Visualizing AI vs. Human Performance in Technical Tasks

Kayla Zhu
2025-04-25 10:44:00
www.visualcapitalist.com

See this visualization first on the Voronoi app.

AI vs. Human Performance in Technical Tasks

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The gap between human and machine reasoning is narrowing—and fast.

Over the past year, AI systems have continued to see rapid advancements, surpassing human performance in technical tasks where they previously fell short, such as advanced math and visual reasoning.

This graphic visualizes AI systems’ performance relative to human baselines for eight AI benchmarks measuring tasks including:

Image classification
Visual reasoning
Medium-level reading comprehension
English language understanding
Multitask language understanding
Competition-level mathematics
PhD-level science questions
Multimodal understanding and reasoning

This visualization is part of Visual Capitalist’s AI Week, sponsored by Terzo. Data comes from the Stanford University 2025 AI Index Report.

An AI benchmark is a standardized test used to evaluate the performance and capabilities of AI systems on specific tasks.

AI Models Are Surpassing Humans in Technical Tasks

Below, we show how AI models have performed relative to the human baseline in various technical tasks in recent years.

Year	Perfomance relative to the human baseline (100%)	Task
2012	89.15%	Image classification
2013	91.42%	Image classification
2014	96.94%	Image classification
2015	99.47%	Image classification
2016	100.74%	Image classification
2016	80.09%	Visual reasoning
2017	101.37%	Image classification
2017	82.35%	Medium-level reading comprehension
2017	86.49%	Visual reasoning
2018	102.85%	Image classification
2018	96.23%	Medium-level reading comprehension
2018	86.70%	Visual reasoning
2019	103.75%	Image classification
2019	36.08%	Multitask language understanding
2019	103.27%	Medium-level reading comprehension
2019	94.21%	English language understanding
2019	90.67%	Visual reasoning
2020	104.11%	Image classification
2020	60.02%	Multitask language understanding
2020	103.92%	Medium-level reading comprehension
2020	99.44%	English language understanding
2020	91.38%	Visual reasoning
2021	104.34%	Image classification
2021	7.67%	Competition-level mathematics
2021	66.82%	Multitask language understanding
2021	104.15%	Medium-level reading comprehension
2021	101.56%	English language understanding
2021	102.48%	Visual reasoning
2022	103.98%	Image classification
2022	57.56%	Competition-level mathematics
2022	83.74%	Multitask language understanding
2022	101.67%	English language understanding
2022	104.36%	Visual reasoning
2023	47.78%	PhD-level science questions
2023	93.67%	Competition-level mathematics
2023	96.21%	Multitask language understanding
2023	71.91%	Multimodal understanding and reasoning
2024	108.00%	PhD-level science questions
2024	108.78%	Competition-level mathematics
2024	102.78%	Multitask language understanding
2024	94.67%	Multimodal understanding and reasoning
2024	101.78%	English language understanding

From ChatGPT to Gemini, many of the world’s leading AI models are surpassing the human baseline in a range of technical tasks.

The only task where AI systems still haven’t caught up to humans is multimodal understanding and reasoning, which involves processing and reasoning across multiple formats and disciplines, such as images, charts, and diagrams.

However, the gap is closing quickly.

In 2024, OpenAI’s o1 model scored 78.2% on MMMU, a benchmark that evaluates models on multi-discipline tasks demanding college-level subject knowledge.

This was just 4.4 percentage points below the human benchmark of 82.6%. The o1 model also has one of the lowest hallucination rates out of all AI models.

This was major jump from the end of 2023, where Google Gemini scored just 59.4%, highlighting the rapid improvement of AI performance in these technical tasks.

To dive into all the AI Week content, visit our AI content hub, brought to you by Terzo.

Learn More on the Voronoi App

To learn more about the global AI industry, check out this graphic that visualizes which countries are winning the AI patent race.

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