Benchmark Almanac

Safety (MiniMax in-house)

Only in system cards

Models respond to safety-relevant user prompts. MiniMax scores whether replies are safe and helpful.

In-house MiniMax evaluation built mostly from Hailuo AI user queries in Mandarin. The queries are not public.

Made by
MiniMax
Released
January 2025
Kind
Refusing harmful requests
Level
Everyday
Scored
Graded by a model
Answers
Open-ended
Tasks
Kept private
Last in a system card
January 2025
Last model added
January 2025
1
Model scored in lab cards
1
System card reports it, from 1 lab

MiniMax-Text-01 leads with 90.9%

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 MiniMax-Text-01 90.9%

Source: Labs’ model cards

#ModelScoreSettingDateSource
1 MiniMax-Text-01 90.9% Jan 2025 Lab model card

MiniMax’s own number for MiniMax-Text-01 passed 85% in January 2025

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
0% 20% 40% 60% 80% 100% 2025 Near the ceiling (85%) MiniMax-Text-01 0% 20% 40% 60% 80% 100% 2025 Near the ceiling (85%) MiniMax-Text-01

Source: Labs’ model cards

Labs report it only in system cards

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

One system card reports it

Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.

DateDocumentScoreAs the document writes itSection
Jan 14, 2025 MiniMax-Text-01 technical report 90.9 In-house Safety (Table 12) Safety

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%