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Ant inclusionAI open-sourced Zooming without Zooming v2 (ZwZ2) on October 27, 2026 in a new GitHub repository, providing training and evaluation code for ZwZ2-4B/9B/27B. The models are based on Qwen3.5-4B/9B and Qwen3.6-27B, trained with GRPO reinforcement learning, using 20.4K multi-region VQA samples validated across models as training data. The models are trained on full images and require no scaling tools at inference time, and can be transferred to perception, spatial reasoning, long-context understanding, and multimodal agent tasks. The code, data synthesis, and evaluation pipeline are all released under the Apache 2.0 license. There are currently no subsequent developments.
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Ant inclusionAI Open-Sources ZwZ2-4B/9B/27B: A Fine-Grained Vision Model Without Zooming ToolsDevelopments
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The inclusionAI repository provides ZwZ2 training and evaluation code
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Oct 27
Ant inclusionAI: New GitHub RepositoryFirst-party
Ant inclusionAI Open-Sources ZwZ2-4B/9B/27B: A Fine-Grained Vision Model Without Zooming Tools
Ant inclusionAI has open-sourced Zooming without Zooming v2 (ZwZ2), trained on Qwen3.5-4B/9B and Qwen3.6-27B using GRPO reinforcement learning, with training data consisting of 20.4K multi-region VQA samples validated across models. The models are trained on full images and require no zooming tools at inference time, and can be transferred to perception, spatial reasoning, long-context understanding, and multimodal agent tasks. The code, data synthesis, and evaluation pipeline are all released under the Apache 2.0 license.