Ant Group publishes Ling-3.1-flash-1019, a 560B open model that lifts its index score to 44

What Ant Group released

Ant Group's inclusionAI organisation, which its Hugging Face profile calls the home of Ant Group's AGI initiative, published Ling-3.1-flash-1019 on 27 October 2026. The model card describes it as an upgraded version of Ling-3.1-flash with further post-training for reasoning and agentic work. A base checkpoint, Ling-3.1-flash-base, is also on Hugging Face for teams that want to run their own post-training.

The architecture is unchanged. It is a hybrid linear-attention mixture-of-experts model with 560 billion total and 25 billion active parameters. It has 63 KDA linear-attention layers and 9 gated MLA layers in a 7 to 1 ratio, 512 routed experts with 8 active plus one shared expert, and a 1M-token context window. The card also lists 4 dense layers, 64 attention heads and a vocabulary of 157,184 tokens. The weights are under the MIT licence, which allows commercial use.

What inclusionAI claims

The model card reports gains over the earlier Ling-3.1-flash checkpoint. inclusionAI says the AA-Briefcase score rose from about 1400 to 1524 Elo and AutomationBench-AA from 62% to 68%. On science tasks, it reports CritPt rising from 18% to 26% and SciCode from 54% to 57%. Overall, it says the model scores 44 on the Artificial Analysis Intelligence Index v4.3.2, up from 41.

These figures come from the developer. For context, Xiaomi reported 46.32 for its larger MiMo-V2.6-Pro on version 4.3 of the same index in September, as covered in the MiMo-V2.6 release story. The index versions differ, so the two numbers are not a direct comparison.

What changed for developers

The recommended engine is SGLang. A day-zero SGLang container adds Ling-3.1-flash support, multi-token prediction for speculative decoding and Hopper decode optimizations. The reference server runs on 8 H200 GPUs with tensor and expert parallelism of 8, or on 4 GB300 GPUs. A vLLM branch is also supported with dedicated tool-call and reasoning parsers. The card recommends temperature 1.0, top_p 0.95, top_k 20 and thinking mode on.

The card links an OpenRouter listing for hosted access, but it does not state a price. It also links a public training-content summary that lists the covered model versions and the scope of training content. inclusionAI says that document does not replace the licence or the technical documentation.

What to watch next

The model card does not link a separate blog post or technical report for the 1019 update, so independent runs of the Artificial Analysis index are the next check on its claims. The team says it is considering open-sourcing LingCode, its long-horizon coding harness built on the Pi agent. More open-weight releases are listed under Open Source AI.

Questions people ask

Is Ling-3.1-flash-1019 open source?

The weights are on Hugging Face under the MIT licence, which allows commercial use and modification.

What hardware does Ling-3.1-flash need?

The model card's SGLang recipe uses 8 H200 GPUs with tensor and expert parallelism, or 4 GB300 GPUs.

How is Ling-3.1-flash-1019 different from Ling-3.1-flash?

It keeps the 560B-parameter architecture and adds post-training. inclusionAI reports an Artificial Analysis Intelligence Index of 44 against 41 for the earlier checkpoint.

Sources

1. Ling-3.1-flash-1019 model card (inclusionAI, Ant Group (Hugging Face), 27 Oct 2026)
2. Ling-3.1-flash model card (inclusionAI, Ant Group (Hugging Face), 27 Oct 2026)
3. inclusionAI organisation profile (inclusionAI, Ant Group (Hugging Face), 27 Oct 2026)