Qwen / qwen/qwen-vl-ocr
Qwen-Vl-Ocr - access through LLMTR
Qwen-Vl-Ocr is optimized for extracting text from images, reading document layout, and OCR-heavy workflows. It is more useful for data extraction and document understanding than for general multimodal chat.
Technical specifications
| Canonical ID | qwen/qwen-vl-ocr |
|---|---|
| Provider | Qwen |
| Context window | 256,000 tokens |
| Operations | CHAT_COMPLETIONS |
| Modalities | text |
Pricing
An 8% platform margin applies to credit top-ups; model usage prices are not separately marked up.
| Operation | Metric | Unit | Price |
|---|---|---|---|
| CHAT_COMPLETIONS | INPUT_TEXT | PER_1M_TOKENS | $0.070000 |
| CHAT_COMPLETIONS | OUTPUT_TEXT | PER_1M_TOKENS | $0.160000 |
Example usage
With existing OpenAI SDK flows, change only the base URL and model identifier.
curl https://llmtr.com/v1/chat/completions -H "Authorization: Bearer llmtr-your_key" -H "Content-Type: application/json" -d '{"model":"qwen/qwen-vl-ocr","messages":[{"role":"user","content":"Hello"}]}'Guides about this model
- Lowering repeated document template cost on Qwen-VL-OCR with cache - The version/region selection and invoice-table validation articles answer different questions. This article covers how caching lowers cost in a high-volume OCR pipeline processing the same document template.
- Qwen-VL-OCR API: extracting image text with the right version and region - The Qwen-VL-OCR model identifier, provider region, and documentation address serve different purposes. Start with one image containing no personal data, then check the request format and deployment conditions.
- Read invoices and tables with Qwen-VL-OCR: validate missing fields - A synthetic invoice workflow for image submission, unknown fields and independent total checks. JSON output is neither a payment instruction nor an accuracy guarantee.
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