Mixedbread Changelog

Vercel Marketplace Integration

Mixedbread is now available on the Vercel Marketplace as a Vercel Native integration in the Searching (and Agents) categories. Install it to:

• Connect projects in one click: we’ll add the required MXBAI_API_KEY and MXBAI_STORE_ID env vars to your Vercel projects automatically.

• Manage from the Vercel dashboard: monitor usage and costs with unified Vercel billing and access controls alongside your other integrations. Read more about it in our Vercel integration docs.

• Ship faster with a starter: deploy our example Next.js app to see Mixedbread Search in action and customize from there.

Mixedbread remains fully available as a standalone platform. Use it directly or via Vercel, whichever fits your workflow.

Mixedbread Search Public Beta

We're excited to announce the public beta of Mixedbread Search, the easy-to-use search API built from the ground up for the AI era. It is a fully-managed search engine that allows you to upload your data and start searching in minutes.

Key Features

• AI-native: Built for the AI era, with both humans and AI in mind
• Multi-modal: Search through text, images, tables, audio, and complex layouts. Video is coming soon
• Multi-lingual: Support for 100+ languages
• Fully-managed: No complex configuration, no complex setup, no complex code
• Low latency: Because you need results now, not in 5700 milliseconds
• Meaningfully state-of-the-art Search: On realistic BrowseComp-Plus benchmarks, LLM assistants are able to reach significantly better response accuracy with Mixedbread Search over existing search systems

Ingestion Speed Optimization (fast track)

Today we're excited to announce that we've optimized the ingestion speed and concurrency of our Mixedbread Search. We can ingest 1000s of files concurrently with sub 1 second latency. This is a significant improvement over the previous 20 files concurrency limit.

Key Features

• High concurrency: 1000s of files can be ingested concurrently
• Minimal latency: most files get ingested one second after they are uploaded

Public Stores

Mixedbread public stores allow users to make stores publicly accessible, so that anyone with an API key can search them. This is useful for public documentation, public knowledge bases, and other use cases where you want to share your data with the world.

Search Latency Optimization

We've optimized the hot path for the search latency of our search system, achieving sub 90ms latency without reranking and sub 120ms with reranking. This includes embedding generation, first stage single-vector retrieval, second stage multi-vector retrieval, and (optionally) reranking.

Key Features

• Minimal latency: latency so low that it's virtually undetectable by users in most scenarios.

MaxSim CPU

MaxSim CPU is a CPU-optimized version of MaxSim, a state-of-the-art similarity search operator for late-interaction models such as ColBERT and ColPali. It powers our multi-vector retrieval system, achieving sub 5ms latency on AVX2 machines.

Key Features

• CPU-optimized: Optimized for CPU-based multi-vector retrieval.
• Low latency: Sub 5ms latency on AVX2 machines.
• High throughput: 10x speedup over existing CPU-based maxsim implementations.
• Open-source: Fully accessible and customizable.

Mixedbread MCP

Introducing the Mixedbread Model Context Protocol (MCP) server, a TypeScript-based integration that exposes powerful store capabilities to AI assistants like Claude Desktop. Built as an open standard, it enables secure and controlled access to external data sources.

Key Features

• Claude Desktop Integration: Seamless integration with Claude and other MCP-compatible AI assistants
• Store Operations: Direct interaction with stores through standardized MCP tools
• Semantic Search: Enable AI assistants to search and retrieve information using natural language
• File Management: Upload, manage, and search through documents in stores
• Secure Data Access: Controlled interface for AI systems to access external data sources

Installation

npm install -g @mixedbread/mcp

mxbai CLI

Introducing the Mixedbread CLI, a command-line interface for managing Mixedbread's services directly from your terminal. Built on top of the Mixedbread SDK, it provides efficient command-line access to all core platform features.

Key Features

• Store Management: Create, list, update, and manage stores with comprehensive control
• Store File Upload & Processing: Upload files with intelligent processing strategies, metadata, and batch operations
• Semantic Search: Search through stores using natural language queries with advanced filtering
• Question Answering: Get AI-powered answers based on your store content
• Intelligent Sync: Sync files with change detection and smart processing strategies to stores

Installation

npm install -g @mixedbread/cli

Platform Alpha

Today we're excited to announce the alpha of the Mixedbread platform, bringing together all our capabilities in a unified API. Experience state-of-the-art embeddings, reranking, document parsing, and stores in one integrated solution.

Now Available in Alpha

• Embeddings API: Transform text into semantic vectors with our award-winning models
• Reranking API: Boost search relevance with advanced cross-encoder models
• Document Parsing API: Extract LLM-ready content from PDFs, DOCX, PPTX, and more
• Stores API: Fully-managed multi-modal search with automatic ingestion pipelines

mxbai-rerank-v2

The second generation of our reranking models features reinforcement learning (GRPO), extended context handling, and support for 100+ languages. These models are 8x faster than comparable alternatives while achieving higher accuracy across all benchmarks.

Models

• mxbai-rerank-base-v2 (0.5B): Balanced performance for production use
• mxbai-rerank-large-v2 (1.5B): Maximum accuracy for critical applications

mxbai-embed-xsmall-v1

Our smallest and most efficient English embedding model. Perfect for edge deployments and resource-constrained environments, it delivers competitive performance in an extra small footprint.

Batched - Dynamic Batching Library

We've open-sourced Batched, our dynamic batching library that powers Mixedbread's inference infrastructure. Achieve up to 10x throughput improvements with minimal latency impact.

Baguetter - Retrieval Testing Framework

Introducing Baguetter, our open-source framework for testing and evaluating retrieval systems. Make your search better with comprehensive testing tools designed for real-world scenarios.

BMX Algorithm

We've developed BMX, a modern take on the classic BM25 algorithm. Combining lexical and semantic signals, BMX delivers superior hybrid search performance.

deepset-mxbai-embed-de-large-v1

In collaboration with deepset, we've released a German/English embedding model that sets new performance standards among open source alternatives.

mxbai-colbert-large-v1

Our ColBERT model brings late interaction capabilities. Built on our mxbai-embed-large-v1 architecture, it achieves state-of-the-art performance on 13 BEIR benchmarks.

mxbai-embed-large-v1

Our flagship English embedding model delivers state-of-the-art performance, outperforming closed source alternatives like OpenAI's text-embedding-v3.

mxbai-embed-2d-large-v1

The world's first 2D-Matryoshka embedding model. This innovative approach allows you to reduce both the number of layers and dimensions while maintaining competitive performance.

mxbai-rerank-v1

We're launching our first generation of reranking models, available in three sizes. These models add a powerful semantic layer to existing search systems, dramatically improving result relevance.

Models

• mxbai-rerank-xsmall-v1: Ultra-efficient for high-volume applications
• mxbai-rerank-base-v1: Balanced performance and speed
• mxbai-rerank-large-v1: Maximum accuracy for critical applications