Mixpeek vs Twelve Labs
A detailed look at how Mixpeek compares to Twelve Labs.
Mixpeek
Twelve LabsKey Differentiators
Why Teams Choose Mixpeek Over Twelve Labs
- Broader Multimodal Support: video + audio + image + PDF + text indexed and searched together
- Your Storage, Indexed: connect the S3/GCS buckets you already have; content stays in your storage
- Features as Data: faces, on-screen text, transcripts, objects, and scenes become queryable fields, not one-off JSON
- Transparent Unit Pricing: video $0.05/min, audio $0.01/min, images $1.50/1K, plans from $25/mo
- Discovered Structure: clustering and taxonomies organize the library and feed relevance back
- Single-Tenant Option: dedicated, isolated data plane in your chosen cloud and region for enterprise
Where Twelve Labs Excels
- Proprietary Marengo and Pegasus models are best-in-class for video understanding and generation tasks.
- Deep specialization in video AI with models trained specifically for temporal and visual reasoning.
- Quick cloud setup: simple API with no infrastructure management required to get started.
- Strong developer experience with clean SDKs and comprehensive video-specific documentation.
- Video-first features including action recognition, object tracking, and scene-level understanding.
- Purpose-built for video search and summarization use cases with high out-of-the-box accuracy.
TL;DR: Twelve Labs is the best pure video-understanding API: video-native Marengo and Pegasus models with minimal setup. Mixpeek is the better fit when video is part of a mixed corpus (documents, images, audio), when you want the extracted signals (scenes, transcripts, on-screen text, faces, objects) indexed and searchable together over your own object storage, or when you want transparent per-unit pricing (video $0.05/min, plans from $25/mo). Many teams even combine them: generate Marengo embeddings with Twelve Labs and store, filter, and search them in Mixpeek MVS.
Mixpeek vs. Twelve Labs
💰 Pricing & Cost Comparison
| Feature / Dimension | Mixpeek | Twelve Labs |
|---|---|---|
| Pricing Model | Flat plan + per-unit usage: video $0.05/min, audio $0.01/min, images $1.50/1K, documents per page; each extra search feature metered on the same unit | Multi-meter usage: indexing, API minutes, output tokens, storage |
| Entry Price | MVS standalone from $25/mo; Managed Build $25/mo + usage | Free plan (3 GB storage); Plus $29/mo, Pro $99/mo, then overage |
| Cost Predictability | ✅ Preflight estimate endpoint quotes any batch before you submit; pay only for features you enable | ⚠️ Multiple meters (indexing, search, generation) make large-library costs harder to forecast |
| Storage Cost | Vectors at $1.56 per 1M a month plus $0.023/GB-month; originals stay in your own S3/GCS at your storage rates | Video hosted in Twelve Labs cloud, storage metered |
| Enterprise Pricing | Custom, with single-tenant deployment option | Custom, negotiated API rates |
🔒 Deployment & Compliance
| Feature / Dimension | Mixpeek | Twelve Labs |
|---|---|---|
| Deployment Options | Managed cloud; single-tenant (dedicated, isolated data plane) for enterprise | Cloud API only |
| Where Content Lives | ✅ Your own object storage (S3/GCS): Mixpeek indexes it in place | 🚫 Video uploaded to and hosted in Twelve Labs cloud |
| Data Residency | ✅ Single-tenant deploys in your chosen cloud and region; data stays in-region | ⚠️ Processed in Twelve Labs regions |
| Tenant Isolation | ✅ Single-tenant: dedicated database, compute cluster, vector shard, and bucket | Shared multi-tenant cloud |
| Compliance Posture | Isolation + in-your-storage indexing simplify GDPR/data-sovereignty reviews | ⚠️ Third-party processing requires DPA review |
🧠 Vision & Positioning
| Feature / Dimension | Mixpeek | Twelve Labs |
|---|---|---|
| Core Pitch | Turn raw multimodal media into structured, searchable intelligence with flexible deployment | Foundation models for video understanding via cloud API |
| Primary Users | Developers, ML teams, solutions engineers, compliance-focused enterprises | Developers building video-centric applications |
| Approach | API-first, service-enabled AI pipelines with deployment flexibility | API-first, specialized video AI models (cloud-only) |
| Deployment Focus | Managed cloud over your object storage; single-tenant for enterprise | API-first, specialized video AI models (cloud-only) |
| Target Market | Healthcare, finance, government, enterprise, startups needing control | SaaS companies, media companies, general video apps |
🔍 Tech Stack & Product Surface
| Feature / Dimension | Mixpeek | Twelve Labs |
|---|---|---|
| Supported Modalities | Video (frame + scene-level), audio, PDFs, images, text | Primarily Video; extracts text, speech, objects from video |
| Multimodal Fusion | ✅ Cross-modal search (find videos by image, audio by text) | 🚫 Video-only, no cross-modal capabilities |
| Custom Pipelines | ✅ Pluggable extractors, retrievers, indexers | 🚫 Fixed video processing pipeline |
