language benchmark
OpenRewriteEval is a benchmark for evaluating open-ended rewriting of long-form texts.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelME | Score40.10% | Percentile100.00% | Participants1 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis open-rewrite AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
Selection summary
Llama 3.2 3B Instruct currently leads Open-rewrite with 40.10%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price, and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
What Open-rewrite measures and how its scores work.
OpenRewriteEval is a language benchmark covering rewriting tasks expressed through natural language instructions, including formality, expansion, conciseness, paraphrasing, and tone and style transfer.
It measures open-ended rewriting performance and reports a Score as a ratio.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about Open-rewrite.
Llama 3.2 3B Instruct is currently ranked first with 40.10%.
The current leaders are Llama 3.2 3B Instruct (40.10%).
No matched official input price is currently available.
The fastest matched records are Llama 3.2 3B Instruct (171.50 tok/s via DeepInfra).
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It measures open-ended rewriting performance and reports a Score as a ratio.
Yes. Higher values rank better for this benchmark.
1 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.