@garrytan: My newest gbrain-evals just dropped - this is how gbrain does vs other options. http://ZeroEntropy.dev is SOTA for rera…

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Summary

Garry Tan released new gbrain-evals benchmarks showing ZeroEntropy.dev achieves state-of-the-art performance in reranking and embedding cost, speed, and retrieval success, beating MemPalace and Vector RAG.

My newest gbrain-evals just dropped - this is how gbrain does vs other options. http://ZeroEntropy.dev is SOTA for reranking and embedding cost, speed, and retrieval success. GBrain beats MemPalace by 1% on LongMemEval and beats Vector RAG by 38% https://github.com/garrytan/gbrain-evals/blob/main/docs/benchmarks/2026-05-23-v0.40.6.0-snapshot.md…
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My newest gbrain-evals just dropped - this is how gbrain does vs other options. http://ZeroEntropy.dev is SOTA for reranking and embedding cost, speed, and retrieval success. GBrain beats MemPalace by 1% on LongMemEval and beats Vector RAG by 38% https://github.com/garrytan/gbrain-evals/blob/main/docs/benchmarks/2026-05-23-v0.40.6.0-snapshot.md…

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# Create an API Key at https://dashboard.zeroentropy.dev

from zeroentropy import ZeroEntropy

zclient = ZeroEntropy()

response = zclient.models.rerank(
    model="zerank-2",
    query="What is Retrieval Augmented Generation?",
    documents=[
        "RAG combines retrieval with generation...",
    ],
)

for doc in response.results:
    print(doc)

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