Moonshot AI 发布新旗舰金K3.1 带有3T参数的 Pro 模型
Moonshot AI 今天推出金 K3.1 Pro，一个能够比Claude Opus 5.5和GPT-6 Astra更好的执行一些任务的大型语言模型。
LLM是中国人工智能公司发布于7月推出的后期训练，或升级版算法。 后者为Kimi K3，包含896个单个神经网络，有3兆参数。 它只在任何特定时间激活其中的16个神经网络，以尽量减少推论成本。
Moonshot AI也以其他方式优化其模型的硬件脚印。 Kim K3具有Kimi Delta Reference的特点，是一种自定义地执行一种名为Gated DeltaNet的保存记忆技术。 它减少了模型的注意力机制用来解释用户提示的RAM量。 该功能大概被结转到Kim K3.1 Pro.
新模式的称公司培训后工作流程消耗的处理功率大大高于过去完成的类似项目。 此外，它还运行在公司培训后堆栈的升级版上。 Moonshot AI增加了自动化质量检查，提高了基础基础设施的效率。
Kimi K3.1 Pro提供特别有竞争力的输出质量的一个领域是3D建模。 创建一个对象的3D模型有两种方法：工程师可以绘制它或者他们可以写一个代码片段，用数字来指定它的几何。 Kimi K3.1 号机车 Pro采取后一种做法。 LLM在名为BeningCAD的3D型号编码上得分92.7%，将其置入Astra和Claude Opus 5.5的4个百分点以内。
Kimi K3.1 号机车 Pro不仅可以生成静态的3D模型，还可以激活它们。 在一次测试中，Moonshot AI使用模型生成了人类运动的动画模拟。 另一个内部评价看到公司制作了多个3D电子游戏。 游戏很难让AI模型生成，因为它们包含大量代码，甚至单个bug都可以崩溃。
Pro在行业标准终端-Bench 4.0编码基准测试上得分65.7%，这使得它比Astra领先7%以上，但略低于Opus 5.5. 此外，它设法在OfficeQA Pro v2上超过了这两个模型。 这是衡量LLMs执行复杂财务分析任务能力的测试。
该模型在流行网络安全上的表现基准测试显著的跟随了Astra和Opus 5.5的得分。 Moonshot AI称，其工程师为了应对安全风险，故意从模型的训练后数据集中删除了网络安全相关信息。 公司计划为其未来的模型配备更先进的脆弱性分析功能。
Kimi K3.1 号机车 Pro通过Moonshot AI在发布上的付费云服务提供。 公司计划在11月4日前将模型的重量定为开源。
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Moonshot AI launches new flagship Kim K3.1 Pro model with 3T parameters
Moonshot AI today introduced Kim K3.1 Pro, a large language model that can perform some tasks better than Claude Opus 5.5 and GPT-6 Astra.
The LLM is a post-trained, or upgraded, version of an algorithm that the Chinese artificial intelligence company released in July. The latter model, Kimi K3, comprises 896 individual neural networks with 3 trillion parameters. It only activates 16 of those neural networks at any given time to minimize inference costs.
Moonshot AI also optimizes its models’ hardware footprint in other ways. Kim K3 features Kimi Delta Attention, a custom implementation of a memory-saving technology called Gated DeltaNet. It reduces the amount of RAM that the model’s attention mechanism uses to interpret user prompts. The feature was presumably carried over to Kim K3.1 Pro.
The company says the new model’s post-training workflow consumed significantly more processing power than similar projects it completed in the past. Additionally, it ran on an upgraded version of the company’s post-training stack. Moonshot AI added automated quality checks and boosted the underlying infrastructure’s efficiency.
One area where Kimi K3.1 Pro delivers particularly competitive output quality is 3D modeling. There are two ways to create a 3D model of an object: engineers can draw it or they can write a code snippet that specifies its geometry in numerical terms. Kimi K3.1 Pro takes the latter approach. The LLM scored 92.7% on a 3D model coding benchmark called BenchCAD, which put it within four percentage points of Astra and Claude Opus 5.5.
Kimi K3.1 Pro can not only generate static 3D models but also animate them. In one test, Moonshot AI used the model to generate an animated simulation of human motion. Another internal evaluation saw the company create multiple 3D video games. Games are difficult for AI models to generate because they contain a large amount of code and even a single bug can crash them.
Pro scored 65.7% on the industry standard Terminal-Bench 4.0 coding benchmark, which put it more than 7% ahead of Astra but slightly behind Opus 5.5. Furthermore, it managed to outperform both models on OfficeQA Pro v2. It’s a test that measures LLMs’ ability to perform complex financial analysis tasks.
The model’s performance on popular cybersecurity benchmarks significantly trails the scores of Astra and Opus 5.5. According to Moonshot AI, its engineers deliberately removed cybersecurity-related information from the model’s post-training dataset to address safety risks. The company plans to equip its future models with more advanced vulnerability analysis features.
Kimi K3.1 Pro is available via Moonshot AI’s paid cloud services on launch. The company plans to open-source the model’s weights by Nov. 4.
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