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OpenRouter Tutorial: How to Send an Image to an LLM via API (Vision Guide)

OpenRouter:Announcements(RSS)T1
08:0008/14, 08:00 AMRSSRead the original ↗Export MD ↓

Score

79
Information gain7 ×0.3

给出了统一的多模态请求范式,并对比了常用传图方式,信息增量明显。

Content quality8 ×0.2

内容结构清晰,步骤明确,属于官方精编教程。

Practical value9 ×0.2

开发者可直接按指南实现图像传输与多模态 RAG,实用性极强。

Timeliness7 ×0.15

多模态 API 当前正热,该教程是近期发布的最新实践指引。

Source reliability9 ×0.15

来自 OpenRouter 官方博客,信息可信度高。

Base 79 × T1 Source weight ×1 = 79

Curation line 60Selected

Why selected

Targeted, detailed, and from an official source, this is a highly practical technical guide.

AI commentary

「The main value of this tutorial is that it unifies image transmission across different providers into one standard, saving developers from adaptating per model. Especially useful for those building agents or multimodal applications.」

Quick overview

OpenRouter's official guide explains how to send images to any vision-capable LLM using a unified request format. It covers base64 vs hosted URLs, model selection, multiple images, tokenization, and multimodal RAG, helping developers quickly adopt multimodal API calls.

  • Send images with a single request shape: a content array containing both text and image_url parts, shared by all vision models.
  • Compares base64 embedding vs hosted URLs, with recommendations on when to use each.
  • Covers multi-image input, tokenization, and building multimodal RAG pipelines.

Full text

Showing the source text; the full translation is being generated.

To get a model to read a screenshot, you need the right request body. This guide shows the content-array pattern that works across every vision-capable model we support, when to use base64 instead of a hosted URL, and how to build multimodal RAG on top of it.

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