long context benchmark
MRCR v2 8-needle variant evaluated on contexts from 512K to 1M tokens.
Updated Aug 17, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelOP | Score73.8% | Percentile100.0% | Participants3 | EvidenceC | Evaluated |
| Rank02 | ModelOP | Score72.5% | Percentile50.0% | Participants3 | EvidenceC | Evaluated |
| Rank03 | ModelOP | Score41.3% | Percentile0.0% | Participants3 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
A closer view of the leading 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 mrcr v2 (8-needle, 512k-1m) AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
Selection summary
GPT-5.6 Sol currently leads MRCR v2 (8-needle, 512K-1M) with 73.8%. 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 MRCR v2 (8-needle, 512K-1M) measures and how its scores work.
MRCR v2 8-needle variant evaluated on contexts from 512K to 1M tokens.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about MRCR v2 (8-needle, 512K-1M).
GPT-5.6 Sol is currently ranked first with 73.8%.
MRCR v2 8-needle variant evaluated on contexts from 512K to 1M tokens.
Yes. Higher values rank better for this benchmark.
3 model results are currently shown.
Yes. This benchmark can contribute to the current LLMBoard capability score.