NEWMVS for embeddings. Managed for files. Both on object storage.Vectors or files. Pick a path.Start →

Start here

Vector Store (MVS)

Bring your own vectors. Dense, sparse, and BM25 search on object storage.

Managed Indexing

Connect a bucket and auto-extract scenes, faces, OCR, transcripts, and embeddings.

Build

Compose multi-stage search in <100ms: filter, join, rerank.

Feature Extractors

Typed pipelines for faces, scenes, transcripts, OCR, fingerprints.

S3, GCS, R2, Mux, LangChain, MCP, and more. Connect your stack.

Generate and store embeddings from 50+ models, then search them.

By Industry

Map, search, and reuse the moments that perform. Plugs into iconik & Mux.

Talent search, brand safety, creative analytics.

Scene search, recommendation, archive access.

Visual search, PDP enrichment, catalog QA.

Lecture search, transcript Q&A, content safety.

View all solutions →

By Use Case

Face & Person Search

Find anyone across video libraries in milliseconds.

IP & Copyright Detection

Logos, songs, faces: one pipeline, one report.

Visual Taste & Recs

Scene-similarity ranked recommendations with RL.

Brand & Ad Safety

Pre-publish content screening at bid-time speeds.

View all use cases →

Build

API reference, SDKs, recipes, and architecture guides.

Launches, deep dives, and field notes from our engineers.

Browse supported HuggingFace models by task and modality.

See what teams are building with Mixpeek.

Education

Vendor-neutral deep dives on perception, retrieval, and embeddings.

Multimodal University

Fundamentals of multimodal retrieval, modules + certs.

Every term you need: embeddings to re-rankers.

Talks, demos, and customer sessions on demand.

Mixpeek vs. Pinecone, Weaviate, Twelve Labs, more.

Mission, team, and the multimodal vision.

We're hiring across research, infra, and design.

Talk to sales, support, or press.

White-glove 30-day production pilot for new customers.

Sign in Request Demo Get started →

Models/Embeddings/ibm-granite/granite-embedding-english-r2

HFText Embeddings

granite-embedding-english-r2

by ibm-granite

420Kdl/month

HuggingFace Run on your data, free

Identifiers

Model ID

ibm-granite/granite-embedding-english-r2

Feature URI

mixpeek://text_extractor@v1/ibm_granite_embed_english_r2

Explore on Mixpeek

More Embeddings models

Compare alternatives in this category

Best Self-Hosted Embedding Models

Hand-picked tools & platforms compared

Instruction-Tuned Embeddings

Deep-dive technical guide

Feature Extractors

See how Mixpeek runs models as extractors

Mixpeek Vector Store

Store & search embeddings at scale

Usage-based pricing for pipelines

All Curated Lists

Compare models, APIs & infrastructure

Specification

FrameworkHF

Organizationibm-granite

FeatureText Embeddings

Output1024-dim vector

Modalitiesdocument, audio

RetrieverText Similarity

Downloads/mo420K

Build a pipeline with granite-embedding-english-r2

Add this model to a processing pipeline alongside other extractors. Combine with retrieval stages for end-to-end search.

Run on your data, free

Alternative Models

BAAI/bge-large-en-v1.5

Text Embeddings

sentence-transformers/all-MiniLM-L6-v2

Text Embeddings

Qwen/Qwen3-Embedding-0.6B

Text Embeddings

nomic-ai/nomic-embed-text-v2-moe

Text Embeddings

Related in Embeddings

openai/clip-vit-large-patch14

Visual Embeddings

google/siglip-base-patch16-224

Visual Embeddings

google/siglip2-giant-opt-patch16-384

Visual Embeddings

facebook/dinov2-large

Visual Embeddings