MRCR v2 slice focused on long-context retrieval at 64K-128K lengths.
BenchLM mirrors the published score view for MRCR v2 64K-128K. GPT-5.5 leads the public snapshot at 83.1%. BenchLM does not use these results to rank models overall.
Year
2026
Tasks
8-needle retrieval tasks
Format
Long-context retrieval
Difficulty
Long-context reasoning
Measures whether models can recover the right details when multiple relevant items are buried in long contexts.
Version
MRCR v2 64K-128K 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
MRCR v2 slice focused on long-context retrieval at 64K-128K lengths.
GPT-5.5 by OpenAI currently leads with a score of 83.1% on MRCR v2 64K-128K.
1 AI models have been evaluated on MRCR v2 64K-128K on BenchLM.
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