Best Platforms for Multimodal Embedding Search in 2026
The short answer
Pick the platform by your dominant media type. “Multimodal” covers very different workloads: hours of video, product photos with captions, scanned documents, voice notes. As of October 26, 2026:
- TwelveLabs Marengo 3.5 — best for video and audio search.
- Gemini Embedding 2 — best general-purpose multimodal API (text, image, audio, video, PDF).
- Cohere Embed 5 — best for enterprise text-and-image search and cheapest text tokens.
- EmbeddingGemma 2 — best open model, and the only one here built to run on the device.
If your corpus is mainly PDFs searched as page images, start with our visual document retrieval comparison instead.
The comparison
| Platform | Modalities | Price (per 1M tokens, Oct 26, 2026) | Deploy | Best for |
|---|---|---|---|---|
| TwelveLabs Marengo 3.5 | Video, audio, image, text, documents | Video $0.260 · audio $0.065 · image $0.080 · document $0.162 · text $0.200; plans from $0 / $29 / $99 a month | Managed API | Video libraries, media, security footage |
| Gemini Embedding 2 | Text, image, audio, video, PDF | Text $0.20 · image $0.45 · audio $6.50 · video $12.00; batch 50% off; free tier | Gemini API | One API for everything |
| Cohere Embed 5 (Pro / Fast) | Text, image, fused text+image | Text $0.12 Pro / $0.08 Fast · images $0.40 | Cohere API, Model Vault, Microsoft Foundry, SageMaker | Enterprise search, 100+ languages |
| EmbeddingGemma 2 | Text, code, image, video frames, audio | Free (open weights) | On-device or self-host | Private, offline search |
Prices from the Gemini API pricing page, Cohere’s Embed 5 launch post and TwelveLabs’ Marengo 3.5 announcement and pricing page.
1. TwelveLabs Marengo 3.5 — best for video
TwelveLabs launched Marengo 3.5 on August 31, 2026 as a video-native embedding model covering video, audio, images, text and documents in one space. It supports composed queries (an image plus text, for example), time-aligned business metadata, an uncertainty signal for low-confidence results and long-form ingestion with no four-hour cap. On TwelveLabs’ own eight-group benchmark aggregate it scores 67.38 at 512 dimensions against 62.35 for Gemini Embedding 2 and 50.34 for Amazon Nova Multimodal Embeddings at 3,072 dimensions — a vendor benchmark, but the smaller vectors also cut index storage. Pricing moved to per-modality tokens: video $0.26 per million, audio $0.065, image $0.08, document $0.162, text $0.20. Plans run Free, Plus ($29/month) and Pro ($99/month, with overage).
2. Gemini Embedding 2 — best general-purpose API
gemini-embedding-2 is Google’s first multimodal embedding model, mapping text, images, video, audio and PDFs into one space. Paid-tier prices: $0.20 per million text tokens, $0.45 image ($0.00012 per image), $6.50 audio ($0.00016 per second) and $12 video ($0.00079 per frame); Batch halves all of them. The free tier exists but Google may use free-tier data to improve its products. Choose it when you want one vendor for mixed media and already use the Gemini API; budget carefully for video, where it is the most expensive option here.
3. Cohere Embed 5 — best for enterprise text and images
Cohere released Embed 5 on September 30, 2026 in two sizes that share one embedding space: Pro at $0.12 and Fast at $0.08 per million text tokens, with image tokens at $0.40. The shared space allows a useful trick: index with Pro, query with Fast. It accepts text, images or fused text-plus-image inputs, a 128K-token context and more than 100 languages, and runs on the Cohere API, private Model Vault deployments, Microsoft Foundry and Amazon SageMaker — the deployment breadth enterprises with data-residency rules need. Pair it with a reranker; see best reranker models.
4. EmbeddingGemma 2 — best open and on-device
Google DeepMind’s EmbeddingGemma 2 (October 6, 2026) is a 740M-parameter open-weight model that maps text, images, video frames and audio into one space, with modular encoders so you load only what you need: about 191 MB of active RAM text-only and 567 MB for the full multimodal model on a Pixel 11 Pro. Google demonstrates it in the AI Edge Gallery app for search-as-you-type over a phone’s photo library and says it will come to Android through ML Kit. Choose it when media must not leave the device, or when you want zero per-query cost on your own GPUs.
Search performance is not only the model
- Dimensions drive cost. A 3,072-dimension vector takes six times the storage and memory of a 512-dimension one; Matryoshka-style truncation, where offered, trades a little recall for a lot of index cost.
- Benchmark on your queries. Write 50 real queries with known answers and measure recall@10 for each candidate before you migrate.
- Re-embedding is a migration. Changing models means re-embedding the whole corpus, so price that in.
How to choose
- Mostly video or audio: Marengo 3.5.
- Mixed media, one vendor, Google stack: Gemini Embedding 2.
- Text and images, enterprise deployment options: Cohere Embed 5.
- On-device or no per-query fees: EmbeddingGemma 2.
Last verified: October 26, 2026.