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#RAG

All collected and published items, ordered by time. Picks are a selected subset.
Models

New models and versions, open weights, and changes in capability and pricing, with their evaluations.

10/7Wed
  1. Google DeepMind71

    Google DeepMind releases EmbeddingGemma 2, a lightweight open multimodal embedding model

    Google DeepMind released EmbeddingGemma 2, a 740M-parameter open model based on the Gemma 4 architecture and licensed under Apache 2.0. It maps text, images, audio, and video into a shared embedding space.

    Why it matters: EmbeddingGemma 2 maps text, images, audio, and video into one embedding space and reports concrete on-device memory and vector truncation figures, helping assess local multimodal retrieval.

  2. The Decoder66

    Google releases EmbeddingGemma 2 multimodal embedding model

    Google released EmbeddingGemma 2, an open multimodal embedding model that converts text, images, video, audio, and code into numerical vectors. It has 740 million parameters. Google says it outperforms competitors with more than twice as many parameters on multimodal embedding benchmarks and scores 78.68 on the Massive Text Embedding Benchmark (Code), nearly 10 points above the previous model's 68.76.

  3. Sundar Pichai · X62

    Google releases EmbeddingGemma 2, an open multimodal embedding model

    Sundar Pichai announced EmbeddingGemma 2, described as Google's first open, natively multimodal embedding model. It handles text, code, image, video, and audio tasks in a modular 740M parameter form factor, is positioned for offline, privacy-first RAG when paired with Gemma 4, and is said to outperform some specialist models more than twice its size. Weights are available now on Hugging Face.

10/3Sat
  1. Hugging Face Blog62

    Ai2 open-sources AstaBrief 8B, a scientific report-generation model

    Ai2 open-sourced AstaBrief 8B, a model that turns research questions and retrieved literature excerpts into reports with citations. It was trained from Qwen3-8B using SFT and DPO and is now available as Asta's Fast mode.

    Why it matters: The source describes AstaBrief's training-data construction and citation-filtering details, which can be adapted to deploy other long-form generation models.

9/3Thu
6/23Tue
  1. Mistral AI62

    Mistral releases OCR 4 with 170-language support and single-container self-hosting

    Mistral has released OCR 4, which returns bounding boxes, block-type classifications, and per-page, per-word confidence scores in addition to extracted text. It supports 170 languages across 10 language families and can be fully self-hosted in a single container.

    Why it matters: OCR 4 returns bounding boxes, block classification, and confidence scores, helping readers assess how document parsing can fit into RAG and agent workflows.

5/28Wed
  1. Mistral AI62

    Mistral releases Codestral Embed, its first code-embedding model

    Mistral has released Codestral Embed, its first embedding model designed for code. It outperforms Voyage Code 3, Cohere Embed v4.0, and OpenAI's large embedding model on real-world code-retrieval tasks.

    Why it matters: Mistral's first code-embedding model offers adjustable dimensions and precision, helping readers weigh retrieval quality against storage costs.