Benchmark Almanac

ITBench

Gemini 3 Pro 58.3% leads since November 2025
Not in model cards

Agents handle IT automation tasks in Kubernetes environments: site reliability incidents, compliance and security checks, and cloud cost work.

Presented as an oral at ICML 2025. IBM and Kaggle added an ITBench leaderboard in 2025-12.

Made by
IBM Research
Released
February 2025
Kind
Terminal tasks
Level
Expert
Scored
Checked automatically
Answers
Agent task
Tasks
All public
Strongest model tested
Gemini 3 Pro #55 on the capability index
Last model added
November 2025
Scores refreshed
November 12th, 2026

In the authors’ words

Realizing the vision of using AI agents to automate critical IT tasks depends on the ability to measure and understand effectiveness of proposed solutions. We introduce ITBench, a framework that offers a systematic methodology for benchmarking AI agents to address real-world IT automation tasks. Our initial release targets three key areas: Site Reliability Engineering (SRE), Compliance and Security Operations (CISO), and Financial Operations (FinOps). The design enables AI researchers to understand the challenges and opportunities of AI agents for IT automation with push-button workflows and interpretable metrics. ITBench includes an initial set of 94 real-world scenarios, which can be easily extended by community contributions. Our results show that agents powered by state-of-the-art models resolve only 13.8% of SRE scenarios, 25.2% of CISO scenarios, and 0% of FinOps scenarios. We expect ITBench to be a key enabler of AI-driven IT automation that is correct, safe, and fast.

Abstract of ITBench: Evaluating AI Agents across Diverse Real-World IT Automation Tasks (arXiv:2502.05352, CC0)
13
Models scored on its own leaderboard

Gemini 3 Pro leads with 58.3% among models released by November 2025

Best score per model from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best.

The newest model with a score here came out in November 2025, and nobody has tested a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:

  1. 1 Gemini 3 Pro 58.3%
  2. 2 GPT-5.1 55.2%
  3. 3 Claude Opus 4.5 52.1%
  4. 4 GPT-5 51.9%
  5. 5 o3 51.7%
  6. 6 Gemini 2.5 Flash Sep 2025 51.7%
  7. 7 Qwen3-235B-A22B 46%
  8. 8 Claude Sonnet 4.5 45.8%
  9. 9 Gemini 2.5 Pro Jun 2025 42.3%
  10. 10 Claude Haiku 4.5 42.1%
  11. 11 Grok 4.1 Fast reasoning 39%
  12. 12 Mistral Small 3.1 32.9%
  13. 13 DeepSeek-R1 May 2025 23.3%

Source: Official ITBench leaderboard

#ModelScoreSettingDateSource
1 Gemini 3 Pro 58.3% Nov 2025 Official leaderboard
2 GPT-5.1 55.2% Nov 2025 Official leaderboard
3 Claude Opus 4.5 52.1% Nov 2025 Official leaderboard
4 GPT-5 51.9% Aug 2025 Official leaderboard
5 o3 51.7% Apr 2025 Official leaderboard
6 Gemini 2.5 Flash Sep 2025 51.7% Sep 2025 Official leaderboard
7 Qwen3-235B-A22B 46% Apr 2025 Official leaderboard
8 Claude Sonnet 4.5 45.8% Sep 2025 Official leaderboard
9 Gemini 2.5 Pro Jun 2025 42.3% Jun 2025 Official leaderboard
10 Claude Haiku 4.5 42.1% Oct 2025 Official leaderboard
11 Grok 4.1 Fast 39% reasoning Nov 2025 Official leaderboard
12 Mistral Small 3.1 32.9% Mar 2025 Official leaderboard
13 DeepSeek-R1 May 2025 23.3% May 2025 Official leaderboard

5 models have held number one on the official leaderboard since its release in February 2025

Lab claims count from the day the card came out, independent runs from the model’s release.

Mistral AI OpenAI Google DeepMind
Own leaderboard Not tested since Nov 2025
Gemini 3 Pro 58.3%

Source: Official ITBench leaderboard

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

On the benchmark’s own leaderboard Best so far
0% 20% 40% 60% 80% 100% 2025 2026 Near the ceiling (85%) Gemini 3 Pro GPT-5 o3 Mistral Small 3.1 0% 20% 40% 60% 80% 100% 2025 2026 Near the ceiling (85%) Gemini 3 Pro GPT-5

Source: Official ITBench leaderboard

No lab model card reports it yet

We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark.

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  • Harbor-Index In use Agents solve about 80 hard tasks drawn from 29 benchmarks run through Harbor adapters, such as HLE, GSO and SWE-bench Pro. Each task keeps its source verifier. GPT-5.5 28.1%
  • Terminal-Bench 2.1 Extended Not in model cards Agents complete long command-line tasks in containers, scored by verification tests. Mercor adds 99 new expert-written tasks to the 89 public ones and reports both scores. Muse Wonder 54%
  • Terminal-Bench 4.1 Not in model cards The Terminal-Bench 4.0 tasks with hardened verifiers: agents complete 66 hard tasks in containerized terminals across software, ML, science, security, and operations. Test scripts verify each result, scored as resolution rate. Claude Opus 5.5 65.8%
  • o11y-bench Not in model cards Agents query metrics, logs and traces in a live Grafana stack, investigate incidents and fix dashboards. Grading checks claims against facts read from the same environment. Claude Opus 5.5 93.8%