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Ant Group's inclusionAI releases LBS-27B, a GUI-grounding VLM that transfers its zoom-in policy to general visual QA

Ant Group (inclusionAI)

Models / LLM official 2 src. ~1 min

LBS-27B appeared on Hugging Face on October 26 under Apache-2.0, built on Qwen3.8-27B and trained only on roughly 10K synthetic GUI-grounding cold-start examples plus 80 GRPO steps (batch 64, 8 rollouts per prompt) from Ant Group with Wuhan University of Technology and CAS. The agentic zoom-in policy reaches 81.15% overall action accuracy on ScreenSpot-Pro and 59.67% judge accuracy on PerceptionBench, and the authors show the same inspect-then-answer behaviour transferring to high-resolution general-domain VQA despite no general VQA training data.

Why it matters

Shows GUI-agent training data buys general visual perception, not just click coordinates.

Importance: 3/5

Open-weight model with a transferable-training result beyond its own benchmark.

Sources