AI Doubling Rate
The length of tasks (measured by how long they take human professionals) that generalist frontier model agents can complete autonomously with 50% reliability has been doubling approximately every seven months for the last six years. The shaded region represents 95% Confidence Interval calculated by hierarchical bootstrap over task families, tasks, and task attempts.
Interactive Features
- Y-Axis Scale: Toggle between Linear and Logarithmic views to see the exponential growth pattern
- Success Rate: Switch between 50% and 80% success probability metrics
- Tooltips: Hover over data points to see model details
METR Benchmark Data
The following table shows AI model performance on the METR-Horizon-v1 benchmark, measuring the task horizon (in minutes) that models can complete with 50% success rate.
| Model | Release Date | Task Horizon (50%) |
|---|---|---|
| GPT-2 | 2019-02-14 | 2.4 sec |
| davinci-002 | 2020-05-28 | 8.9 sec |
| GPT-3.5 | 2022-03-15 | 36.3 sec |
| GPT-4 | 2023-03-14 | 5.4 min |
| GPT-4 Turbo | 2023-11-06 | 8.5 min |
| GPT-4 (Jan) | 2024-01-25 | 5.4 min |
| Claude 3 Opus | 2024-03-04 | 6.4 min |
| GPT-4 Turbo (Apr) | 2024-04-09 | 6.6 min |
| GPT-4o | 2024-05-13 | 9.2 min |
| Qwen 2 72B | 2024-06-07 | 2.2 min |
| Claude 3.5 Sonnet | 2024-06-20 | 18.7 min |
| o1-preview | 2024-09-12 | 22.0 min |
| Qwen 2.5 72B | 2024-09-19 | 5.2 min |
| Claude 3.5 Sonnet v2 | 2024-10-22 | 29.6 min |
| o1 | 2024-12-05 | 41.1 min |
| DeepSeek V3 | 2024-12-26 | 18.5 min |
| DeepSeek R1 | 2025-01-20 | 26.9 min |
| Claude 3.7 Sonnet | 2025-02-24 | 56.1 min |
| DeepSeek V3 (Mar) | 2025-03-24 | 23.3 min |
| o3 | 2025-04-16 | 1.6 hrs |
| o4-mini | 2025-04-16 | 1.3 hrs |
| Claude 4 Opus | 2025-05-22 | 1.4 hrs |
| Claude 4 Sonnet | 2025-05-22 | 1.2 hrs |
| DeepSeek R1 (May) | 2025-05-28 | 32.2 min |
| Gemini 2.5 Pro | 2025-06-05 | 39.5 min |
| Grok 4 | 2025-07-09 | 1.8 hrs |
| Claude 4.1 Opus | 2025-08-05 | 1.9 hrs |
| GPT-5 | 2025-08-07 | 2.3 hrs |
| Claude Sonnet 4.5 | 2025-09-29 | 2.0 hrs |
| GPT-5.1 Codex | 2025-11-19 | 2.9 hrs |
| Claude Opus 4.5 | 2025-11-24 | 4.8 hrs |
AI's Ability to Handle Long Tasks
Summary of the METR Research
Why This Matters
As artificial intelligence (AI) becomes more advanced, it's not just about answering trivia questions or writing short emails anymore. A key question now is: Can AI complete long, complex tasks the way humans can—like writing software, planning events, or conducting research?
The METR team has developed a new, easy-to-understand way to measure this:
How long a task (in human time) can today's AI complete successfully?
What Did They Measure?
- METR looked at 170 real-world tasks like fixing software bugs, writing reports, or planning multi-step actions.
- Each task was rated by how long it typically takes a skilled human to do it—from just a few minutes to several hours.
- Then they tested how well top AI systems performed those same tasks.
What They Found
- Today's best AI systems (like OpenAI's and Anthropic's) can reliably complete tasks that take up to about 5 hours of human effort.
- For very short tasks (under 5 minutes), AI is nearly perfect.
- But as tasks get longer and more complex—especially past 8 hours—AI still struggles.
- Most importantly: the ability of AI to complete longer tasks is doubling roughly every 7 months.
Why This Trend Is Big News
If the current pace continues:
- In 2–3 years, AI may handle tasks that take a human a full week or more.
- In 5 years, it may independently manage projects that currently take a team of people a month.
This means AI could soon:
- Write complete software products
- Research and draft business strategies
- Conduct customer support or internal reporting workflows end-to-end
Things to Keep in Mind
- A 50% success rate isn't perfect. AI may still make mistakes or need supervision.
- These results are from test environments—not always real-world conditions.
- Longer-term planning and error handling are still hard for AI.
What This Means for Strategy
- Plan Ahead: AI systems may soon be capable of completing longer tasks with little oversight.
- Pilot Projects: Start testing where AI might assist or automate longer workflows.
- Talent Planning: Expect changes in the types of roles that will benefit from human–AI collaboration.
- Risk Management: Use these benchmarks to guide safe and responsible AI adoption.
Five Year Projection
Starting from late 2025 (~5 hours), if the 7-month doubling rate continues:
| Date | Projected Task Horizon |
|---|---|
| November 2025 | 5 hours |
| June 2026 | 10 hours |
| January 2027 | 20 hours |
| August 2027 | 40 hours (1 week) |
| March 2028 | 80 hours (2 weeks) |
| October 2028 | 160 hours (1 month) |
| May 2029 | 320 hours (2 months) |
| December 2029 | 640 hours (4 months) |
| July 2030 | 1280 hours (8 months) |
References
Here are the original source references from the Metr site: