Benchmark Almanac

Temporal reasoning with search

Only in system cards

Models with search answer real queries that test date arithmetic, stale facts and time-sensitive context. Reports error rate.

In-house Google DeepMind evaluation. The tasks are not public.

Made by
Google DeepMind
Kind
Questions that need search
Level
Everyday
Scored
Graded by a model
Answers
Short answer
Tasks
Kept private
Strongest model tested
Gemini 4 Argon #9 on the capability index
Last in a system card
October 2026
Last model added
October 2026
1
Model scored in lab cards
1
System card reports it, from 1 lab

Gemini 4 Argon leads with 11.8%

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 Gemini 4 Argon 11.8%

Source: Labs’ model cards

#ModelScoreSettingDateSource
1 Gemini 4 Argon 11.8% Oct 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
0% 20% 40% 60% 80% 100% Gemini 4 Argon 0% 20% 40% 60% 80% 100% Gemini 4 Argon

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
Oct 13, 2026 Gemini 4 Argon system card 11.8 Temporal reasoning (internal), error rate 11.8%, with search (Table 5.4) Hallucination

More in Knowledge

All 121 in Knowledge
  • MMLU-Pro In use Harder 10-option version of MMLU with reasoning-focused questions across 14 subjects. Intern-S2-397B 89.8%
  • SuperGPQA In use 26,529 graduate-level multiple-choice questions across 285 disciplines. Accuracy. Qwen 3.6 Max (Preview) 73.9%
  • WideSearch In use 200 bilingual broad info-seeking tasks: agent collects many atomic facts into a table. Scored by success rate and row/item F1. Tencent Hy4 preview 83.9%
  • BBEH micro average In use Models solve harder replacements for each of the 23 BIG-Bench Hard tasks, 4,520 examples in total. The score is the share of all examples answered correctly. Gemma 4 31B IT 74.4%
  • KMMLU-Pro In use Models answer multiple-choice questions taken from Korean National Professional Licensure exams. It tests professional knowledge used in Korean industry. Solar Pro 4 79.2%
  • HLE-Verified In use Verified and revised version of Humanity's Last Exam (1,811 items) with uncertain items removed. Seed2.0 Pro 73.6%