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title: We analyzed 10,643 AI code reviews. | daily.dev
description: An analysis of 10,643 AI-powered pull request reviews run through Kilo&#x27;s platform between June 22 and July 23, 2026 reveals that open-weight models took two of...
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og:description: An analysis of 10,643 AI-powered pull request reviews run through Kilo&#x27;s platform between June 22 and July 23, 2026 reveals that open-weight models took two of...
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# We analyzed 10,643 AI code reviews.

**[Kilo Blog](https://daily.dev/sources/kilo-ai-blog)** · 6 min read · 1 upvotes · 0 comments

## Summary

An analysis of 10,643 AI-powered pull request reviews run through Kilo's platform between June 22 and July 23, 2026 reveals that open-weight models took two of the top three spots for surfacing critical findings, with Kimi K2.7 Code leading at 0.179 critical findings per review. Open-weight models accounted for 75% of tokens at roughly 16x lower cost per token than closed models. The security gap between open and closed models largely disappeared when a single outlier (GPT 5.6 Sol) was removed. Key takeaways: license category is a weak predictor of model behavior, using separate models for authoring and reviewing reduces blind spots, and 32.3% of reviews already used a different model than the one that wrote the code.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.kilo.ai/p/we-analyzed-10643-ai-code-reviews>

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---

Tags: [#open-source](https://daily.dev/tags/open-source), [#llm](https://daily.dev/tags/llm), [#ai-coding](https://daily.dev/tags/ai-coding)

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