Kimi K2.7 Code by @Kimi_Moonshot is 5th overall among open weight models on Design Arena with an Elo of 1312.
This is in the same performance band as MiniMax M3 by @MiniMax_AI. With an average generation time of 337.6 seconds, Kimi K2.7 Code is 78.8 seconds faster than Kimi K2.6
World's first benchmark for real-world design with 4M+ creators and counting. Made by @intelligence_ai
Joined June 2025
- BREAKING: Riverflow Pro 2.5, a reasoning model by @riverflow_ai that calls a mix of proprietary and open diffusion models, has scored 1st on Image Arena (Models + Routers), 1st on Graphic Design Arena, and 1st in Image Edit (Models + Routers). Riverflow Pro 2.5 averages 10 Elo
- BREAKING: GLM-5.2 is now 1st on Design Arena. With an Elo of 1360, GLM-5.2 has jumped ahead of the now unavailable Claude Fable 5. And it's open weights. This is an improvement of 4 positions and 27 Elo points to achieve one of the highest Elo scores in our code categories
- BREAKING: Reve 2.0 by @reve debuts at 2nd on Image Editing Arena with an Elo of 1325. Reve establishes a new Pareto frontier for Preference vs. Speed, faster than any model at this preference level with an average generation time of 86.8 seconds. Reve is now the highest-ranked
- Design Arena repostedBREAKING: Le Chaton Fat has fully saturated our benchmark. We are at a loss for words. In response, we are retiring Design Arena. Congratulations to the @MistralAI team, and thanks for putting us on vacation.
- Introducing Real-World Agentic Evaluations on Design Arena! Our new series of evaluations measuring end-to-end agentic model performance. Using real-world sessions and apps created by our 4M+ users, we analyzed agent traces to capture how models behave during deployment and in00:00Replying to @DesignarenaOur first set of evaluations are now live, with more to follow. View our Agentic Evaluations now at
- Replying to @DesignarenaReal-World Reach & Daily Usage Design Arena users can publish their winning apps for other community members to see. Using Wilson Score Intervals, we calculated the average unique views and real user views with apps from each model - normalized as deviations from the tableUser Retention We tracked how often users returned to an app a week after its creation on average: measuring whether models were building apps worth revisiting.
- Kimi-K2.7-Code by @Kimi_Moonshot is now available on Design Arena! Built upon Kimi K2.6, Kimi-K2.7-Code introduces improvements in coding and agent performance, reasoning efficiency, and long-horizon coding, marking it as their strongest coding model yet. Congrats to the🌘 Kimi-K2.7-Code, our latest coding model, is now released and open-sourced! 🔷 Improved coding & agent performance over K2.6: +21.8% on Kimi Code Bench v2, +11.0% on Program Bench, and +31.5% on MLS Bench Lite. 🔷 Reasoning efficiency: Less overthinking, with 30% lower
- Replying to @DesignarenaWe will continue monitoring Opus 4.8 performance and how it compares to other models. Fable analysis coming soon. Congratulations to the @AnthropicAI team on the launch, and try out Opus 4.8 for free on DesignArena.ai.
- Replying to @DesignarenaWhat this means for model selection Opus 4.8 is a step backward for UI-focused, single-turn tasks. It's worse than Opus 4.7 in both workflow and agentic settings, and substantially worse in single-turn pipelines. For teams choosing a Claude model for design work, Opus 4.7, Opus
- Replying to @DesignarenaBut there is a bright spot: Opus 4.8 is very good at backend! Opus 4.8 has real strengths in database design, API scaffolding, and auth implementation, as is shown by holding the 1st position on Design Arena’s Agentic Web Dev Backend Evaluation. Since these are easily checked
