tools
Mixedbread Embed
Legacy direct embedding APIs and models from Mixedbread; new integrations are directed to Mixedbread Search Stores.
Mixedbread Embed was a set of direct embedding APIs and open-source embedding models for creating vector representations of text and other content. Listed model families include mxbai-embed-large-v1, mxbai-embed-2d-large-v1, and mxbai-embed-xsmall-v1.
Mixedbread now labels the embedding documentation as legacy and recommends Stores for new managed-search integrations. Stores handle parsing, indexing, retrieval, and reranking, with usage-based pricing and optional paid plans.
Features
- Direct embedding APIs for generating vector representations
- Embedding model family mxbai-embed-large-v1
- Embedding model family mxbai-embed-2d-large-v1
- Embedding model family mxbai-embed-xsmall-v1
- Supports multilingual and multimodal search through current Stores
- Current workflow handles parsing, indexing, retrieval, and reranking
- API access for integrating search into applications
Use cases
- Generate embeddings for semantic search systems
- Build retrieval-augmented generation pipelines
- Migrate legacy embedding integrations to Mixedbread Stores
- Search documents, images, code, and video through a managed API
- Add ranked retrieval to applications and AI agents
Pros
Cons
Pricing
- Starting price
- Free
- Pricing checked
- 2026-09-19
Starter
Free
- $5 one-time credits
- 3 workspace users
- 10 stores
- 100 requests / minute
- Community Slack support
Scale
$20/ month
- $20 of credits included every month
- Unlimited workspace users
- 10,000 stores
- 1,200 queries/min, 360 ingestion/min
- Automatic backups
- Priority Slack support (same-day SLA)
Enterprise
Custom
- Volume-based discounts
- Unlimited workspace users
- Unlimited stores
- Custom rate limits & SLA
- Automatic backups, point-in-time recovery
- Dedicated support team