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BenchLM

CC-OCR

We show this table for reference; we do not rank on it.

Data verified 34 confirmed releases in the last 30 daysFollow model changes

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

Benchmark score on CC-OCR — September 27, 2026

We compile the CC-OCR rows from provider self-reports. Qwen3.6-35B-A3B leads the table at 81.9%, followed by Qwen3.6-27B (81.2%) and Qwen3.8 Max (79.6%). We do not use these results to rank models overall.

1Open weights

Qwen3.6-35B-A3B

Alibaba

81.9%
Overall 41.88Context 262K
2Open weights

Qwen3.6-27B

Alibaba

81.2%
Overall 46.49Context 262K
3Open weights

Qwen3.8 Max

Alibaba

79.6%
Overall 71.8Context 1M

3 modelsMultimodal & GroundedCurrentDisplay onlyUpdated September 27, 2026

Benchmark score table (3 models)

Score
1
Qwen3.6-35B-A3BAlibaba · Open weight
81.9%
2
Qwen3.6-27BAlibaba · Open weight
81.2%
3
Qwen3.8 MaxAlibaba · Open weight
79.6%

Among the reported CC-OCR rows, Qwen3.6-35B-A3B is first at 81.9%. The third row is 2.3 points behind. The broader top-10 range is 2.3 points, so many of the published results sit in a relatively narrow band.

3 models have been evaluated on CC-OCR. The benchmark falls in the Multimodal & Grounded category. CC-OCR is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.

About CC-OCR

Year

2026

Tasks

Optical character recognition

Format

Text extraction from images and documents

Difficulty

Document reading

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.

Qwen3.6 launch benchmarks

Freshness and provenance

Version

CC-OCR 2026

Refresh cadence

Quarterly

Staleness state

Current

Question availability

Public benchmark set

CurrentDisplay only

BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.

Questions

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.

Compare top models on CC-OCR

Qwen3.6-35B-A3B vs Qwen3.6-27BQwen3.6-27B vs Qwen3.8 Max
Last updated: September 27, 2026 · BenchLM version CC-OCR 2026

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