CDR-Bench - Atomic Mappers: leaderboard
CDR-Bench (2026) tests whether LLMs faithfully execute data-refinement recipes written in natural language over web, LaTeX, RAG-preparation and privacy text, using 29 Data-Juicer operators with deterministic reference outputs. This board is the percent of atomic mapper tasks (one text-rewriting operator) that the model gets exactly right within three attempts, with each model in non-thinking mode. Higher is better.
Metric: Recipe success RS@3 (%) on the atomic mapper (single text-rewriting operator) tasks of CDR-Bench (3,462 data-refinement tasks over web, LaTeX, RAG-preparation and privacy text with 29 Data-Juicer operators and deterministic reference outputs): a task counts when the model's refined text or KEEP/DROP judgment exactly matches the reference within 3 attempts; non-thinking mode, baseline prompt; higher is better. Source: arxiv.org. Saturation forecast: Around 2029. 11 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5.4 (Non-reasoning) | 30.3 | #123 (GPT-5.4) |
| 2 | Claude Opus 4.6 | 29.55 | #102 |
| 3 | Gemma 4 31B (IT) (Non-reasoning) | 29.55 | #342 (Gemma 4 31B (IT)) |
| 4 | Kimi K2.6 (Non-reasoning) | 29.23 | #178 (Kimi K2.6) |
| 5 | Claude Opus 4.5 | 27.27 | #156 |
| 6 | GLM-5 (Non-reasoning) | 26.15 | #260 (GLM-5) |
| 7 | Qwen 3.6 Max | 26.15 | #180 |
| 8 | DeepSeek V4 Flash (Non-reasoning) | 24.62 | #258 (DeepSeek V4 Flash) |
| 9 | Qwen 3.6 27B (Non-reasoning) | 24.24 | #341 (Qwen 3.6 27B) |
| 10 | Qwen 3.6 35B A3B (Non-reasoning) | 18.18 | #462 (Qwen 3.6 35B A3B) |
| 11 | Llama 4 Scout | 16.92 | #1776 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=cdr-bench-atomic-mappers · How It Works · Data refreshed daily, snapshot 2026-11-13.