MCR-Bench - TypeScript Defect Identification F1: leaderboard

MCR-Bench (arXiv 2608.27442v1, Table 5): multi-round code review, where a model follows pull-request discussions and code revisions across review rounds and must identify the defects raised. Defect identification F1 against annotated defects on the TypeScript subset, percent; plain prompting without a review scaffold. Higher is better.

Metric: F1 (%; matched defects). Source: arxiv.org. Saturation forecast: Around March 2027. 7 models tracked.

Top models

#ModelScoreOverall rank
1Claude Haiku 4.552#287
2GPT-5.251.6#115
3Gemini 3 Flash48.6#103
4DeepSeek V3.246#210
5GLM-4.742.5#202
6Qwen 3 Max38.8#213
7Kimi K233.1#252

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=mcr-bench-typescript-defect-identification-f1 · How It Works · Data refreshed daily, snapshot 2026-11-05.