Kimi K3 发布,2.8万亿参数,综合智能排名第三
Kimi K3 发布并已在网页端上线,参数量达2.8万亿,是目前公开的开源模型中规模最大的一个。它基于Kimi Delta Attention(KDA)混合线性注意力机制,并引入Attention Residuals结构,原生支持视觉理解,上下文窗口达100万token。
推荐理由:原文列出Kimi K3的参数规模、KDA与AttnRes架构改动及多项榜单跑分,可据此判断当前开源模型的能力位置。
月之暗面 Kimi 系列模型与产品动态:K 系列开源模型、长上下文技术与产品演进的追踪。
Kimi K3 发布并已在网页端上线,参数量达2.8万亿,是目前公开的开源模型中规模最大的一个。它基于Kimi Delta Attention(KDA)混合线性注意力机制,并引入Attention Residuals结构,原生支持视觉理解,上下文窗口达100万token。
推荐理由:原文列出Kimi K3的参数规模、KDA与AttnRes架构改动及多项榜单跑分,可据此判断当前开源模型的能力位置。
Kimi Code, our open-source coding agent, just got a major upgrade! 🔹One-line CLI install, zero setup, fast startup 🔹Drag in videos as coding context: reference-to-LUT, long-video-to-short, screen-recording-to-code, and more 🔹Plugins for stocks, financial reports, academic papers, with more coming 🔹Supports the ACP protocol, and works with JetBrains, Zed, and more 🔹Hooks for custom tools and workflows Try it with Kimi K2.6 👉 kimi.com/code Issues, plugin ideas, and PRs welcome! Community feedback helps shape what ships next.🚀
推荐理由:原文列出升级后的零配置安装、视频上下文与插件能力,读者可据此判断编码智能体的门槛变化。
Meet Kimi Work - a local AI agent on your desktop that does the work for you. 🔹Native agent swarm: Up to 300 AI agents running in parallel on your local machine. 🔹Browser use: Paired with WebBridge extension, your agent will navigate websites in your browser: search, scroll, click, type and complete tasks. 🔹Built for Finance: Native global market data tool call from Yahoo Finance and World Bank - no complex API setup required. 🔹Memory system: Kimi Desktop keeps a running diary of your preferences, past decisions, and context to know you better. Available for macOS (Apple Silicon) and Windows. 🔗Try it now: kimi.com/products/kimi-work Video
推荐理由:官方披露了本地代理规模、浏览器操作与财经数据原生调用等能力,读者可据此判断桌面端智能体的落地形态。
Cursor's new Composer 2.5 takes third on the Artificial Analysis Coding Agent Index and is ~10-60x lower cost than the higher-effort Opus 4.7 and GPT-5.5 variants above it. This release puts Composer among the leading coding agent models, something that wasn’t clear for past releases @cursor_ai has released Composer 2.5, the latest model in its Composer line. Composer 2.5 scored 62 on our Coding Agent Index, a 14 point gain over Composer 2 (48). This puts it in third place of our tested agents, behind only Claude Opus 4.7 (max) in Claude Code (66) and GPT-5.5 (xhigh reasoning) in Codex (65). These cost $4.10 and $4.82 per task respectively, ~10x the cost of Composer 2.5 Fast ($0.44) and ~60x the cost of Composer 2.5 standard ($0.07). Key results for Composer 2.5 in Cursor CLI: ➤ Cost-quality Pareto frontier: At $0.07 (standard) and $0.44 (Fast) per task, Composer 2.5 is cheaper than every other agent scoring above 60 on the Index. Medium-effort peers cost $1.24–$2.21 per task; higher-effort variants land 3-4 points above at $4.10–$4.82 ➤ Per-benchmark gains vs Composer 2: +35 points on SWE-Bench-Pro-Hard-AA (12% → 47%), +2 points on Terminal-Bench v2 (64% → 66%), and +3 points on SWE-Atlas-QnA (69% → 72%). At 47%, Composer 2.5's score on SWE-Bench-Pro-Hard-AA is comparable to Claude Opus 4.7 (max) in Claude Code ➤ Among the fastest coding agents: Composer 2.5 Fast runs at an average wall time of 6.7 minutes per task, the third-fastest agent on the Artificial Analysis Coding Agent Index, behind only Claude Opus 4.7 (medium) in Claude Code (5.8m) and GPT-5.5 (medium) in Cursor CLI (6.2m) ➤ Fast mode enables better responsiveness at 6x pricing: Fast runs 30% faster than standard Composer 2.5, but is ~6x the cost per task ($0.44 vs $0.07). Token pricing is 6x higher for Fast: $3.00/$15.00 vs $0.50/$2.50 per million input/output tokens Model details: ➤ Base model: Continued training on @Kimi_Moonshot's open weights Kimi K2.5 as with Composer 2, with Cursor reporting ~85% of total compute from its own additional training and reinforcement learning ➤ Pricing: $0.50/$2.50 per million input/output tokens for the standard variant; $3.00/$15.00 for the Fast variant (the default in Cursor) ➤ Available exclusively in Cursor: both Cursor IDE and Cursor CLI, an externally accessible API is not available Congratulations @cursor_ai and @mntruell on the impressive release!
推荐理由:推文用每任务成本对比 Composer 2.5 与两个更高分编码智能体,读者可据此权衡编码任务上的性能与花费。