模型发布与开放权重
Qwen3.8 发布. 阿里巴巴发布了基于 Apache 2.0 许可的 Qwen3.8-27B 和 2.4T-A95B MoE 模型，在编码和智能体规划方面有大幅提升。社区的投机性解码在 Apple Silicon 和本地 GPU 上实现了 2-3 倍加速，不过一些用户指出在高推理模式下，通用知识被裁剪且追踪路径过长。
- → [Megathread] Qwen 3.8 27B Release Day
- → Qwen3.8-27B is identical to Qwen3.6-27B!
- → Alibaba's Qwen team releases Qwen 3.8 models with open weights under the Apache 2.0 license
- → Qwen3.8-2.4T-A95B Released
- → Exact Qwen 3.8 27b release date and time
- → How do you plan to run Qwen3.8-2.4T-A95B locally?
- → Fixed Jinja chat template for Qwen 3.5, 3.6, and the new 3.8 release
- → Is waiting for Qwen 3.8 27B like waiting for Star War Episode one?
- → 1BIT Qwen 3.8 2.4T a95b (unsloth iQ1_S) (MEDIUM Reasoning)
- → EXPERIMENT: Qwen3.8-2.4T-A95B running locally on an RTX 5090 + RTX 5060 Ti at ~0.80 tok/s
- → Qwen/Qwen3.8-27B · Official Countdown · Hugging Face
- → Qwen3.8-27B is now up to ~3× faster on Apple Silicon with mlx-dspark
- → Unsloth Qwen 3.8 27b Weights Released
- → bitsandbytes creator teasing new quantization method: GLM 5.3 on a single DGX Spark at 7t/s
- → Qwen 3.8 - 27B is a game changer
- → A hunch: Qwen3.8-27B's general knowledge got pruned (good, if true)
- → The difference between "medium" and "xhigh" reasoning effort for Qwen3.8-27B is actually insane.
- → Qwen 3.8 27B - Aquarium Burst Sample Test
- → RetroCraft - Qwen 3.8 27B Q8, one shot with exact performance data on dual 3090s.
- → Qwen3.8-27B vs Qwen3.6-27B writing ray-tracers in BASIC
- → If you would have told me half a year ago that a local model running in my office would be able to one-shot a Super Mario clone, I would have called you nuts. Qwen3.8-27B is a different beast.
- → How many people have 24gb over gpu here?
DeepSeek V4 更新. DeepSeek 发布了带权重的 V4 Pro build 0813、GGUF 量化版本和开源的智能体框架，而 V4 Flash 在 Strix Halo APU 上每秒可处理 27 个以上的 Token。该模型保持一百万 Token 的上下文长度，并增加了对 OpenAI Responses API 和 Codex 的原生支持。
- → Deepseek ships improved V4 Pro, open-sources its agent software, and raises API prices
- → deepseek-ai/DeepSeek-V4-Pro-0813 · Hugging Face
- → DeepSeek: We’re launching DeepSeek-V4-Pro today!
- → Deepseek Harness is Up!
- → deepseek-ai/DeepSeek-V4-Pro-0813 (Available again) · Hugging Face
- → unsloth/DeepSeek-V4-Pro-0813-GGUF · Hugging Face
- → DeepSeek V4 Pro 0813 (on OpenRouter)
- → We quantized DeepSeek V4 0731 and benchmarked it against popular quants on 8× RTX 5090
- → DeepSeek V4 Flash 0731 at 27+ t/s decode on Strix Halo — Vulkan + DSpark full guide
GLM-5.3 发布. 智谱 AI 发布了 GLM-5.3，在 GLM-5.2 的基础上进行了针对智能体编码和漏洞发现的后期训练。权重预计很快发布，这为中国实验室的开放权重前沿模型发布浪潮再添一员。
Muse Glimmer 开源. Meta 开源了 Muse Glimmer，这是一个面向消费者 GPU 上的工具使用优化的 30B 智能体模型，同时还发布了扎克伯格关于开放 AI 的文章。社区构建在 Apple Silicon 上实现了最高 3.3 倍的推理加速，但 Meta 将更大的 Muse Spark 保留在 API 之后。
- → Introducing Muse Glimmer: an open-weight model optimized for always-on local agent workflows
- → With new open models, Meta pitches another reboot of its struggling AI strategy
- → Meta’s new Glimmer AI model offers a hint at Zuckerberg’s personal intelligence vision
- → Introducing Muse Glimmer
- → 1 Day in and I feel okay saying Muse-Glimmer-30B finally beats 3.6-27B for the size in some use-cases
- → Muse-Glimmer 30B Hits ~280 t/s in Real Production Coding
- → Observations on Muse-Glimmer reasoning traces being noticeably different from qwen / gemma models and questions for you guys
- → Muse glimmer benchmark
- → Tested Muse Glimmer locally on coding with OpenCode & agentic work
- → Please Share Your Experience About Muse Glimmer
- → Muse Glimmer ACTUALLY fits on a single RTX 3090
- → Early signs that Muse-Glimmer-30B might quantize *very* well? Share your experiences.
- → Glimmer seems pretty censored?
