Core Features of doubao 1.5 api

This api is specifically optimized for high-resolution OCR and bilingual visual reasoning. Unlike many general models, it maintains spatial accuracy in dense tables and complex diagrams, making it a specialized tool for document processing. Its multi-scale encoding preserves fine details without aggressive downscaling, ensuring that even small text in large technical blueprints remains legible and ready for structured extraction.

Yes. At GPTProto.com, we provide an OpenAI-compatible interface for the doubao 1.5 api. You can migrate existing workflows simply by updating your base URL and model name. The message structure for image URLs is identical, allowing your team to switch from expensive alternatives like GPT-4o to this cost-efficient model in minutes without rewriting core logic or changing your existing Python or Node.js integration patterns.

The pricing for the doubao 1.5 api is highly competitive. Input tokens are priced at $0.12 per 1M, while output tokens cost $0.48 per 1M. This makes it roughly 90% cheaper than GPT-4o for similar multimodal reasoning tasks. For high-volume enterprise workloads like e-commerce moderation or massive document digitizing, these savings significantly reduce the total cost of ownership while maintaining Pro-level performance.

Absolutely. The doubao 1.5 api features robust native JSON enforcement. By setting the response format to json_object, developers can ensure that the model returns structured data from visual inputs with high reliability. This is particularly useful for automated invoicing or identity document verification, where extracting specific fields into a machine-readable format is essential for downstream automation and database entry.

The doubao 1.5 api supports a context window of 32,768 tokens. This capacity allows it to handle multiple high-resolution images or lengthy text prompts in a single request. While not as large as specialized long-context models like Gemini, it is more than sufficient for detailed document analysis, UI/UX audits, and educational tutoring tasks that require a deep understanding of visual and textual context simultaneously.

Currently, the doubao 1.5 api does not support direct video file uploads. However, you can perform video analysis by extracting keyframes from your footage and sending them as individual image inputs. This method is highly effective for visual agents and monitoring applications. The model’s low-latency inference ensures that processing a sequence of frames remains fast enough for most near-real-time agentic vision use cases.