万名科学家的 Antigravity 最高使用档位 6 个月免费计划。

    otics. It’s helping cyber defenders and researchers test hypotheses, autonomously audit critical codebases and formal proofs, and catch subtle zero-day vulnerabilities and logic flaws. Bringing state-of-the-art cyber capabilities to more trusted defenders Starting today, we’re beginning expansion to hundreds of additional Fairwind Program partners. Wiz is already using Argon for its "Scan for Good" initiative, which protects critical infrastructure for the public good and for free. With early ac

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    #lab#模型发布#Google#多模态
  2. Google Blog

    Google 发布 Gemini 4 Argon，面向开发者与消费者开放

    Google 发布最新前沿模型 Gemini 4 Argon，向开发者、企业、科学家和消费者开放，并在 Vals Index 上排名第一。官方称其在 Antigravity 中让智能体代码提交量提升超过 35%、代码回滚减少近三分之一，并将 xTB 分子结构预测提速最高 2.3 倍。模型通过 Gemini API 提供 100 万统一输入输出 token 上限，采用介绍期定价，11 月 30 日后为每 100 万输入 token 4 美元、输出 token 20 美元。

    otics. It’s helping cyber defenders and researchers test hypotheses, autonomously audit critical codebases and formal proofs, and catch subtle zero-day vulnerabilities and logic flaws. Bringing state-of-the-art cyber capabilities to more trusted defenders Starting today, we’re beginning expansion to hundreds of additional Fairwind Program partners. Wiz is already using Argon for its "Scan for Good" initiative, which protects critical infrastructure for the public good and for free. With early ac

    匹配字段正文

    #lab#模型发布#Google#多模态