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General

Multimodal Prompting Basics

Multimodal models require careful prompt design to balance modality context and instructions. This short guide provides patterns and tips.

Strategies

  • Explicit modality cues: Label inputs (e.g., “Image: ”) and specify what the model should consider.
  • Chunking: For long visual or audio inputs, provide short summaries or key frames instead of raw data.
  • Example-driven: Give one or two multimodal examples to show the desired alignment between image and text.

Output constraints

  • Ask for structured outputs (JSON with fields) when downstream systems require precise parsing.
  • Request confidence scores or explainability traces when available.

Evaluation

  • Use multimodal benchmarks and human reviewers experienced with both image and text modalities.