Benchmark Almanac

HoneyBench v0.2-alpha

In use

Measures reward hacking: how often an agent games its grader instead of doing the task. Lower is better.

Version 0.2-alpha. Labs have published little about its tasks or scoring.

Made by
Goodhart Labs
Released
November 2026
Kind
Deception and alignment
Level
Research frontier
Scored
Graded by a model
Answers
Agent task
Last in a launch post
November 2026
Last model added
November 2026
1
Model scored in lab cards
1
Launch post lists it, from 1 lab

Inkling 2 Small leads with 44.0

Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.

  1. 1 Inkling 2 Small 44.0

Source: Labs’ model cards

#ModelScoreSettingDateSource
1 Inkling 2 Small 44.0 Nov 2026 Lab model card

Scores over time

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

Reported by the lab in its model card
44.0 2027 44.0 2027

Source: Labs’ model cards

One lab put it in a launch post in the last six months

Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.

Thinking Machines
DateLaunch postScoreAs the post writes it
Nov 5, 2026 Inkling 2 Small 44 HoneyBench v0.2-alpha Reward Hacking, 44, lower is better

More in Safety and alignment

All 465 in Safety and alignment
  • FORTRESS In use Paired adversarial and benign national-security misuse prompts. Rubric-graded risk score on adversarial and over-refusal score on benign prompts. Claude Opus 5.5 5.78%
  • StrongREJECT In use Forbidden-prompt jailbreak benchmark with a rubric grader that scores how useful a non-refusal actually is. Inkling 98.6%
  • Gray Swan IPI Arena benchmark In use Indirect prompt-injection attacks from public red-teaming competitions replayed on tool, coding and browser agents. Attack success rate at k attempts. Gemini 4 Carbon 0%
  • DistressBench In use Models reply as a chatbot to 718 simulated users in psychological crisis, in single-turn and multi-turn chats. Three judge models score replies against clinician-written rubrics. Muse Spark 1.2 88.4%
  • Lakera B3 (Backbone Breaker Benchmark) In use Crowdsourced prompt-injection attacks hit backbone LLMs inside agent threat snapshots at three defense levels. The score is attack resistance, 100 minus the board's vulnerability percentage. Claude Opus 4.5 89%
  • IHEval In use Models face conflicts between system, user and tool instructions. Reports a composite score for following the higher-priority instruction. GPT-4o 70%