memory benchmark
CI Memories Coverage reports evaluation coverage for privacy behavior in memory-enabled agents using contextual-integrity scenarios.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelME | Score64.80% | 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 ci memories coverage 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
Muse Glimmer-30B currently leads CI Memories Coverage with 64.80%. 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 CI Memories Coverage measures and how its scores work.
CI Memories Coverage is a benchmark for evaluating privacy behavior in memory-enabled agents using contextual-integrity scenarios.
It measures evaluation coverage and reports the result as a Score 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 CI Memories Coverage.
Muse Glimmer-30B is currently ranked first with 64.80%.
The current leaders are Muse Glimmer-30B (64.80%).
No matched official input price is currently available.
No matched runtime record is currently available.
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It measures evaluation coverage and reports the result as a Score 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.