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nwaughachukwuma 
posted an update Aug 19
Post
3584
# VLM Run Gateway: Run GLM-OCR, DeepSeek-OCR-2, and Dots.mocr with an OpenAI Compatible API

Open-weight OCR VLMs have advanced significantly over the past year, yet most teams still rely on frontier VLMs for document parsing because researching, evaluating, and deploying the right models remains challenging.

So we built VLM Run Gateway: one OpenAI-compatible endpoint for open-weight OCR and VLM models.

If you’re using frontier VLMs primarily for OCR/document parsing, open-weight OCR models can be dramatically cheaper and often very accurate. With a one-line change, you can switch between open-weight OCR VLMs (DeepSeek OCR 2, GLM-OCR, dots.mocr, Paddle OCR VL, PP-OCRv6, etc.) and process 100K+ pages for under $60.

Try it out quickly via the 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:
client = OpenAI(
    base_url="https://gateway.vlm.run/v1/openai",
    api_key="<VLMRUN_API_KEY>",
)

response = client.chat.completions.create(
    model="rednote-hilab/dots.mocr",
    messages=[{
      "role": "user",
		  "content": [{
            "type": "document_url",
            "document_url": {"url": "https://.../invoice.pdf"},
      }],
    }],
    extra_body={"document_dpi": 72},
)


Docs: https://docs.vlm.run/gateway

Catalog: https://docs.vlm.run/gateway/models

MCP: https://docs.vlm.run/gateway/mcp-server

Colab Quickstart: https://colab.research.google.com/drive/1RkuVIyuc5Po-UlcSlFyJCam5tjCm9IHM?usp=sharing

Read the full post here: https://huggingface.co/blog/vlm-run/intro-to-vlmrun-gateway
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