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To approach long context prompts proficiently, models demand sturdy remember abilities. The 'Needle In A Haystack' (NIAH) analysis measures a product's capability to accurately remember info from the large corpus of data. We Increased the robustness of this benchmark through the use of among thirty random needle/query pairs for each prompt and test

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