Qwen1.5-32B-Chat · RepoQA & LongCodeArena · RepoQA retrieval accuracy · similarity threshold 0.8 ↗
Qwen / MODEL EVIDENCE
Qwen1.5-32B-Chat
2 benchmarks · 3 observations · 2 sources
Scores at a glance
2 benchmarks · large dot: Qwen1.5-32B-Chat; small dots: closest models where reported
Qwen1.5-32B-Chat · MixEval & MixEval-Hard · accuracy · original comparison ↗
1 more reported result
81% · Qwen1.5-32B-Chat · MixEval & MixEval-Hard · accuracy · original comparison · MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures ↗
Closest models by score
Similar positions on shared benchmark leaderboards. Smaller gaps are closer.
Mistral-7B-Instruct-v0.2 →Mistral
2 of 2 shared benchmark comparisons
2 of 2 shared benchmark comparisons
Mixtral-8x7B-Instruct-v0.1 →Mistral
2 of 2 shared benchmark comparisons
How similarity is measured
Mean absolute gap in percentile positions on shared benchmark settings; lower is closer. At least 60% overlap is required, with a minimum of three when available. Independent evaluations are used when there are at least three; otherwise published report comparisons are used. Repeated model observations within one setting are averaged before ranking. Writing-style traits and composite indices are excluded. This describes similarity, not an overall quality ranking.
Sources
Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.
- RepoQA: Evaluating Long Context Code Understanding — published result table ↗
All 8 authors
Jiawei Liu, Jia Le Tian, Vijay Daita, Yuxiang Wei, Yifeng Ding, Yuhan Katherine Wang, Jun Yang, Lingming Zhang
- MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures — published result table ↗
All 8 authors
Jinjie Ni, Fuzhao Xue, Xiang Yue, Yuntian Deng, Mahir Shah, Kabir Jain, Graham Neubig, Yang You
Names used in source tables
Qwen1.5-32B-Chat