MMLU ↗65.2%
c4ai-command-r-08-2024 · MMLU · EM · % ↗
Cohere / MODEL EVIDENCE
c4ai-command-r-08-2024
5 benchmarks · 5 observations · 5 sources · released 2024-08-30
Scores at a glance
5 benchmarks · large dot: c4ai-command-r-08-2024; small dots: closest models where reported
LMCA ↗9.19%
c4ai-command-r-08-2024 · LMCA · Score · % ↗
DTBench ↗46.4%
c4ai-command-r-08-2024 · DTBench · Accuracy · % ↗
LiveBench ↗27.48%
c4ai-command-r-08-2024 · LiveBench · Global average · % ↗
KOR-Bench ↗31.12%
C4ai-Command-R-08-2024 · KOR-Bench · Overall accuracy · main comparison ↗
Closest models by score
Similar positions on shared benchmark leaderboards. Smaller gaps are closer.
3 of 5 shared benchmark comparisons
Llama 3.1-8B →Meta
3 of 5 shared benchmark comparisons
Qwen2.5-7B →Qwen
3 of 5 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.
- KOR-Bench: Benchmarking Language Models on Knowledge-Orthogonal Reasoning Tasks — published result table ↗
All 12 authors
Kaijing Ma, Xinrun Du, Yunran Wang, Haoran Zhang, Zhoufutu Wen, Xingwei Qu, Jian Yang, Jiaheng Liu, Minghao Liu, Xiang Yue, Wenhao Huang, Ge Zhang
- DTBench — Conceptual Reasoning Index ↗
- LMCA — Conceptual Reasoning Index ↗
- Holistic Evaluation of Language Models (HELM) ↗
- LiveBench — model evaluation leaderboard ↗
Names used in source tables
C4ai-Command-R-08-2024 · c4ai-command-r-08-2024