A million-token MRCR long-context retrieval benchmark reported in DeepSeek-V4 model evaluations.
BenchLM mirrors the published score view for MRCR 1M. DeepSeek V4 Pro (Max) leads the public snapshot at 83.5% , followed by DeepSeek V4 Pro (High) (83.3%) and DeepSeek V4 Flash (Max) (78.7%). BenchLM does not use these results to rank models overall.
DeepSeek V4 Pro (Max)
DeepSeek
DeepSeek V4 Pro (High)
DeepSeek
DeepSeek V4 Flash (Max)
DeepSeek
The published MRCR 1M snapshot is tightly clustered at the top: DeepSeek V4 Pro (Max) sits at 83.5%, while the third row is only 4.8 points behind. The broader top-10 spread is 46.0 points, so the benchmark still separates strong models even when the leaders cluster.
6 models have been evaluated on MRCR 1M. The benchmark falls in the Reasoning category. This category carries a 17% weight in BenchLM.ai's overall scoring system. MRCR 1M is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
Year
2026
Tasks
Million-token retrieval
Format
Long-context retrieval MMR
Difficulty
Million-token long context
BenchLM stores this DeepSeek-reported MRCR 1M value as a display-only row distinct from the existing MRCRv2 keys.
Version
MRCR 1M 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.
A million-token MRCR long-context retrieval benchmark reported in DeepSeek-V4 model evaluations.
DeepSeek V4 Pro (Max) by DeepSeek currently leads with a score of 83.5% on MRCR 1M.
6 AI models have been evaluated on MRCR 1M on BenchLM.
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