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
- October 2026
- Kind
- Taste and style
- Level
- University
- Scored
- Graded by a model
- Answers
- Open-ended
- Tasks
- Kept private
- Strongest model tested
- Kimi K3.1 Pro #16 on the capability index
- Last in a launch post
- October 2026
- Last model added
- October 2026
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.
- 1 Kimi K3.1 Pro 957
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Kimi K3.1 Pro | 957 | 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
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.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| Oct 24, 2026 | Kimi K3.1 Pro | 957 | Design Bench (Internal, Elo-score) |
More in Writing and taste
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- 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.