Qwen2.5-VL
A multimodal vision-language model in Alibaba's Tongyi Qianwen series, supporting tasks such as image and video understanding and document parsing.
Timeline (last 90 days)
In the owl target experiment, the student model trained on data selected by a schemer that prefers owls exhibits a higher target-to-alternative likelihood ratio in image-free readout, and this directional shift appears on LLaVA-1.5, Qwen2.5-VL, Qwen3-VL, and Gemma 4.
Open-weight VLM refers to vision-language models whose parameters can be publicly downloaded and deployed to run locally, such as the Qwen2.5-VL and InternVL series.
HyperCLOVAX Vision V2 is a vision-language model developed by NAVER that uses the HyperClovaX language model backbone paired with a Qwen2.5-VL visual encoder, supports text, image, and video input, and implements chain-of-thought reasoning via thinking tokens.
The Qwen2.5-VL series released by Alibaba's Tongyi Qianwen team includes a 7B version that performs excellently on tasks such as image understanding, document parsing, and OCR.
The Qwen2.5-VL series performs especially well on the DocVQA and OCRBench benchmarks.
For M4 Pro 64GB users pursuing fast visual response, Qwen2.5-VL-7B or Llama 3.2 Vision 11B is recommended.
All Facts (6)
In the owl target experiment, the student model trained on data selected by a schemer that prefers owls exhibits a higher target-to-alternative likelihood ratio in image-free readout, and this directional shift appears on LLaVA-1.5, Qwen2.5-VL, Qwen3-VL, and Gemma 4.
50%UnverifiedOpen-weight VLM refers to vision-language models whose parameters can be publicly downloaded and deployed to run locally, such as the Qwen2.5-VL and InternVL series.
50%UnverifiedHyperCLOVAX Vision V2 is a vision-language model developed by NAVER that uses the HyperClovaX language model backbone paired with a Qwen2.5-VL visual encoder, supports text, image, and video input, and implements chain-of-thought reasoning via thinking tokens.
50%UnverifiedThe Qwen2.5-VL series released by Alibaba's Tongyi Qianwen team includes a 7B version that performs excellently on tasks such as image understanding, document parsing, and OCR.
50%UnverifiedThe Qwen2.5-VL series performs especially well on the DocVQA and OCRBench benchmarks.
50%UnverifiedFor M4 Pro 64GB users pursuing fast visual response, Qwen2.5-VL-7B or Llama 3.2 Vision 11B is recommended.
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