이미지: METAL LAB 생성
Summary
- Ant Group has released Ling 3.0 Flash, an open-weight model.
- With a total of 124B parameters, it scored 38 on the Artificial Analysis Intelligence Index.
- Artificial Analysis noted it marks a clear improvement over the previous generation and sits on the Pareto frontier for total parameters relative to intelligence.
- 모델명
- Ling 3.0 Flash
- 개발사
- 앤트그룹(Ant Group)
- 공개 형태
- 오픈웨이트(open weights)
- 총 파라미터
- 124B
- Artificial Analysis Intelligence Index
- 38점
- 평가 코멘트
- 지능 대비 총 파라미터 파레토 프론티어에 위치
- 출처·시점
- Artificial Analysis 게시물, 2026년 8월 7일
Ant Group unveils Ling 3.0 Flash
Ant Group has released Ling 3.0 Flash, an open-weight language model. Benchmark evaluator Artificial Analysis reported that the model has a total of 124B parameters and scored 38 on its composite metric, the Artificial Analysis Intelligence Index.
Improvement over the previous generation
Artificial Analysis assessed that Ling 3.0 showed a "marked improvement" over its predecessor. However, the specific score or parameter scale of the previous-generation model used for comparison was not disclosed in the post.
Position in terms of parameter efficiency
What stands out is not the absolute score but the parameter efficiency. Artificial Analysis explained that Ling 3.0 Flash sits on the Pareto frontier along the axis of Total Parameters relative to Intelligence. This means no other model achieves the same level of intelligence score with fewer total parameters. That said, details such as active parameter count, architecture, licensing terms, and training data were not confirmed in this announcement.
| Item | Confirmed value |
|---|---|
| Model | Ling 3.0 Flash |
| Total parameters | 124B |
| Intelligence Index | 38 |
| Weight release | Open-weight |
| Pareto frontier | Positioned on total parameters vs. intelligence |
An extension of Chinese open-weight competition
Ant Group, a fintech company that split off from the Alibaba group, has recently been releasing its own model lineup as open weights. The Ling series is reportedly part of that trend. This announcement can be seen as another example of ongoing competition within the open-weight camp along the axis of performance per parameter.
For more on recent trends in the open-weight model ecosystem, see METAL LAB's model category coverage.
What remains to be confirmed
The information disclosed so far is based on a single post from Artificial Analysis. Further confirmation is needed on detailed benchmark scores by category, context length, support for reasoning mode, and deployment channels.
