# CC-OCR

> An OCR-focused benchmark for reading and extracting text from visually complex documents and images.

Canonical page: https://benchlm.ai/benchmarks/ccocr

- Category: [Multimodal & Grounded](/multimodal-grounded)
- Last updated: September 27, 2026

## About CC-OCR

- Year: 2026
- Tasks: Optical character recognition
- Format: Text extraction from images and documents
- Difficulty: Document reading
- Paper: [Qwen3.6 launch benchmarks](https://qwen.ai/blog?id=qwen3.6)

CC-OCR is useful as a direct check on raw reading ability before higher-level reasoning. It highlights whether failures come from extraction quality or from later reasoning over the extracted content.

CC-OCR is currently displayed on BenchLM for reference, but it is excluded from the weighted scoring formula.

## Leaderboard (3 models)

| Rank | Model | Creator | Score |
|------|-------|---------|-------|
| 1 | [Qwen3.6-35B-A3B](/models/qwen3-6-35b-a3b) | Alibaba | 81.9% |
| 2 | [Qwen3.6-27B](/models/qwen3-6-27b) | Alibaba | 81.2% |
| 3 | [Qwen3.8 Max](/models/qwen3-8-max) | Alibaba | 79.6% |

## FAQ

### What does CC-OCR measure?

An OCR-focused benchmark for reading and extracting text from visually complex documents and images.

### Which model scores highest on CC-OCR?

Qwen3.6-35B-A3B by Alibaba currently leads with a score of 81.9% on CC-OCR.

### How many models are evaluated on CC-OCR?

3 AI models have been evaluated on CC-OCR on BenchLM.

### Does CC-OCR affect BenchLM's overall score?

Not directly. CC-OCR is still displayed on BenchLM for reference, but it is excluded from the weighted scoring formula.

## Compare Top Models on CC-OCR

- [Qwen3.6-35B-A3B vs Qwen3.6-27B](/compare/qwen3-6-27b-vs-qwen3-6-35b-a3b)
- [Qwen3.6-27B vs Qwen3.8 Max](/compare/qwen3-6-27b-vs-qwen3-8-max)