| Retrieval | ✅ Staged retriever pipelines: metadata filters, multimodal feature search, reranking; BYO embeddings via MVS | Proprietary multimodal embeddings for video search |
| Automation | ✅ Bucket syncs, triggers, alerts, and webhooks index new content as it lands in storage | Async processing for uploaded videos |
| Structure Discovery | ✅ Clustering across feature spaces; clusters promote to navigable taxonomies | Classification against user-defined classes |
| Developer Surface | ✅ Python + JavaScript SDKs, MCP server and function-calling integrations for agents | Client SDKs (Python, JS) for their API |
| Model Choice | ✅ Model-agnostic pipelines: pick extractors per collection, swap models as they improve | 🚫 Fixed to Twelve Labs foundation models |
⚙️ Use Cases & Capabilities
| Feature / Dimension | Mixpeek | Twelve Labs |
|---|---|---|
| General Multimodal Search | ✅ Across video, audio, image, PDF, text | 🚫 Video-only |
| Video Content Moderation | ✅ NSFW/safety extractors in customizable pipelines | ✅ Strong capability (cloud-based) |
| Video Ad Targeting/Analytics | ✅ Scene/object/audio data with custom logic | ✅ Core use case for video intelligence |
| Compliance-Heavy Industries | ✅ Single-tenant isolation for healthcare, finance, government | ⚠️ Cloud processing may not meet requirements |
| Image/PDF/Audio Search | ✅ Fully supported | 🚫 Not supported |
| Custom Internal Tooling | ✅ Composable APIs: buckets, collections, retrievers, taxonomies | ⚠️ Limited to video tasks via cloud API |
| Agent Integrations | ✅ MCP server, OpenAI function calling, LangChain | ⚠️ API + SDKs; no MCP surface documented |
🚀 Migration & Integration
| Feature / Dimension | Mixpeek | Twelve Labs |
|---|---|---|
| API Compatibility | Custom API design or compatible endpoints | Twelve Labs API |
| Migration Difficulty | Medium - typically 1-2 weeks with support | N/A |
| Data Export | ✅ Export all embeddings, metadata, and features | ⚠️ Check data portability options |
| Parallel Running | ✅ Can run both systems during migration | N/A |
| Migration Support | ✅ Solutions team assists with mapping and migration | Developer support available |
| Typical Migration Time | 1-2 weeks for most teams | N/A |
📈 Business Strategy & Support
| Feature / Dimension | Mixpeek | Twelve Labs |
|---|---|---|
| GTM | SA-led land-and-expand + dev-first motion | Developer-first, API-driven adoption |
| Service Layer | ✅ Solutions team builds pipelines and templates | Developer support, documentation |
| Monetization Model | Self-serve plans ($25/$250/mo) + per-unit usage; enterprise single-tenant contracts | Usage-based API calls, tiered plans |
| SLA & Support | Custom SLAs on enterprise single-tenant, email support on all plans | SLA based on plan tier |
| Customer Feedback Loop | Bespoke deployments inform core product | Developer community, direct API user feedback |
| Community/Open Source | ✅ SDK + app ecosystem via mxp.co/apps | Active developer community, some open tools/examples |
🎯 When to Choose Which
| Feature / Dimension | Mixpeek | Twelve Labs |
|---|---|---|
| Choose Mixpeek | ✅ Mixed corpus (video + documents + images + audio) • Content already lives in S3/GCS • Extracted features (faces, OCR, transcripts) must be queryable together • Transparent per-unit pricing • Data residency or tenant isolation requirements | 🚫 Not ideal for these needs |
| Choose Twelve Labs | 🚫 Not ideal for these needs | ✅ Video-only use case • Best out-of-the-box video foundation models • Video-to-text generation (Pegasus) • Quick cloud setup preferred |
| Migration Triggers | Teams add or switch to Mixpeek when: multi-meter costs become hard to forecast • non-video content needs the same search • features must land in their own storage and schema • agents need MCP access to the index | N/A |
🏆 Bottom Line: Mixpeek vs. Twelve Labs
| Feature / Dimension | Mixpeek | Twelve Labs |
|---|---|---|
| Best for | Multimodal search over your own object storage, features as queryable data, agents | Best out-of-the-box video-native models, video-only apps |
| Deployment | Managed cloud or enterprise single-tenant (your cloud, your region) | Cloud-only |
| Modalities | Video + Audio + Image + PDF + Text | Video-only |
| Cost Model | Plans from $25/mo + transparent per-unit usage (video $0.05/min) | Multi-meter usage-based |
| Where Content Lives | ✅ Your S3/GCS buckets, indexed in place | Uploaded to Twelve Labs cloud |
| Migration Path | ✅ 1-2 week migration with solutions team support; MVS stores existing embeddings as-is | N/A |
| When to Switch | When you need: mixed modalities • search over your own storage • queryable features • predictable per-unit pricing | When you want: strongest video foundation models • video-to-text generation • quick setup |
Frequently Asked Questions: Twelve Labs vs AWS vs Mixpeek for contextual advertising
Twelve Labs vs AWS for contextual advertising: which should I use?
