# DesignArena ranks Ling-3.2-flash tenth on Image to Frontend Arena

> Original title: BREAKING: Ling-3.2-flash by @AntLingAGI lands at #10 on Image to Frontend Arena with an Elo of 1238! This model also establishes a new Pa...

- Source: Design Arena
- Published: 2026-11-05T19:45:04.000Z
- Bad Influence: https://badinfluence.news/items/qkkmcfunwg9wbr8zf7yzw8l0q
- Original: https://x.com/DesignArena/status/2118429408189132952

## Summary

DesignArena says Ant Ling's Ling-3.2-flash ranks #10 on its Image to Frontend Arena with an Elo of 1238. The model costs $0.30 per 1M input tokens and $0.90 per 1M output tokens, which DesignArena calls the cheapest for its performance level. It wins most often on Portfolio and Corporate builds, at about 63% and 60% of tournaments respectively.

## Post

BREAKING: Ling-3.2-flash by @AntLingAGI lands at #10 on Image to Frontend Arena with an Elo of 1238! This model also establishes a new Pareto frontier for Preference vs Price at $0.30 input / $0.90 output per 1M tokens, the cheapest for any model at this performance.

It most often wins on its Portfolio and Corporate builds where it wins around 63% and 60% of its tournaments respectively. This also places Ling-3.2-flash among leading models from @AIatMeta, @AnthropicAI, and @deepseek_ai.

Congrats to the @AntLingAGI team on a Top-10 placement on DesignArena!

![](https://badinfluence.news/api/img-proxy?u=https%3A%2F%2Fpbs.twimg.com%2Fmedia%2FHWYsMnGb0AAxcvi.jpg&mode=thumb&exp=1794096000&sig=82eabc6bec95d11b)

## Quoted post @AntLingAGI

> Introducing Ling-3.2-flash, Ant Ling's native multimodal model: 560B total / 25B active parameters.
> Stronger complex visual understanding, long-horizon multimodal agents, 3D understanding & interaction, and medical intelligence.
> Outscores Opus 5 (max) in release evaluations:
> - OmniDocBench1.5: 92.21 vs 90.56
> - ZEROBench(Sub): 43.71 vs 39.52
> - Vision2Web: 85.86 vs 80.20

https://x.com/AntLingAGI/status/2118428246664761379