MemoryBench (Meta): Results as Published

MemoryBench is an internal Meta benchmark of recall across long multi-turn conversations of 64K to 100K tokens: the target facts are spread over several turns, with distractor conversations and injected turns that conflict with or later update them. An LLM judge scores each answer against weighted, question-specific rubric criteria.

Every number here is read from the same catalog file as the benchmark table, data version 2026103001, and is the number the table shows for that model and test. Where one page printed a model under several setups, each value is listed. The catalog is public in armanobosyan/sugra-llm-benchmarks; a wrong number can be reported from the table, with Report an error under the value, or as an issue in that repository.