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Ant Group's Ling team open-sources 560B Ling-3.1-flash

AI summary

On October 15, Ant Group's Ling team released Ling-3.1-flash as open weights, publishing an FP8 checkpoint under the MIT license on Hugging Face and ModelScope. The model has about 560B total parameters and activates about 25B per token; Ant says it supports up to 1M context, though 36Kr notes the repository's max_position_embeddings is 262,144 and 1M is listed as a target, while Artificial Analysis measured an intelligence index of 41 and about 210 tokens per second. Ant says a mixed MXFP4/block-FP8 scheme cuts weights from about 534GB to 292GB and its Hopper test configuration from eight GPUs to four; 36Kr also notes vendor benchmark scores were run on the unreleased LingCode harness, and independent testing found flaws in long-chain agent tasks.

In-depth insight

According to the vendor, the open-weight release lets teams with server-class GPUs run a roughly 560B-parameter model on fewer cards, while 36Kr cautions that the four-GPU figure comes from a specific test configuration and is not a procurement checklist.

智东西 作者 |  杨京丽 编辑 |  李水青

智东西10月15日报道,近一周,硅谷AI大厂轮番放出新进展,都指向让AI接手真实工作。

10月12日,Meta发布Muse Wonder系列,包括Muse Wonder和Muse Wonder Full两个型号,重点面向个人与专业智能体任务。

10月9日,谷歌云也在Gemini at Work 2026大会上推出企业通用智能体Gemini Agent,能够自主规划任务、调用工具,在办公文档、邮件和开发环境中完成多步骤工作。昨天,谷歌开放其最新旗舰模型Gemini 4 Argon,重点面向编程、金融、法律、网络安全和科学等领域的复杂现实任务。

海外厂商加快布局个人与企业智能体的同时,中国厂商已经在围绕办公、金融、医疗等产业场景持续探索。模型能完成多少工作、交付质量如何,正在成为观察AI能力的重要切口。

#Ant Group#Bailing (Ant Group)#Ling-3.1-flash#Hugging Face#ModelScope#Artificial Analysis#LingCode

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