Vision Models

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Model overview

Vision models add image and video input to our text models for more complete and accurate understanding and reasoning. We currently offer the step series of vision models:

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Models

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Step 3.7 Flash

Recommended. Our flagship multimodal reasoning model with native image and video understanding — no extra vision MCP or auxiliary model required. It handles image / video Q&A and cross-modal analysis directly, with three reasoning effort levels (low / medium / high) and a 256K context window. See Step 3.7 Flash.

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Key terms

1. Image resolution: Pixel width/height. Higher resolution conveys more detail but increases cost, latency, and transfer time. Keep longest side under 4096px.
2. Image token count: Depends on resolution; images are adaptively scaled to an optimal size.
3. Supported formats: JPG/JPEG, PNG, static GIF, WebP.
4. URL formats:
   • http/https: Must be accessible from mainland China; load time affects first-token latency.
   • base64: Follow RFC2394, e.g. data:image/jpeg;base64,<base64_data_string>.
   • References: RFC2397, Data URL Format

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Usage limits

1. Images per request: The number of images per request is bounded by the model’s context length. For long conversations, summarize images first via a multimodal model, then pass the summaries as text.
2. Total image size: Keep combined uploads within 20MB.
3. Image metadata: Metadata (path, filename, size, original resolution, author, camera model, location, etc.) is stripped before inference to protect privacy; images are also resized to optimal dimensions.
4. Small text: Tiny fonts may reduce recognition quality.
5. Rotation/cropping: Incomplete or misaligned images can hurt recognition.
6. Counting: Numeric outputs are estimates, not exact counts.
7. Accuracy: Descriptions or captions may be imperfect; avoid relying on outputs where errors have serious consequences.

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Quickstart