Benchmark Almanac

DeepSeek search Q&A evaluation

DeepSeek-V4-Pro 28.1% Only in system cards

Models answer objective and subjective Chinese search questions with retrieval or agentic search. Pairwise judging gives win, loss and tie rates.

In-house DeepSeek evaluation. The prompts are not public.

Made by DeepSeek Released Apr 2026 Questions that need search Tasks kept private Last in a system card Apr 2026 Last model added Apr 2026
Level
Everyday Most adults, without training
Scored
Ranked by matches Models play against each other, and the results become ratings.
Answers
Open-ended Free-form text, documents, designs or media judged as a whole.
1
Model scored in lab cards
1
System card reports it, from 1 lab

DeepSeek-V4-Pro leads with 28.1%

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 DeepSeek-V4-Pro 28.1%
#ModelScoreSettingDateSource
1 DeepSeek-V4-Pro 28.1% Apr 2026 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% 2026 Near the ceiling (85%) DeepSeek-V4-Pro 0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) DeepSeek-V4-Pro

Labs report it only in system cards

We read the headline results of 479 launch posts from 51 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
26 Apr 2026 DeepSeek-V4-Pro technical report 28.1 Search Q&A, retrieval augmented search, total V4 win rate vs DeepSeek-V3.2 over 956 questions, V3.2 10.4, tie 61.5 (Table 11) Capabilities

More in Knowledge

All 109 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%
  • 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%
  • BIG-Bench Extra Hard In use Models solve harder replacements for each of the 23 BIG-Bench Hard tasks, 4,520 examples in total. The score is a harmonic mean of task accuracies. Gemma 4 31B IT 74.4%
  • 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%