Ant Ling (Bailing)

Ant Group's open-weight Ling and Ring model family, including trillion-parameter models released free on Hugging Face and ModelScope.

LLMs & Chat Open Source Open Source
Researched · Published · Reviewed
RECATOOLS Score
7.2 / 10
HQ
Hangzhou, China
Launched
Oct 2025
Developer
Ant Group

Overview

Ling (also called Bailing) is an open-weight large language model family from Ant Group's Inclusion AI team. It spans the Ling non-thinking series, including trillion-parameter models such as Ling-1T and the upgraded Ling-2.6-1T, and the Ring reasoning series. The models use a mixture-of-experts design that activates only a fraction of parameters per token for efficiency, and are released free under open weights on Hugging Face and ModelScope.

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Pricing

Pricing shown for reference only. These figures reflect RECATOOLS research as of 1 Sep 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.

Free
Free
Open weights, free to download and self-host on Hugging Face and ModelScope

What you can produce with Ant Ling (Bailing)

  • MIT-licensed trillion-parameter weights on Hugging Face and ModelScope, with no licensing friction to negotiate
  • Reasoning results from the Ring series: around 70.42% on AIME 2025, a #1 open-source finish on ArtifactsBench, roughly 81.6% on Arena-Hard V2, and an IMO silver-medal-equivalent showing billed as a first for an open system
  • An open non-reasoning model in Ling-1T, which DeepLearning.AI's The Batch highlighted as outperforming closed competitors
  • Hosted endpoints, which is how most people will actually reach these models
  • ⚠️ Not realistically self-hostable, which undercuts the open-weights point: a 1T mixture-of-experts flagship needs serious infrastructure even though MoE activates only a slice of parameters per token
  • Second-best rather than leading among reasoning models — strong but chasing the closed frontier — and Western adopters weigh the provenance and data-transparency questions that come with any Chinese-lab model
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RECATOOLS Verdict

What this is for: An open-weight model family covering fast-response Ling models (up to a trillion parameters) and Ring reasoning models, built on efficient mixture-of-experts architectures.

Who this is for: Developers and researchers who want to self-host large open-weight Chinese-origin models, including trillion-parameter flagships, without licensing fees.

Availability: Free, open weights on Hugging Face and ModelScope. Developed by Ant Group's Inclusion AI (Bailing) team.

Independent AI-assisted assessment by RECATOOLS.

What people say

Ant Group's Inclusion AI team earned strong open-source credibility with the Ling and Ring families, and the benchmark reception has been unusually warm for a Chinese-origin release. DeepLearning.AI's The Batch highlighted Ling-1T as an open non-reasoning model that outperforms closed competitors, while the Ring reasoning series posted headline results: around 70.42% on AIME 2025, a #1 open-source finish on ArtifactsBench, roughly 81.6% on Arena-Hard V2 (approaching GPT-5-Thinking), and an IMO silver-medal-equivalent showing billed as a first for an open system. The MIT license on the trillion-parameter weights, published to Hugging Face and ModelScope, is a genuine draw for teams that want no licensing friction.

The obvious limitation is practicality: these are trillion-parameter mixture-of-experts models, and while MoE activates only a slice of parameters per token, self-hosting a 1T flagship is out of reach for almost everyone without serious infrastructure, pushing most users toward hosted endpoints and undercutting the open-weights advantage. Benchmark placement is also often second-best among reasoning models, i.e. strong but chasing the closed frontier rather than leading it, and some Western adopters weigh provenance and data-transparency questions that come with any Chinese-lab model. The signal is credible and rising, but the models reward well-resourced teams far more than hobbyists.

Summary of public user & expert reviews, compiled by RECATOOLS.

Frequently asked questions

Free on Hugging Face and ModelScope, published by Ant Group's Inclusion AI (Bailing) team.
Ling is the fast-response, non-thinking series, including trillion-parameter models such as Ling-1T and the upgraded Ling-2.6-1T. Ring is the reasoning series.
No. This is a weights release — self-hosting is the deployment path, which is also why there are no licensing fees.

About this listing

Researched on
Published on
Last reviewed

This entry was compiled from publicly available data including Ant Ling (Bailing)'s official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Ant Ling (Bailing) unless explicitly stated.

Data accuracy

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