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Agentset.ai

Open-source platform for building AI apps with reliable answers and RAG.

Agentset.ai news & updates

  • RAG for the AI SDK

    A practical guide to implementing retrieval-augmented generation with the AI SDK — from ingesting documents into vectors to retrieving context at query time.

    Agentset.ai Blog1 min read
  • Gemini 2 Is the Top Model for Embeddings

    Google released Gemini Embedding 2, their first natively multimodal embedding model. We ran it against 17 models across 7 datasets. It takes #1 with 1605 Elo, but the top three are within 18 points of each other.

    Agentset.ai Blog1 min read
  • GPT-5.4: OpenAI's RAG Regression

    OpenAI released GPT-5.4 with a Pro variant for extended reasoning. We tested both on our LLM-for-RAG leaderboard across three workloads.

    Agentset.ai Blog1 min read
  • Zembed-1: The Current Best Embedding Model

    ZeroEntropy released zembed-1, a 4B embedding model distilled from zerank-2 reranker. We tested it to see how it performs on real retrieval tasks.

    Agentset.ai Blog1 min read
  • Claude Sonnet 4.6 for RAG

    We evaluated Claude Sonnet 4.6 in a RAG setup across factual retrieval, synthesis, and scientific tasks compared to frontier models.

    Agentset.ai Blog1 min read
  • Voyage 4: Evaluation Notes

    We tested Gemini 3 inside an actual retrieval setup and compared it directly with GPT-5.1 across five areas that matter for RAG.

    Agentset.ai Blog1 min read
  • Claude Opus 4.6 Performance in RAG

    We evaluated Claude Opus 4.6 in a RAG setup across factual retrieval, synthesis, and scientific tasks versus 11 frontier models.

    Agentset.ai Blog1 min read
  • How to Detect Hallucinations in RAG

    RAG helps, but hallucinations still happen. We tested four detection methods to find the best for production—comparing accuracy, latency, and cost.

    Agentset.ai Blog1 min read
  • Gemini 3 Flash: A strong factual RAG model

    We evaluated Gemini 3 Flash in a RAG setup to understand where it excels and where it falls short—focusing on factual retrieval and grounding.

    Agentset.ai Blog1 min read
  • GPT-5.2 RAG Performance: We Tested It

    We plugged GPT-5.2 into our LLM RAG leaderboard and compared it against nine other frontier models under the same RAG pipeline.

    Agentset.ai Blog1 min read
  • Best Vector Databases for RAG

    We reviewed seven popular vector databases to understand how they differ in deployment, cost, and where they fit in real RAG systems.

    Agentset.ai Blog1 min read
  • Opus 4.5 is the new best model for RAG

    An evaluation of Opus 4.5 inside a real retrieval setup, compared against Gemini 3 Pro and GPT 5.1 across five behaviors that matter for RAG.

    Agentset.ai Blog1 min read
  • Gemini 3 vs GPT 5.1 for RAG

    We tested Gemini 3 inside an actual retrieval setup and compared it directly with GPT-5.1 across five areas that matter for RAG.

    Agentset.ai Blog1 min read
  • Embedding models have converged

    We compared 13 embedding models across 8 datasets using an LLM judge and ELO scoring. The result: almost all of them perform in the same narrow band.

    Agentset.ai Blog1 min read

Details are compiled from Agentset.ai's website and public sources, last verified Oct 3, 2026. Features and pricing change — confirm on the official site before you buy.

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