Qwen@Alibaba_QwenAI 评分5050Qwen3.8-2.4T-A95B is now live on Fireworks with Day-0 support! This 2.4T parameter MoE model is built for autonomous agents, heavy coding, large context windows, and is ideal for coding and agentic performance. Start building today: https://fireworks.ai/models/fireworks/qwen3p8-max
Qwen@Alibaba_QwenAI 评分5959Qwen3.8-2.4T-A95B is going open weight: 2.4T parameters, with 95B active, and Nebius Token Factory is joining as a Day 0 launch partner. Qwen3.8-2.4T-A95B is coming to Nebius Token Factory Managed Services for dedicated inference. @Alibaba_Qwen @alibaba_cloud
Qwen@Alibaba_QwenAI 评分4747Now available: @Alibaba_Qwen 3.8-2.4T-A95B from @alibaba_cloud on DigitalOcean Serverless Inference via NVIDIA HGX™ B300 GPUs. 🤖 1M context, built for long-horizon coding. 🔗 https://do.co/45VBAyZ One API, usage-based pricing, no infra to manage.
Qwen@Alibaba_QwenAI 评分4545🎉 Qwen3.8-27B is here from @Alibaba_Qwen, and the whole thing fits on a single GPU. Same hybrid backbone as the 2.4T flagship, dense instead of MoE. Day-0 support in vLLM. 🚀 What is in it for serving ✨ - Fits one Blackwell GPU in every precision. Qwen ships BF16 and FP8, the NVFP4 build from @inferact - 262K native context, stretching to 1M. At that length one GB300 still has room for roughly 6.6M KV tokens. Six full-length sequences in flight, on one GPU - An MTP draft head rides inside the checkpoint, so speculative decoding needs no separate speculator repo. Acceptance on short prompts measured 92.2% in BF16 and 84.8% in FP8 Verified end-to-end on @NVIDIA GB300: BF16 and FP8 at TP4, NVFP4 at TP1, tool calls working, correct generations at 1M context. Two prerequisites, vLLM nightly and transformers 5.8.0+. 🔗 http://recipes.vllm.ai/Qwen/Qwen3.8-27B
Z.ai@Zai_org精选AI 评分6666推荐理由：比单点漏洞发现更值得关注的是 GLM-5.3 在多步利用任务上的提升，这细分了安全团队能够交给模型的工作类型，从定位缺陷到验证攻击路径。
Qwen@Alibaba_Qwen精选AI 评分7171推荐理由：官方称 27B 稠密多模态模型整体表现超过 Qwen3.7-Plus，262K 原生上下文可扩至 1M，Apache 2.0 协议下本地部署轻量应用多了一个更高效的选择。
Qwen@Alibaba_QwenAI 评分5050Qwen3.8-2.4T-A95B is live on Together AI. The Qwen team’s new open-weight MoE packs 2.4T total parameters with 95B active, a 1M context window, and strong coding & agent capabilities. Start building: https://www.together.ai/models/qwen3-8-max
Qwen@Alibaba_QwenAI 评分4545Qwen3.8-2.4T-A95B is now live on Fireworks with Day-0 support! This 2.4T parameter MoE model is built for autonomous agents, heavy coding, large context windows, and is ideal for coding and agentic performance. Start building today: https://fireworks.ai/models/fireworks/qwen3p8-max
阿里千问大模型公众号宣布正式开源 Qwen3.8-27B，所有开发者、科研机构和企业均可自由下载、部署和使用。该模型为原生多模态稠密模型，支持 262K 原生上下文，可通过 YaRN 技术外推至 1M Tokens。较 Qwen3.6-27B，新模型在编程和办公场景性能大幅提升，表现超越 Qwen3.7-Plus，并新增 reasoning_effort 功能以按任务难度控制思考深度。
Unsloth AI@UnslothAI精选AI 评分7676Unsloth 发布 Qwen3.8-27B 的 Dynamic GGUF 量化版本，4-bit 量化可在 17-19GB 内存设备上本地运行，并同时上传 NVFP4 量化。
