Arena 分析 Agent Arena: Code 中 29 个模型的 20840 条 trace 后发现,前沿模型获得的正向反馈明显更多,新模型整体反馈更偏正面。
What can user praise and complaints tell us about coding agents themselves?
We analyzed 20,840 traces from Agent Arena: Code across 29 models, and found that direct feedback unlocks novel opportunities in tracking the frontier.
Some topline findings:
- Today’s frontier models receive markedly more positive feedback. Overall, newer models across labs tend to show a more positive feedback balance.
- Broken code is still the biggest driver of complaints, sloppy behavior comes second. 69.1% of complaints point to code not working. The next themes are incomplete output (27.1%), weak finish and usability (27.1%), and ignored instructions (20.3%).
- Models share common weaknesses, but differ in how they disappoint. Fable 5.1 attracts fewer “slop” and design complaints than Astra (3.9% versus 5.7% of sampled traces), and fewer complaints about being “flaky” (3.1% versus 5.0%).
Read more by diving into the full article from @DawidGalarowicz below.
https://x.com/i/article/2101066086867492864在 X 查看被引用的帖子
来源:Arena.ai · x.com