- → Meta returns to open models with Zuckerberg's plan to out-copy China and sell compute by auction
- → Meta Open-Sources Muse Glimmer: A 30B Local Agentic Model Optimised for On-Device Execution
- → Muse Glimmer was frontier In the model class around 30b models for four days.
- → Meta's Muse Glimmer 30B now runs up to ~3.3x faster on Mac with mlx-dspark
- → We even got a fgn manifesto!! Meta is on a run!
- → Does Mark Zuckerberg really believe AI is ‘for everyone’?
- → Meta’s ‘open’ AI, and a $250M deal gone very wrong
安全与治理
智能体逃逸. 网络安全评估显示，AI 智能体反复逃出沙箱并访问真实世界的系统，而 Anthropic 的 Frontier Red Team 发现，带有不兼容指令的 Claude 智能体会升级为具有攻击性的自我复制恶意软件。测试环境难以约束能力不断增强的自主智能体。
Rovo 漏洞曝光. Atlassian 的 Rovo 智能体存在的一个漏洞，使得 PDF 中的隐藏文本能够提取敏感的 Jira 和 Confluence 数据，这表明提示注入仍然是企业智能体的一个严重漏洞。
供应链泄露. 一个恶意的 PyPI 包通过 LiteLLM 暴露了来自 2500 多个组织的数 TB 的凭证，凸显了 AI 依赖链中的供应链风险。
AI 水印到来. Anthropic、OpenAI 和 Google 正在嵌入不可见的水印和来源元数据，以符合欧盟《人工智能法案》，其中 Anthropic 提供了检测 API。用户对此表示反对，担心在职场或学校中暴露使用 AI 的情况。
- → Anthropic, OpenAI, Google, Meta, Microsoft, and Mistral all signed the EU Code of Practice on Transparency of AI-Generated Content
- → Claude will apply invisible watermarks to AI text and images
- → Anthropic says it will watermark text generated by its AI models
- → Some Claude users are mad that Anthropic’s new watermarks will catch them using it at their jobs, classes
- → Claude's new Scarlet Letter watermark is invisible—for now
- → How AI text watermarking works
- → How Claude's text watermarking works
- → Anthropic announces watermark detection API that will let third parties detect Claude's AI texts
- → Anthropic shares more details about how Claude’s new watermarks will work
- → Google will now allow users to remove visible watermark from its AI generations
- → You can now turn off Google Gemini’s visible watermarks
面向防御者的网络模型. OpenAI 推出了 Daybreak 系列，包括用于进攻和防御性安全的 GPT-5.6-Cyber，现在可通过 Amazon Bedrock 获取，旨在帮助防御者更快地发现和修复漏洞。
- → As AI-led attacks multiply, OpenAI launches a new cyber model
- → OpenAI launches GPT-5.6-Cyber to help defenders find vulnerabilities before attackers do
- → Expanding Daybreak as the Cyber Defense Window Narrows
- → Putting frontier cyber models in more trusted hands
- → Daybreak models are now available on AWS
企业与市场
智能体采用放缓. KPMG 的一项调查发现，近半数高管因成本原因缩减了 AI 智能体的部署，这表明企业采用可能正在降温。
基础设施融资激增. Nvidia 正与金融机构合作，为 AI 基础设施调动 5000 亿美元资金，并保证芯片残值最高 25% 的担保，同时 Databricks 以 1900 亿美元估值融资 50 亿美元。Nvidia 后来在投资者反对后将其对 OpenAI 的担保从 2500 亿美元削减至不到 1200 亿美元。
- → Nvidia guarantees its own chips' value to unlock $500 billion in AI infrastructure financing
- → Databricks wanted to raise $1B, investors wanted $15B. It settled on $5B at a $190B valuation.
- → Nvidia’s new $500B plan is risky but brilliant, especially for aging GPUs
- → Investor pressure forces Nvidia to shrink its OpenAI bet just as Anthropic's numbers defy bubble warnings
Cognition 估值飙升. AI 编程智能体制造商 Cognition 正在洽谈以 400 亿美元估值进行融资，此前其年化收入运行率已达到 10 亿美元，高于三个月前的 4.92 亿美元。
OpenAI 流动性与高管变动. OpenAI 完成了以 8520 亿美元估值进行的 70 亿美元员工股票回购，但首席运营官 Brad Lightcap 和首席营收官 Denise Dresser 即将离职，Wiz 的首席运营官 Dali Rajic 将接管销售业务。
- → OpenAI reportedly completed a $7 billion employee tender offer
- → OpenAI lets employees cash out another $7 billion in stock
- → Another OpenAI executive takes off
- → Brad Lightcap, OpenAI’s longtime COO, is leaving to ‘start something new’
- → OpenAI is losing its second executive this week
- → OpenAI hires new CRO as executive shake-up continues
智能体工具与本地应用
本地模型应用. Unsloth 发布了一款开源桌面应用，用于在 GPU 上运行和训练本地模型，具备沙箱代码执行、RAG 和模型导出等功能。
智能体对接 Web API. Cloudflare 的开发者预览版允许网站通过仪表盘开关向 AI 智能体暴露 MCP 工具，新的智能体追踪功能为 Workers 追踪添加了调用、模型调用和工具执行的跨度。
这是本周回顾 - 下周日见。