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Lona Kiragu
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VLM Run Gateway: Run GLM-OCR, DeepSeek-OCR-2, dots.mocr with an OpenAI Compatible API
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# One API for Every Visual & OCR Models. The VLM Run Gateway is a fully compatible API for OpenAI chat completions for visual intelligence. If you’re building document extraction or visual understanding, the Gateway exposes OCR, VQA, and detection behind a single interface you already know. Read the docs: https://docs.vlm.run/gateway/introduction. We actively support the following recent OCR and VQA models, which you can try today at no cost: * zai-org/glm-ocr * rednote-hilab/dots.mocr * paddleocr/pp-ocrv6 * qwen/qwen3.5-0.8b ## Quickstart ### CLI ```bash uvx vlmrun gw models uvx vlmrun config set --api-key '<VLMRUN_API_KEY>' # anon-user, rate-limited uvx vlmrun gw chat <doc>.pdf -m zai-org/glm-ocr uvx vlmrun gw chat <doc>.pdf -m zai-org/glm-ocr --json-mode uvx vlmrun gw chat <doc>.pdf -m deepseek-ai/deepseek-ocr-2 uvx vlmrun gw chat <doc>.pdf -m rednote-hilab/dots.mocr uvx vlmrun gw chat <doc>.pdf -m paddleocr/pp-ocrv6 ``` ### OpenAI SDK ``` from openai import OpenAI client = OpenAI( base_url="https://gateway.vlm.run/v1/openai", api_key="<VLMRUN_API_KEY>", ) response = client.chat.completions.create( model="zai-org/glm-ocr", messages=[ { "role": "user", "content": [ { "type": "document_url", "document_url": { "url": "https://storage.googleapis.com/vlm-data-public-prod/hub/examples/finance.sec-filings/tsla-8k.pdf" }, }, ], } ], extra_body={"method": "markdown", "document_dpi": 150}, ) print(response.choices[0].message.content) ``` ## Auth and limits Anonymous auth is enabled, so you can omit the authorization header entirely, or send Bearer "" or Bearer vlmrun. Rate limits are 60 req/min and 1000 req/hr.
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