For most teams they are partners, so the choice is which video model reads the scenes. Twelve Labs' Marengo and Pegasus models run inside Amazon Bedrock, next to AWS's own building blocks: Rekognition Video labels objects and scenes and runs content moderation at $0.10 per stored minute each (AWS Rekognition pricing, us-east-1), and Elemental MediaTailor inserts the ads and can pass contextual signals with each ad request. Pick Twelve Labs when you need scene-level meaning such as tone, dialogue and actions. Pick Rekognition when object and moderation labels are enough. Either way you still need a step that maps each scene to IAB Content Taxonomy 3.1 categories and an index your ad decisioning can query, which is the part Mixpeek does.
Can I use Twelve Labs models on AWS?
Yes. Amazon Bedrock offers four TwelveLabs models: Marengo Embed 2.7 and 3.0 for embeddings, and Pegasus 1.2 and 1.5 for video-to-text analysis. Per AWS's Bedrock documentation, Marengo Embed 3.0 returns 512-dimension embeddings (down from 1,024 in earlier versions), takes up to 4 hours of video or audio in a file of up to 6 GB, covers 36 languages, and runs video through the asynchronous StartAsyncInvoke call. Both Pegasus models answer through InvokeModel, with a streaming variant. The Marengo Embed 3.0 model ID is twelvelabs.marengo-embed-3-0-v1:0.
What does Mixpeek add to Twelve Labs or AWS for contextual advertising?
Mixpeek reads your files where they already live, in S3, GCS or any bucket, and turns what's in them into data your software can search, classify and moderate. For contextual advertising that means each scene's transcript, on-screen text, objects and faces become filterable fields, and each scene is classified against the 704 categories of IAB Content Taxonomy 3.1. On IAB Tech Lab's open classification benchmark (704 pages, one per category), Mixpeek's IAB 3.1 text retriever put the correct category first on 512 pages and in its top five on 660; the method and per-page results are in the Mixpeek guide 'IAB Content Taxonomy classification benchmark'. If you already generate Marengo embeddings, you can store, filter and search them in Mixpeek MVS.
How much does video analysis cost on Twelve Labs, AWS and Mixpeek?
AWS Rekognition Video lists $0.10 per minute for label detection, $0.10 per minute for content moderation and $0.05 per minute for shot detection on stored video in us-east-1. Twelve Labs lists a free plan with 3 GB of storage, Plus at $29 a month and Pro at $99 a month, with usage beyond the plan billed as overage on a separate page. Mixpeek charges $0.05 per minute of video and $0.01 per minute of audio, with plans from $25 a month, and its preflight estimate quotes a batch before you submit it.
Where does my video live with Twelve Labs, AWS and Mixpeek?
With the Twelve Labs API you upload video into a Twelve Labs index. On Amazon Bedrock, Marengo's asynchronous calls read from and write to S3 in your AWS account. Mixpeek indexes the objects in your own S3 or GCS bucket in place, and its enterprise single-tenant option runs a dedicated data plane in the cloud and region you choose.
Can Mixpeek replace Twelve Labs for video AI?
For search, classification and moderation over a mixed library, usually yes: Mixpeek indexes video at the scene level alongside audio, images, PDFs and text, and its extractors can be swapped per collection. Twelve Labs remains the stronger pick when you want its own video-language models, Marengo for embeddings and Pegasus for generated scene descriptions, with no pipeline to configure. Many teams combine the two.
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