Moonshot AI Releases Kimi K3.1 Pro: A 3T-Class Open-Weight Model Strengthening Coding, 3D and Finance Agents
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Moonshot AI has released Kimi K3.1 Pro, calling it the strongest 3T-class open-weight model, featuring a 1M-token context and multimodal capabilities. It simultaneously launched a Highspeed version that is about 2–3× faster, with full weights planned to be open-sourced before 2026-11-04. The model scores 65.7% on Terminal-Bench 4.0, above GPT-6 Astra's 58.2% and slightly below Claude Opus 5.5's 66.4%; it scores 92.7% on BenchCAD with tools and 64.4% on OfficeQA Pro v2. The open-weight version removes cyber-related data from both mid-training and RL, and its xdev-bench-hard score drops from 90.5% to 81.0%.
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The original text lists K3.1 Pro's specific scores on coding, 3D and finance benchmarks along with the comparison models, which can be used to gauge the gap between open-weight models and closed-source frontier models.
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View original postIntroducing Kimi K3.1 Pro: our most capable 3T-class open-weight model. 🔹 1M-token context, 2.8T total / 104B active params (MoE), Multimodal. 🔹 Full-project coding: games in Unreal, Unity & Godot. 🔹 Excels at parametric 3D modeling in Blender & CAD. 🔹 More reliable at finance work: Accurate modeling with hallucination down by 65%. 🔹 Matching the strongest proprietary models across coding, agentic and knowledge benchmarks. Kimi K3.1 Pro and K3.1 Pro Highspeed (2–3× faster) are now live on https://t.co/85jA71X9gw, Kimi Work, Kimi Code, and the Kimi API. Open weights by Nov 4, 2026. 🔗 API: https://t.co/XCrgjXAqMw 🔗 Tech blog: https://t.co/5iPP0MBej6
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Introducing Kimi K3.1 Pro: our most capable 3T-class open-weight model. 🔹 1M-token context, 2.8T total / 104B active params (MoE), Multimodal. 🔹 Full-project coding: games in Unreal, Unity & Godot. 🔹 Excels at parametric 3D modeling in Blender & CAD. 🔹 More reliable at finance work: Accurate modeling with hallucination down by 65%. 🔹 Matching the strongest proprietary models across coding, agentic and knowledge benchmarks. Kimi K3.1 Pro and K3.1 Pro Highspeed (2–3× faster) are now live on https://t.co/85jA71X9gw, Kimi Work, Kimi Code, and the Kimi API. Open weights by Nov 4, 2026. 🔗 API: https://t.co/XCrgjXAqMw 🔗 Tech blog: https://t.co/5iPP0MBej6
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月之暗面开源级 3T 模型升级：Kimi K3.1 Pro 强化编程、3D 与金融 Agent
K3.1 Pro 是 K3 的大规模后训练版，号称目前最强的 3T 级开源权重模型（1M token 上下文）；在 Terminal-Bench 4.0 等 Agent 编程榜上接近 Claude Opus 5.5，并同步放出 2–3× 速度的 Highspeed 版，完整权重计划 2026-11-04 前开源。 https://t.co/EgPeZypeXB
模型定位 · Kimi K3.1 Pro：K3.1 系列首发，基于 Kimi K3 加大后训练算力，强调跨数百下游域的联合 RL。 · Kimi K3.1 Pro Highspeed：同能力线，交互速度约 2–3×。 · 今日起可用：https://t.co/V7wNUt9vLy、Kimi Work、Kimi Code、Kimi API；完整权重 11 月 4 日前发布。企业端默认关闭，需管理员开启。
核心技术叙事 团队优化了整条 RL 栈（框架、长上下文推理、训练效率、沙箱、rollout 调度、环境质检平台），使每单位 RL 算力回报更稳定，从而在各域「一致提升」。
编程与长程 Agent · Terminal-Bench 4.0：65.7%（用 Claude-Code harness），高于 GPT-6 Astra 58.2%，略低于 Claude Opus 5.5 的 66.4%。 · Kimi Code Bench 3.0 Long-horizon（内部）：61.2%，高于 K3 的 55.95%。 · 覆盖修 bug 到整项目构建；Unity / Unreal / Godot + 搜索 + 3D 生成；前端与 Three.js 观感更好。 · 内部案例：基于含 296 骨骼件、402 肌肉的 human-atlas，做人体行走动力学模拟；167 次任务、420 次独立评审后，连续行走约 11.2 秒；奖励塑形无效时，用开环探针查出并修正肩部肌力矩臂 36 处错误后再训练。
3D 与设计 · BenchCAD（多视图渲染 → CAD 代码）：带工具 92.7%，接近 Opus 5.5（96.2%）与 GPT-6 Astra（95.9%）。 · 强项：参数化建模（机械件、建筑、可配置产品、定制家具）；无需 MCP 也可写/跑 Blender、CAD 脚本。 · 产品侧：3D Make 已上线 https://t.co/jKNycbUAAF 与 App，可在线预览编辑、导出打印或视频/Live Photo。
金融 · OfficeQA Pro v2：64.4，文称 SOTA（复杂财报检索、跨文档校验、多步数值推理）。 · 相对 K3：Financial Modeling +7.2；Financial Research +11.6；Business Operation 约 4.2×。 · 幻觉：Kimi Hallu Bench Hard 上 claim 级幻觉率 23.4% → 8.3%；含至少一处事实错误的回复比例约为前代的 42.4%（压力测试，不代表日常整体错误率）。
网络安全与开源原则（篇幅最长的一节） · 观察到：后训练放大后，漏洞研究能力随算力上升；溯源到 mid-training 语料与 RL 环境里的 cyber 相关内容。 · 开源权重版主动从 mid-training 与 RL 两侧剔除 cyber 相关数据，保留通用编程任务。 · xdev-bench-hard（内核、Node、JSC、Exim、VirGL 等近期漏洞复现，需写利用拿 flag）：未做风险削减 checkpoint pass@3 = 90.5%；最终 K3.1 Pro = 81.0%。 · 立场：不把「进攻性 cyber 绝对前沿」放进开源权重；同时认为逐步扩散双用途能力（尤其防御与自审代码）长期更安全。能力仍落后于已公开至少三个月的头部闭源模型。