我们承诺过开源 Qwen3.8 的模型权重。现在，是时候见面了！🎉 ⚡ Qwen3.8-27B： - 一款原生多模态稠密模型。仅凭 27B 参数，综合表现超越 Qwen3.7-Plus，在真实世界的编码与办公工作流中尤为亮眼。 - 原生支持 262K 上下文，可通过 YaRN 轻松扩展至 1M tokens。 - 为开发者而生。高效、高质量，并采用 Apache 2.0 许可证。 🚀 Qwen3.8-2.4T-A95B（Max 级别）的开放权重也已于近日发布。 无论你是想用 Qwen3.8-27B 在本地部署轻量级应用，还是用 Qwen3.8-2.4T-A95B 构建智能体，它们现在都属于你了！ 下载、部署，去构建我们尚未想象到的东西吧。👀👇 - Hugging Face： https://huggingface.co/collections/Qwen/qwen38 - ModelScope： https://www.modelscope.cn/collections/Qwen/Qwen38
推荐理由：原文给出了本地运行的具体内存门槛、量化版本和硬件对照表，读者可以据此判断能否在自己的设备上跑通这个 27B 模型。
Qwen@Alibaba_QwenAI 评分4141不到 2 小时就要见面了👋。时间快到了！很快见：👀 https://huggingface.co/Qwen/Qwen3.8-27B
Rohan Paul@rohanpaul_aiAI 评分5252Introducing GLM-5.3: Built to Code. Ready for Cyber Defense. - Top-tier coding and agentic capabilities, achieved through post-training on the 743B base model - A major leap in cybersecurity, setting a new standard among open models Tech Blog: https://z.ai/blog/glm-5.3
小红书技术开源 dots3-note Preview，这是 dots3 系列最轻量模型，总参数 280B、激活参数 16B，支持 512K 上下文及文本、视觉、语音多模态理解，并针对复杂推理和长程 Agent 任务优化。
推荐理由：除开源模型外，TEMPO 让同一智能体在每个宏观步骤切换为 critic，用测试时推理估计回报，给稀疏奖励长程任务的强化学习训练提供了可借鉴的结构。
智谱发布 GLM-5.3，与上一代 GLM-5.2 共享相同基座，全部提升来自扩展的后训练，并称其为最强开源权重编程模型，智能体任务进步最大。该模型经安全数据训练，在 269 个项目中找到 2,436 个漏洞，部分漏洞存在长达 40 年。GLM-5.3 现可通过 GLM Coding Plan 使用，权重将在安全审查完成后于两周内开源。
Z.ai 发布 GLM-5.3，沿用 GLM-5.2 的 743B 基座模型，全部提升来自扩展的后训练。Terminal-Bench 3.0 得分从 4.6 升至 28.3，CyberGym 达 84.5%，超过 Mythos 5（83.8%）和 GPT-5.6 Sol（83.6%）。模型已通过 Z.ai API、GLM Coding Plan 和 ZCode 提供，权重预计在发布约两周后公开。
MiniMax 今日推出音乐生成模型 MiniMax-Music3，可根据歌词和音乐描述生成最长 5 分钟的完整歌曲。该模型采用分层自回归架构，Global LLM 参数规模为 8B（基于 Qwen3-8B 初始化），Local LLM 参数规模为 0.6B，输出格式为 32kHz、16-bit 立体声 WAV 文件。官方称其能在长音频中保持音乐主题、节奏、歌声身份和编曲推进。
智谱今日发布 GLM-5.3，基于与 GLM-5.2 相同的基座模型，通过后训练 Scaling 将编程能力提升 50%，在 Terminal Bench 3.0、Agents' Last Exam (CLI) 等公开基准中取得开源第一。
Cactus Compute 发布 Needle 2，一个 45M 参数的开源工具调用模型，以 14MB 二进制文件发布，约 28MB RAM 即可运行完整会话。
jietang@jietangAI 评分5151Introducing GLM-5.3: Built to Code. Ready for Cyber Defense. - Top-tier coding and agentic capabilities, achieved through post-training on the 743B base model - A major leap in cybersecurity, setting a new standard among open models Tech Blog: https://z.ai/blog/glm-5.3
智谱发布GLM-5.3，基于与GLM-5.2相同的基座，通过极致的后训练Scaling提升智能上界，编程能力较前代提升50%，在Terminal Bench 3.0等公开基准中取得开源第一，并接近Claude Fable 5。模型在白盒代码审查等安全任务中表现持平Mythos 5，在CyberGym测试中得分84.5%。模型权重将在两周后开源，即日起上线ZCode、AutoClaw等工具。
SiliconFlow@SiliconFlowAI精选AI 评分6565推荐理由：每百万缓存命中 0.44 美元与 1M 上下文组合，使 Agent 工作流在长上下文成本测算上有了更具体参照。
Meituan LongCat@Meituan_LongCatAI 评分4848LongCat-2.0 from @Meituan_LongCat is free in Nous Portal for one week. It is a 1.6T-parameter MoE with 1M context built for agentic coding, scores 70.8 on Terminal-Bench 2.1, and can ingest an entire codebase in one pass. Try it out at https://portal.nousresearch.com
谷歌推出专为编程与 Agents 场景打造的 Gemini 3.7 Flash 模型，距 3.6 Flash 发布仅约三周，在软件工程、知识工作及网页开发工作流方面大幅提升。
Tibo@thsottiauxAI 评分4242Previewing Ultrafast mode: GPT-5.6 Sol at up to 14x the speed. Launching first in the OpenAI API to a select group of customers with expanded access to more businesses as capacity grows.
