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 & evaluate

API reference, SDKs, recipes, and architecture guides.

Browse supported HuggingFace models by task and modality.

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

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 →

Text To Speech Models

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

333 models available

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

Showing 73-96 of 333 models

Text To Speech

isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF

23K

72

transformers

Text To Speech

myshell-ai/MeloTTS-Japanese

23K

18

transformers

Text To Speech

kenpath/svara-tts-voiceclone-beta

22K

7

transformers

Text To Speech

nari-labs/Dia-1.6B

22K

2,904

Text To Speech

ai4bharat/IndicF5

21K

166

Text To Speech

FunAudioLLM/Fun-CosyVoice3-0.5B-2512

20K

612

Text To Speech

kakao-enterprise/vits-ljs

20K

50

transformers

Text To Speech

nineninesix/kani-tts-400m-en

19K

39

transformers

Text To Speech

OpenMOSS-Team/MOSS-TTS

18K

412

Text To Speech

mlx-community/Qwen3-TTS-12Hz-0.6B-Base-4bit

18K

9

mlx-audio

Text To Speech

mlx-community/orpheus-3b-0.1-ft-bf16

17K

3

mlx

Text To Speech

myshell-ai/MeloTTS-French

17K

18

transformers

Text To Speech

mlx-community/Qwen3-TTS-12Hz-1.7B-Base-bf16

15K

20

mlx-audio

Text To Speech

wasmdashai/vits-ar-sa-A

15K

2

transformers

Text To Speech

vibevoice/VibeVoice-1.5B

15K

30

transformers

Text To Speech

nicolajreck/csm-1b-danish-tts

14K

3

transformers

Text To Speech

IndexTeam/IndexTTS-2

14K

775

Text To Speech

pevers/parkiet

14K

12

Text To Speech

HumeAI/tada-1b

14K

240

Text To Speech

vibevoice/VibeVoice-7B

13K

205

Text To Speech

mlx-community/Kokoro-82M-bf16

13K

65

mlx

Text To Speech

Audio8/Audio8-TTS-Preview-0.6b

13K

333

transformers

Text To Speech

sbintuitions/sarashina2.2-tts

12K

66

Text To Speech

mudler/magpie-tts.cpp-gguf

12K

......

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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.