agents benchmark
MLE-Bench Lite Leaderboard
MLE-Bench Lite evaluates AI agents on machine learning engineering tasks for Kaggle-style competitions in a lightweight evaluation format.
Updated Oct 23, 2026
Models2
Model coverage2
MetricScore
EvidenceB
MLE-Bench Lite Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelSA | Score86.20% | Percentile100.00% | Participants2 | EvidenceC | Evaluated |
| Rank02 | ModelMI | Score66.60% | Percentile0.00% | Participants2 | EvidenceC | Evaluated |
MLE-Bench Lite Highlights
The leading models and scores on this benchmark.
MLE-Bench Lite Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for MLE-Bench Lite
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What is MLE-Bench Lite?
What MLE-Bench Lite measures and how its scores work.
MLE-Bench Lite is a benchmark for evaluating AI agents on machine learning engineering tasks.
It measures agents' ability to build, train, and optimize machine learning models, using the Score metric with ratio as the unit.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- MLE-Bench Lite
- Modality
- text
- Primary category
- agents
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- overall
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about MLE-Bench Lite.
Which model scores highest on MLE-Bench Lite?
Atria Dawn Preview is currently ranked first with 86.20%.
What are the top three models on MLE-Bench Lite?
The current leaders are Atria Dawn Preview (86.20%) and MiniMax M2.7 (66.60%).
Which MLE-Bench Lite model has the lowest official input price?
MiniMax M2.7 has the lowest matched official input price at $0.30 input / $1.2 output per 1M tokens.
Which models are fastest among MLE-Bench Lite results?
No matched runtime record is currently available.
Does the highest score result prove overall model quality?
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.