Models / Qwen
Qwen2.5-VL 7B Instruct
Strengths
Vision-language specialist at 7B. Beats Llama 3.2-Vision 11B on MMMU (58.6), MathVista (68.2), DocVQA (95.7). Apache 2.0. Variable resolution and aspect ratio support, video frames.
Weaknesses
Older than the Gemma 4 multimodal variants. 32K native context (extendable via YaRN). CPU inference is slow because vision processing is RAM-hungry.
Qwen2.5-VL 7B is the open-weight vision-language specialist most teams reach for at this size. Where Gemma 4 E4B and 31B are generalists with multimodal as a feature, Qwen2.5-VL was trained from the ground up around image and video understanding, and it shows on document/chart/diagram benchmarks.
The 7B fits comfortably on a 16GB GPU, supports variable image resolution, and reads structured documents (DocVQA 95.7) better than most generalist VLMs at the same size.
When to pick it
- Document, screenshot, or chart understanding is the headline task.
- You need video-frame analysis without paying for a 30B+ generalist.
- Apache 2.0 with no commercial caveats.
When to skip it
- You want one generalist that "also does vision." Gemma 4 E4B/31B fits better.
- You need >32K context routinely (use YaRN for long context, or pick a different VLM).