activeAgents

CyberGym

Metric: Pass@1 (higher is better)Introduced: 2026

Cybersecurity agent benchmark measuring model performance on offensive and defensive security tasks. DeepSeek V4.1 Flash launch materials report Pass@1 scores with max reasoning effort.

Models ranked

4

tracked on this benchmark

Score band

95.1 – 82.2

best → lowest tracked

Snapshot trend

-5.90

Sep 10 → Oct 19 · 1 models

Leaderboard

Tracked models ranked by Pass@1 (higher is better).

Compare candidates
#Model variant and provenanceScore
1
Version: CyberGymHarness: Not recordedEvaluator: Not recordedObserved: Oct 9, 2026Confidence: Not recordedSource
95.1
2
Version: CyberGymHarness: Not recordedEvaluator: Not recordedObserved: Oct 9, 2026Confidence: Not recordedSource
94.0
3
Version: CyberGym Pass@1; max reasoning effortHarness: Not recordedEvaluator: Not recordedObserved: Sep 10, 2026Confidence: Not recordedSource
88.1
4

Configuration: MiniMax M3.1 Flash

Version: CyberGymHarness: Claude Code 2.1.263 (1M context)Evaluator: MiniMaxObserved: Oct 19, 2026Confidence: self-reportedSource

Notes: MiniMax M3.1 Flash launch blog (2026-10-19) main benchmark table image m31-flash-en-2 (webp converted to png; values transcribed by eye from table) incl. footnotes. Blog prose rounds to '82%'. Retrieved 2026-10-19.

82.2

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: Sep 10, 2026

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