Josh Woodward@joshwoodwardAI 评分4545Introducing Gemini 3.7 Flash : ) - it is fast! - 50% lower price than 3.6 flash (through end of year) - strong intelligence increase in only ~3 weeks (thanks to some awesome algorithmic improvements) - available in the API, AI Studio, Antigravity, and more!
MiniMax (official)@MiniMax_AIAI 评分4646Music 3 也开源了！！🙌 已在 @ComfyUI 本地可用 “在 AGI 到来之前，我们将一直保持开源。”💙 云端版本即将推出。
MiniMax Music 3 by @MiniMax_AI is now on ComfyUI! Available locally in Comfy, Cloud coming soon!
Writer 周四推出新旗舰模型 Palmyra X6，基于 Z.ai 开源模型 GLM-5.2 构建，结合框架基础设施升级，预计可为客户在基础任务上削减高达 50% 的成本。该公司同时发布标准智能体框架的重大升级，两项功能即日起对客户开放。Writer 研究显示，框架效率优化比模型选择更能可靠降低成本，测试中成本平均下降 40%。
Rohan Paul@rohanpaul_aiAI 评分6161Our Flash models are workhorses that offer performance at a great price. So, we're shipping updates fast to get them in developers’ hands. And now just 3 weeks after launching 3.6 Flash, 3.7 Flash shows significant gains including in coding and agentic work. It delivers substantial improvements across software engineering, knowledge work, and web development, all with an introductory price at half the original cost of 3.6 Flash. We've gotten positive feedback from early users, including our own engineers using 3.7 in @Antigravity, and we’re excited for you to try it there. Also available via Gemini API in @GoogleAIStudio, Gemini Enterprise & more, full list and details here: https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-3-7-flash/
Artificial Analysis@ArtificialAnlysAI 评分7272Google 发布 Gemini 3.7 Flash，在 Artificial Analysis 智能指数上得分 56，较 3.6 Flash 提升 4 分，并登上智能 vs. 单任务耗时帕累托前沿。
Elon Musk@elonmuskAI 评分4444Congrats to @SpaceXAI on one more amazing model: Grok 4.6. We benchmarked it as an orchestrator on our Wide-And-Deep-Research benchmark using the Perplexity Computer harness, and it neatly sits on the Pareto frontier of performance vs cost. Available to all Pro and Max users on Perplexity!
Aravind Srinivas@AravSrinivasAI 评分5151Grok 4.6 is now available in Perplexity and Perplexity Computer. On WANDR, it sits on the Pareto frontier of performance and efficiency, matching Fable 5 results at over 60% lower cost.
SpaceXAI@SpaceXAIAI 评分4949ICYMI refresh your model catalogs. Grok 4.6 is out 🛸 Built for long-running agent tasks, with stronger capabilities across coding, knowledge work, and visual tasks. $2/M input and $6/M output. Welcome Grok 4.6 to Pi.
Google 推出 Gemini 3.7 Flash，这是对 3.6 Flash 的算法改进而非新预训练模型，支持 1M-token 上下文窗口和最高 64K 输出 token。
Demis Hassabis@demishassabisAI 评分6161Gemini 3.7 Flash 为软件工程、Web 开发和知识工作带来重大升级。且 introductory 价格仅为原 3.6 Flash 的一半。祝构建愉快！
Gemini 3.7 Flash is here. It’s stronger for coding, knowledge work, and web development. 🧵
Google AI Developers@googleaidevsAI 评分6666
