# Ant Ling — Ling 3.0 Flash

> AI lab announcements, news reports and podcasts.

forck.live follows what companies announce about their own products. Press may
corroborate an official story; it never leads and never appears as an item of its
own. A missing date stays missing. A title is the publisher's words — where a
company does not publish in English, an English rendering is listed separately
as `Title in English` and named as this site's translation, never as theirs.

This file is the record of one model version: what the model registry states
about it, Ant Ling's launch post, the first-party posts this record
holds about it, the outlets that reported on those posts, and other companies'
announcements that it runs on their platforms. A model ranks nothing here and
nothing is composed: each date names whose it is, and a field nothing states is
`not stated` rather than missing.

- This model's page: https://forck.live/models/ling-3-0-flash
- Ant Ling's page: https://forck.live/company/ant-ling
- Every model: https://forck.live/models
- Catalogue: https://forck.live/llms.txt

## Model

- Name: Ling 3.0 Flash
- Company: Ant Ling (ant-ling.com)
- Launch post: Ling-3.0-flash: More Useful Work per Token — https://forck.live/items/22330-ling-3-0-flash-more-useful-work-per-token
- Announced: 2026-07-24
- Launch source: https://developer.ant-ling.com/en/blogs/ling-3.0-flash-release
- Launch chosen by: the earliest dated release post naming it
- Released (per models.dev): not stated
- Listed (per OpenRouter): 2026-07-23
- Open weights: not stated
- Posts about it: 2
- Outlets named under its posts: 0
- Variant: Ling 3.0 Flash VL — https://forck.live/models/ling-3-0-flash-vl
- OpenRouter id: inclusionai/ling-3.0-flash — https://openrouter.ai/inclusionai/ling-3.0-flash
- Context window: Native 256K context, extendable to 1M — from https://forck.live/items/22330-ling-3-0-flash-more-useful-work-per-token

## Posts about it

_Ant Ling's own posts whose title names Ling 3.0 Flash, and its launch post, in the record's order: dated newest first, undated last. The record reads the newest 50 first-party posts mentioning the model, every company's together, so a model mentioned more often than that lists the newest of them._

Every entry is one first-party announcement, and carries the same eight fields
in this order before any others:

    Company · Announced · Category · Coverage · Announcement · Group · Source · Record

`Source` is the company's own page the announcement was traced to and `Record`
is this site's page for it. Both are safe to cite.

`Coverage` is a number of outlets, or `not counted` — which means this record
reached no count of its own, never that nobody wrote about it.

`Category` is this tracker's own analysis, and is authoritative wherever it is
stated. `not stated` means either that nothing has analysed the post yet or
that the analysis placed it outside this taxonomy; neither is a verdict about
the announcement.

`Announcement` is whether the post is news of something the company did, rather
than a how-to, a customer story, a changelog listing or a staffing note.

`Group` is which of this record's groups the entry falls in, carried on the
entry itself so it holds where the groups are headings and where they are not.
One of: `models`, `covered`, `announcements`, `routine`.

Anything after `Record` is held detail that only some announcements carry.

### Ant Ling — Ling-3.0-flash for AI Agents: Open-Weight Intelligence with Lower Token Costs

- Company: Ant Ling (ant-ling.com)
- Announced: 2026-09-18
- Category: not stated
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://developer.ant-ling.com/en/blogs/lower-token-costs
- Record: https://forck.live/items/22329-ling-3-0-flash-for-ai-agents-open-weight-intelligence-with-lower-token-costs
- Subject: Ling / Ring / Ming

Note: This is a guest blog prepared by the amazing team at Atomic Chat. Agent workloads make latency and token costs especially noticeable because a single task can require dozens of inference calls, and those costs compound quickly.

### Ant Ling — Ling-3.0-flash: More Useful Work per Token

- Company: Ant Ling (ant-ling.com)
- Announced: 2026-07-24
- Category: new-model
- Coverage: not counted
- Announcement: yes
- Group: models
- Source: https://developer.ant-ling.com/en/blogs/ling-3.0-flash-release
- Record: https://forck.live/items/22330-ling-3-0-flash-more-useful-work-per-token
- Subject: Ling / Ring / Ming

Ant Ling released Ling-3.0-flash, a 124B-parameter Mixture-of-Experts model with 5.1B active parameters per token, designed for token efficiency in agent workflows. The model features native 256K context extendable to 1M, hybrid linear attention (KDA + MLA), and agent-focused training across over 10,000 environments. It achieves a 25.3% pass rate on MiniAppBench, competitive with open-source models roughly twice its size.

## Who reported on it

_This record names no outlet that reported on these posts._

---

Record: https://forck.live/models/ling-3-0-flash
Catalogue: https://forck.live/llms.txt
Current issue: https://forck.live/feed.md
