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nwaughachukwuma 
posted an update Jul 20
Post
739
# 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
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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