scoring

ONNX Runtime hybrid search scoring inconsistencies on GPU

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Problem – HybridSearch Scoring Inconsistencies on GPU In a development sandbox (Ubuntu 22.04, NVIDIA A10G, ONNX Runtime 1.18, PyTorch backend) a BERT‑based reranker that uses the HybridSearch operator returns different top‑k results when the model is executed on the CPU (FP32) versus the GPU (FP16 mixed‑precision). Typical symptoms include: Top‑5 candidate order differs by up to three positions. … Read more

Mistral AI hybrid search scoring discrepancy between staging and production

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Problem Description Symptoms and Impact After the nightly CI/CD pipeline retrains the Mistral AI embedding model and rolls out the new container image, the /v1/hybrid-search endpoint returns noticeably different relevance scores in the production Kubernetes cluster compared to the staging cluster. Typical observations: Top‑K results differ in ordering despite identical query text. Score drift of … Read more

Gemini hybrid search scoring inconsistency in air-gapped environment

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Problem – Gemini Hybrid Search Scoring Inconsistency in an Air‑Gapped Deployment Engineers deploying Google Gemini in a hybrid search configuration (vector + keyword) inside an air‑gapped environment have reported that the relevance scores returned for the same query differ dramatically between the local vector database and the remote knowledge‑base (KB) component. Typical manifestations include: Score … Read more