zai-org/GLM-OCR

OCRzai-org/GLM-OCR

Document and image OCR with multimodal chat messages.

Send OpenAI-style multimodal user content (image + instructions) to extract text from scans, PDF renders, and screenshots.

Best for

PDF OCR

Mode

OCR

Reasoning

No reasoning mode

Tools / coding

—

Throughput

1.96 pages PDF/sec

At a glance

  • Modalities: Image · Multimodal
  • Vision + OCR style prompts
  • Great for ingestion pipelines
  • Resize images for latency

Integration examples

These snippets are adapted for this model's API mode: OCR. The model field is set to zai-org/GLM-OCR. If your deployment uses an alias, mirror that value when you paste into your app. For general concepts, see the main documentation hub.

Deploy a model →

Keys and base URL

Replace YOUR_API_KEY with the key from Models after you sign in. This page's snippets use http://app.ai-grid.io:4000 when you are signed in (see DOCS_AUTHENTICATED_API_BASE_URL). Otherwise they keep the placeholder host for sovereign-safe documentation.

For PDFs, render each page to PNG/JPEG first, then send each page as image input. Keep files small enough for browser or gateway limits.

Extract text from an image

OCR

/v1/chat/completions
OCR · HTTP
IMAGE_DATA="$(base64 -w 0 document-page.png)"

curl http://app.ai-grid.io:4000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "zai-org/GLM-OCR",
    "messages": [
      {
        "role": "user",
        "content": [
          { "type": "text", "text": "Extract all readable text. Preserve tables and line breaks." },
          {
            "type": "image_url",
            "image_url": {
              "url": "data:image/png;base64,'"$IMAGE_DATA"'"
            }
          }
        ]
      }
    ],
    "max_tokens": 1200
  }'

Other models

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Throughput

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View documentation

Qwen · Text LLM

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Reasoning

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Throughput

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  • Tune system prompts for chain-of-thought depth
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Google · Text LLM

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High-volume chat

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Fast 31B text generation for assistants and RAG answers.

Throughput

580 tokens/sec

  • Great for high-volume chat
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Embeddings

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Throughput

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DeepSeek · OCR

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OCR-focused multimodal stack for documents.

Throughput

860 tokens/sec

  • Multimodal messages for scans
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  • Batch pages for throughput
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