activeAgents

Agents' Last Exam

Metric: Score (higher is better)Introduced: 2026

Multi-domain agentic reasoning benchmark spanning professional long-horizon workflows. OpenAI's GPT-5.6 launch reports standard-mode scores; preserve harness and mode labels because code-mode and standard-mode rows are not directly comparable.

Models ranked

4

tracked on this benchmark

Score band

52.7 – 26.3

best → lowest tracked

Snapshot trend

+3.30

Aug 14 → Sep 10 · 1 models

Leaderboard

Tracked models ranked by Score (higher is better).

Compare candidates
#Model variant and provenanceScore
1
GPT-5.6 Sol
Version: OpenAI launch table; professional long-horizon workflows; standard modeHarness: Not recordedEvaluator: Not recordedObserved: Jul 9, 2026Confidence: Not recordedSource

Notes: Official GPT-5.6 GA launch benchmark row.

52.7
2
DeepSeek V4.1 Flash
Version: Agent's Last Exam Pass@1; official scaffold; max reasoning effortHarness: Not recordedEvaluator: Not recordedObserved: Sep 10, 2026Confidence: Not recordedSource
31.8
3
GLM-5.3
Version: Agents' Last Exam (CLI)Harness: Not recordedEvaluator: Not recordedObserved: Aug 14, 2026Confidence: Not recordedSource
28.5
4
GLM-5.3-Flash
Version: Agents' Last Exam (CLI)Harness: Not recordedEvaluator: Not recordedObserved: Aug 26, 2026Confidence: Not recordedSource
26.3

How to read this benchmark

This benchmark scores models where higher is better. Use scores for directional filtering and shortlisting, not universal quality ranking; then validate pricing, context window, provider availability, and fit for your workload.

Trust this score when

  • There is a fresh timestamped snapshot (or multiple snapshots) for this benchmark.
  • The model list covers the same version family you can actually deploy today.
  • Top candidates overlap with your required routing and feature requirements.

Be cautious when

  • There is only one benchmark snapshot or the dataset appears stale.
  • The benchmark metric direction is opposite of your decision objective.
  • The score difference between options is narrow and likely within implementation variance.

Related benchmarks

Last reviewed: Jul 9, 2026

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