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Qwen2.5-VL image token budget impacts accuracy

The `max_pixels` configuration in Qwen2.5-VL models is a token budget in disguise, with default settings often leading to a significantly higher budget than recommended. This can result in suboptimal performance, especially for large targets within an image. The optimal token budget is dependent on the size of the specific object being sought, with smaller targets benefiting from larger budgets while larger targets perform best at lower token counts. AI

IMPACT Optimizing `max_pixels` can improve accuracy and efficiency for multimodal models, especially in applications involving object detection or grounding.

RANK_REASON The cluster discusses a technical finding about model configuration and its impact on performance, supported by experimental data. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

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Qwen2.5-VL image token budget impacts accuracy

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  1. dev.to — LLM tag TIER_1 English(EN) · Niv Dvir ·

    max_pixels is a token budget in disguise — and the right cap depends on the size of what you're looking for

    <p>Run the same image through the same Qwen2.5-VL model on different runtimes, and it can cost anywhere from <strong>8 to 16,384 visual tokens</strong> — a 2,000× spread — depending on which inference stack you picked. Nobody changed the model. They just disagree about one config…