Benchmark Almanac

Design Bench (Moonshot)

Kimi K3.1 Pro 957 In use

Models make graphic designs from direct prompts or few-shot reference images. An automated grader rates the results as Elo scores.

In-house. It shares the DECK-Arena harness and grader. Other benchmarks use the same name.

Made by Moonshot AI Released Oct 2026 Taste and style Tasks kept private Last in a launch post Oct 2026 Last model added Oct 2026
Level
University Undergraduates and entry-level professionals
Scored
Graded by a model A language model scores each response, usually against a rubric.
Answers
Open-ended Free-form text, documents, designs or media judged as a whole.
1
Model scored in lab cards
1
Launch post lists it, from 1 lab

Kimi K3.1 Pro leads with 957

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.

Bars start at 909.15.

Bars start at 909.15.

  1. 1 Kimi K3.1 Pro 957
#ModelScoreSettingDateSource
1 Kimi K3.1 Pro 957 Oct 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
957 2027 957 2027

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.

Moonshot AI
DateLaunch postScoreAs the post writes it
24 Oct 2026 Kimi K3.1 Pro 957 Design Bench (Internal, Elo-score)

More in Writing and taste

All 24 in Writing and taste
  • WritingBench Fading Models complete 1,000 real-world writing requests across 6 domains and 100 subdomains. A judge model scores each reply on five query-specific criteria. GPT-5 83.9
  • Creative Writing (MiniMax in-house) Only in system cards Models write creative pieces for real Hailuo AI user requests. Automatic assessments score the writing. MiniMax-Text-01 81.3%
  • DeepSeek Chinese functional writing evaluation Only in system cards Models answer 3,170 everyday Chinese writing prompts such as reports, emails and speeches. Pairwise judging against a baseline model gives a win rate. DeepSeek-V4-Pro 62.6%
  • Slide generation human evaluation (Z.ai) Only in system cards People compare HTML slide decks from two models on content, layout and visual quality. Metric is overall win rate. GLM-5 67.5%
  • Task-dependent output homogenization evaluation Only in system cards Models answer prompts several times. A judge scores functional diversity where it is wanted and consistency where one answer is right. Muse Spark 0.21
  • DeepSeek Chinese creative writing evaluation Only in system cards Models write Chinese fiction, prose, poetry and lyrics for 2,837 prompts. Pairwise judging gives separate win rates for instruction following and writing quality.