long context benchmark
InfiniteBench/En.MC Leaderboard
InfiniteBench/En.MC is the English Multiple Choice variant of InfiniteBench, with 12 tasks spanning diverse domains and average data length surpassing 100K tokens.
Updated Sep 5, 2026
Models1
Model coverage1
MetricScore
EvidenceB
InfiniteBench/En.MC Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelME | Score63.30% | Percentile100.00% | Participants1 | EvidenceC | Evaluated |
InfiniteBench/En.MC Highlights
The leading models and scores on this benchmark.
The Top AI Models for InfiniteBench/En.MC
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis infinitebench/en.mc AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01MEMeta
- Score
- 63.30%
- Speed
- Up to 171.50 tok/s via DeepInfra
Strengths
- Ranks #1 of 1 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures InfiniteBench/En.MC, not total model capability
Selection summary
Best AI Models for InfiniteBench/En.MC
Llama 3.2 3B Instruct currently leads InfiniteBench/En.MC with 63.30%. 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 is InfiniteBench/En.MC?
What InfiniteBench/En.MC measures and how its scores work.
InfiniteBench/En.MC is an English Multiple Choice benchmark variant for evaluating long-context capabilities across 12 tasks spanning diverse domains.
It measures long-context capabilities using the Score metric, reported as a ratio.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- InfiniteBench/En.MC
- Modality
- text
- Primary category
- long context
- 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 InfiniteBench/En.MC.
Which model scores highest on InfiniteBench/En.MC?
Llama 3.2 3B Instruct is currently ranked first with 63.30%.
What are the top three models on InfiniteBench/En.MC?
The current leaders are Llama 3.2 3B Instruct (63.30%).
Which InfiniteBench/En.MC model has the lowest official input price?
No matched official input price is currently available.
Which models are fastest among InfiniteBench/En.MC results?
The fastest matched records are Llama 3.2 3B Instruct (171.50 tok/s via DeepInfra).
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.