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SimpleVQA

Multimodal · 2025-02-18

SimpleVQA measures multimodal factuality with 2,025 short, verifiable image-grounded questions in English and Chinese whose answers do not change over time. An LLM judge grades each response correct, incorrect or not attempted, and the score is the correct rate over all questions without search tools; search-augmented runs are the separate simplevqa-with-tools benchmark. Higher is better.

Top models (higher is better)

ModelScore
Qwen3.8-Max75.0
Gemini 3 Pro Preview73.2
Gemini 3.1 Pro Preview73.1
Muse Spark71.3
Kimi K2.571.2
Qwen3.7-Plus (source unspecified)70.3
Qwen3.6 Plus (2026-04-02)67.3
Opus 4.867.3
Qwen3.5 397B A17B67.1
GPT-5.6 Sol66.6
Qwen3.5 Plus (2026-02-15)66.1
Opus 4.565.7
Qwen3.5-Omni-Plus65.3
Opus 4.662.2
Qwen3.5 122B A10B61.7
GPT-5.461.1
Qwen3.6 35B A3B58.9
Qwen3.5 35B A3B58.3
Sonnet 4.557.6
Grok 4.2057.4
GPT-5 Mini56.8
Qwen3.6 27B56.1
Qwen3.5-27B56.0
GPT-5.255.8
Qwen3.5-Omni-Flash54.4
Gemini 2.5 Flash-Lite54.1
Gemma 4 31B IT52.9
Gemma 4 26B A4B IT52.2
Qwen3.5-9B51.2
GPT-5 Nano46.0
Qwen3.5-4B43.4
Qwen3.5-2B39.5
Qwen3.5-0.8B31.3
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