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

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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 & evaluate

API reference, SDKs, recipes, and architecture guides.

Browse supported HuggingFace models by task and modality.

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

Media & data converters: no account, runs in your browser.

See what teams are building with Mixpeek.

Learn

Best-of comparisons: vector DBs, embedding models, moderation APIs.

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

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

Papers behind multimodal search (MUVERA, SAM 3, and more) explained.

Every term you need: embeddings to re-rankers.

Videos, diagrams & university →

Mission, team, and the multimodal vision.

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

Talk to sales, support, or press.

45-min working session on your data: leave with a running notebook.

Sign in Request Demo Get started →

Fill Mask Models

Browse AI models for multimodal decomposition and recomposition pipelines: plug any model into your extractors.

303 models available

Run models on your own files, free Schedule Demo Read Documentation

Showing 97-120 of 303 models

Fill Mask

jhu-clsp/ettin-encoder-68m

64K

5

transformers

Fill Mask

nreimers/MiniLMv2-L6-H384-distilled-from-BERT-Large

63K

1

transformers

Fill Mask

flaubert/flaubert_base_uncased

60K

4

transformers

Fill Mask

microsoft/deberta-v3-xsmall

60K

48

transformers

Fill Mask

nlpaueb/legal-bert-base-uncased

60K

313

transformers

Fill Mask

unikei/bert-base-smiles

59K

9

transformers

Fill Mask

kykim/bert-kor-base

56K

36

transformers

Fill Mask

google/muril-base-cased

56K

62

transformers

Fill Mask

jhu-clsp/mmBERT-small

53K

79

transformers

Fill Mask

dccuchile/bert-base-spanish-wwm-cased

51K

76

transformers

Fill Mask

vinai/bertweet-large

50K

13

transformers

Fill Mask

InstaDeepAI/nucleotide-transformer-500m-human-ref

48K

15

transformers

Fill Mask

nlpaueb/bert-base-uncased-contracts

47K

32

transformers

Fill Mask

microsoft/infoxlm-base

46K

8

transformers

Fill Mask

klue/roberta-base

46K

50

transformers

Fill Mask

aubmindlab/bert-base-arabertv2

44K

44

transformers

Fill Mask

dmis-lab/biobert-base-cased-v1.2

44K

55

transformers

Fill Mask

multimolecule/rnafm

43K

multimolecule

Fill Mask

Twitter/twhin-bert-base

40K

46

transformers

Fill Mask

SAVSNET/PetBERT

40K

5

transformers

Fill Mask

snunlp/KR-ELECTRA-generator

40K

1

transformers

Fill Mask

westlake-repl/SaProt_650M_PDB

39K

4

transformers

Fill Mask

biohub/ESMC-600M

39K

12

transformers

Fill Mask

klue/bert-base

38K

62

transformers

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Retrievers

What's new in models

Jun 22, 2026200+ model pages and new retrieval deep-divesExpanded the model catalog with enriched pages (architecture, benchmarks, Mixpeek SDK examples, and pipeline pairings) across embedding, vision-language, video, audio, OCR, and reranking models: plus new vendor-neutral guides on Matryoshka embeddings, reasoning rerankers, and retrieval feedback loops.