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    Sapience reportedly scores 97.7 on MRCR versus GPT-6 Astra’s 96.3

    A user says Sapience reads about 15,000 tokens and uses the open model DeepSeek V4 Pro to answer, while GPT-6 Astra reads 500,000–1 million tokens.

    AG
    2 Sources, 16d ago, first seen 16d ago

    TLDR

    A user sharing long-context benchmark results says Sapience scores 97.7 on OpenAI’s MRCR, compared with 96.3 for GPT-6 Astra. They describe Sapience as a custom system that reads about 15,000 tokens, with DeepSeek V4 Pro doing the answering; Astra, they say, reads the full 500,000–1 million tokens. In a follow-up reply, the same user cites similar results on RULER and suggests Sapience does not appear custom-built to game a particular long-context benchmark.

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    2 Sources, first seen 16d ago

    Combined views

    5.1K

    2 Sources, first seen 16d ago

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    4 comments
    10 saves
    2 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

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    2 Sources

    @gordic_aleksai find these long-context results quite surprising (promising?) on OpenAI's MRCR benchmark @Sapience_Labs scores 97.7 whereas GPT-6 Astra scores 96.3 Sapience is a custom system that reads in only ~15K tokens and an open model (DeepSeek V4 Pro) is doing the answering (Astra has to read the whole thing to answer, i.e. from 500k-1M tokens) [not affiliated with them, @lvrzhn is the guy behind it, i just find it cool]

    2 Sources

    @gordic_aleksai find these long-context results quite surprising (promising?) on OpenAI's MRCR benchmark @Sapience_Labs scores 97.7 whereas GPT-6 Astra scores 96.3 Sapience is a custom system that reads in only ~15K tokens and an open model (DeepSeek V4 Pro) is doing the answering (Astra has to read the whole thing to answer, i.e. from 500k-1M tokens) [not affiliated with them, @lvrzhn is the guy behind it, i just find it cool]