image to text benchmark
TextVQA
TextVQA contains 45,336 questions on 28,408 images that require reasoning about text to answer. Introduced to benchmark VQA models' ability to read and reason about text within images, particularly for assistive technologies for visually impaired users. The dataset addresses the gap where existing VQA datasets had few text-based questions or were too small.
Updated Aug 11, 2026
Models15
Model coverage15
MetricScore
EvidenceB
TextVQA Ranking
Higher score ranks better on this benchmark.
| 01 | AC | 85.5% | 100.0% | 15 | C | |
| 02 | AC | 84.9% | 92.9% | 15 | C | |
| 03 | AC | 84.4% | 85.7% | 15 | C | |
| 04 | DE | 84.2% | 78.6% | 15 | C | |
| 05 | DE | 83.4% | 71.4% | 15 | C | |
| 06 | AM Nova ProAmazon | 81.5% | 64.3% | 15 | C | |
| 07 | DE | 80.7% | 57.1% | 15 | C | |
| 08 | AMNova LiteAmazon | 80.2% | 50.0% | 15 | C | |
| 09 | XA | 78.1% | 42.9% | 15 | C | |
| 10 | MI | 75.6% | 35.7% | 15 | C | |
| 11 | ME | 73.5% | 28.6% | 15 | C | |
| 12 | MI | 72.0% | 21.4% | 15 | C | |
| 13 | GO | 67.7% | 14.3% | 15 | C | |
| 14 | GO | 65.1% | 7.1% | 15 | C | |
| 15 | GO | 57.8% | 0.0% | 15 | C |
TextVQA Score Distribution
A closer view of the leading scores on this benchmark.
TextVQA Highlights
The leading models and scores on this benchmark.
What is TextVQA?
What TextVQA measures and how its scores work.
TextVQA contains 45,336 questions on 28,408 images that require reasoning about text to answer. Introduced to benchmark VQA models' ability to read and reason about text within images, particularly for assistive technologies for visually impaired users. The dataset addresses the gap where existing VQA datasets had few text-based questions or were too small.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- TextVQA
- Modality
- multimodal
- Primary category
- image to text
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- textvqa|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about TextVQA.
Which model scores highest on TextVQA?
Qwen2-VL-72B-Instruct is currently ranked first with 85.5%.
What does TextVQA measure?
TextVQA contains 45,336 questions on 28,408 images that require reasoning about text to answer. Introduced to benchmark VQA models' ability to read and reason about text within images, particularly for assistive technologies for visually impaired users. The dataset addresses the gap where existing VQA datasets had few text-based questions or were too small.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
15 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.