Latest Blogs
Catch all the latest releases and updates from ZeroEntropy. Explore our full blog archive here.
harrier-27b: Can 27B Parameters Beat zembed-1?
A head-to-head evaluation of ZeroEntropy's zembed-1 against all three Harrier embedding models across 24 diverse datasets, using graded LLM relevance judgments.
Smarter Context Compression for LLM Pipelines: zerank-2 as a Calibrated Classifier
How to use zerank-2's calibrated relevance scores as a binary classifier for context compression, document routing, and multi-label classification — at 50-100x less cost than LLM classification.
Beyond Binary: A New Version of the MTEB
We re-annotated 24 MTEB datasets with LLM pointwise scoring on a 0-10 scale using three independent judges. With graded relevance, the retrieval leaderboard looks meaningfully different.
zembed-1 vs voyage-4
A thorough evaluation comparing the performance of ZeroEntropy's zembed-1 and Voyage's latest voyage-4 embedding models.
Introducing zembed-1: The World's Best Text-Embedding Model
Introducing zembed-1: The World's Best Text-Embedding Model
How Assembled Powers High-Quality AI Customer Support with ZeroEntropy
After integrating ZeroEntropy's reranking into their retrieval pipeline and validating it on live production traffic, Assembled migrated to 100% of their reranking volume through ZeroEntropy.
Prompting Best Practices For Instruction-Following Rerankers
In this guide, we will go over best practices around prompting a reranker for state-of-the-art relevance.
Open-source alternatives to Cohere Rerank in 2026
Learn about the open-source and open-weight rerankers to use as an alternative to closed-source models.
Latency Performance Assessment of zerank-2
In this blog, we go over the latency performance of ZeroEntropy's latest reranker model zerank-2.
Introducing zerank-2: The Most Accurate Multilingual Instruction-Following Reranker
zerank-2 is ZeroEntropy's latest multilingual cross-encoder model, tuned for instruction-following, and score calibration.
The Latency Myth: Why Reranking Is Still the Smartest Optimization You Can Make
Yes, technically, rerankers add a layer to your search pipeline. Yet, reranking improves both efficiency and quality once you consider the full retrieval-generation loop.
How Vera Health Achieved State-of-the-Art Clinical Accuracy Using ZeroEntropy
Vera Health sets a new accuracy record on medical question answering using ZeroEntropy Search and Rerank APIs.
Implementing ZeroEntropy Reranking with turbopuffer Retrieval
Learn how to implement a two-step search pipeline for fast and accurate retrieval, using turbopuffer and ZeroEntropy.
Paper TLDR: How we trained zerank-1 with the zELO method
This is a short TLDR summarizing the main concepts in the zELO paper. We describe the training approach of ZeroEntropy's reranker zerank-1.
Mem0 Improves Memory Retrieval Accuracy with ZeroEntropy
Mem0 migrated their production rerank traffic to ZeroEntropy's zerank-1, a critical component of their retrieval stack.
Should You Use LLMs for Reranking? A Deep Dive into Pointwise, Listwise, and Cross-Encoders
Are LLMs cheap, calibrated, and fast enough for reranking tasks? How should you select the best results from a candidate set of k=100, or even k=200? We go over the pros and cons of using LLMs as rerankers and what the best approach is.
My AskAI Improves Support Agent Latency and Accuracy with ZeroEntropy
My AskAI replaced its existing reranker with ZeroEntropy's zerank‑1 across production traffic. Results: faster responses at scale, a measurable lift in answer quality, and lower cost.
Announcing ZeroEntropy's First Rerankers: zerank-1 and zerank-1-small
Meet zerank-1: ZeroEntropy's powerful new reranker, outperforming Cohere and Gemini with up to 28% higher precision—now live via API and Hugging Face.
ZeroEntropy Raises $4.2M Seed Round to Make AI Retrieval Truly Intelligent
ZeroEntropy raises $4.2M to reinvent AI retrieval—enabling lightning-fast, accurate search across unstructured data. Backed by YC, Initialized & more.
Improving Retrieval with ELO Scores
ZeroEntropy uses chess-inspired ELO scores to train the next-gen reranker—boosting accuracy with nuanced, scalable relevance scoring. Try zerank-1 today.
What is a reranker and do I need one?
Learn what a reranker is and how it boosts precision in RAG pipelines—surface the right results faster, reduce hallucinations, and improve LLM output quality.
Deep Dive: The Architecture of ZeroEntropy v1
Discover how ZeroEntropy v1 blends BM25, dense embeddings, and LLMs for lightning-fast, accurate hybrid search over unstructured documents.
