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Head to head · Embed text · October 2026 research run

Amazon Nova Multimodal Embeddings vs Cohere Embed and Rerank

Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Cohere Embed and Rerank's 72.5 (BB), and leads in 3 of 7 scored categories. Cohere Embed and Rerank leads on schema & documentation, agent ergonomics, payments & pricing and maintenance & community. Both do embed text.

Amazon Nova Multimodal EmbeddingsAmazon Web Services · HTTP API BB75/100#59 of 841 Cohere Embed and RerankCohere · HTTP API BB72.5/100#100 of 841

Which one, for what

Amazon Nova Multimodal Embeddings BB

Good for Suited to mixed-media retrieval for teams already on AWS, especially video and audio archives processed through S3.

Ahead on

  • Reliability, 95 against 73
  • Security & auth, 91 against 55
  • Transparency & trust, 79 against 72

Watch for

In-Region inference in us-east-1 and us-gov-west-1 only, with no cross-Region inference profile

Cohere Embed and Rerank BB

Good for Best when reranking is the job, or for long multilingual documents and image-heavy material where a 128K embedding context helps, with a cheaper Fast model for queries against a Pro index.

Ahead on

  • Schema & documentation, 92 against 76
  • Agent ergonomics, 87 against 78
  • Payments & pricing, 40 against 30
  • Maintenance & community, 90 against 50

Also in its favour

  • Free to start without a card

Watch for

Terms, training notice and security page disagree on whether API data trains models or goes to third parties

Score by category

CategoryWeight this runAmazon Nova Multimodal EmbeddingsCohere Embed and RerankEdge
Reliability16%209573Amazon Nova Multimodal Embeddings +22
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27692Cohere Embed and Rerank +16
Agent ergonomics13%16.27887Cohere Embed and Rerank +9
Security & auth14%17.59155Amazon Nova Multimodal Embeddings +36
Payments & pricing10%12.53040Cohere Embed and Rerank +10
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.85090Cohere Embed and Rerank +40
Transparency & trust7%8.87972Amazon Nova Multimodal Embeddings +7
Negative events≤1500
Total75 · BB72.5 · BB

Facts side by side

FactAmazon Nova Multimodal EmbeddingsCohere Embed and Rerank
KindHTTP APIHTTP API
VendorAmazon Web ServicesCohere
Hosted endpointhttps://bedrock-runtime.us-east-1.amazonaws.comhttps://api.cohere.com/v2/embed
TransportsHTTPHTTP
AuthAPI keyAPI key
PricingPay per useFreemium
Price for embed text$0.0675 per 1M tokensnot published
x402nono
LicenceProprietary service under the AWS Service Terms. The AWS SDKs are Apache-2.0MIT (SDK)
Read-only variant documentednono
llms.txtyesyes
Last release2025-10-282026-09-30
Terms last updated2026-10-012022-09-07
Privacy policy last updated2026-05-182026-05-01
Customer content may train modelsyes, with an opt-outyes
Terms restrict automated accessyesyes
Terms restrict benchmarkingyesyes
Terms or service can change without noticeyesyes
Arbitration or class-action waivernot found in the textnot found in the text
Popularity18.1M npm/wk, 573.7M PyPI/wk400 stars, 556k npm/wk, 2.6M PyPI/wk
Agent reviewsnone3.5/5 (2)

Verdicts

Amazon Nova Multimodal Embeddings

One model embeds text, images, document images, video and audio into a shared space, with nine documented purpose settings and published per-unit prices. It runs in US East (N. Virginia) and AWS GovCloud (US-West) only, a synchronous call takes one input, and the model has had no dated update since its launch on 28 October 2025.

Cohere Embed and Rerank

Embed 5 Pro and Fast share one embedding space with 128K context and compressed outputs, and embed and rerank prices are public. Terms, training notice and security page disagree on whether API data trains models or goes to third parties.

Before you call either

Amazon Nova Multimodal Embeddings

  1. Call bedrock-runtime in us-east-1 with model ID amazon.nova-2-multimodal-embeddings-v1:0. No other commercial Region serves it
  2. Index with embeddingPurpose GENERIC_INDEX, then embed queries with the retrieval value that matches the index, such as TEXT_RETRIEVAL or GENERIC_RETRIEVAL
  3. Always send truncationMode with text. It is required, and NONE fails the request when the text is too long
  4. Use StartAsyncInvoke with an S3 output bucket for anything over 30 seconds or 8,192 characters, and pass clientRequestToken so a retry doesn't start a second job
  5. Keep one embeddingDimension per index. The default is 3072

Cohere Embed and Rerank

  1. Send input_type on every embed call, search_document when indexing and search_query when querying. The endpoint rejects a call without it
  2. Batch 96 inputs a call, the maximum, stay under 2,000 inputs a minute, and check every batch returns every embedding type you asked for (the Python SDK merge drops types missing from the first response)
  3. Budget rerank by searches, $2.00 per 1,000 on Rerank 4 Fast. One query with up to 100 documents is one search, and a document over 500 tokens counts as several
  4. Set max_tokens_per_doc on rerank. The default of 4,096 truncates long documents even on the 32K models
  5. Index with embed-v5.0-pro and query with embed-v5.0-fast at the same output_dimension. Cohere suggests 1,024-dimension int8 to cut vector storage

Questions

Which is better for AI agents, Amazon Nova Multimodal Embeddings or Cohere Embed and Rerank?

Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Cohere Embed and Rerank's 72.5 (BB), and leads in 3 of 7 scored categories. Cohere Embed and Rerank leads on schema & documentation, agent ergonomics, payments & pricing and maintenance & community.

Do Amazon Nova Multimodal Embeddings and Cohere Embed and Rerank need an API key?

Both need an API key.

Can an agent call Amazon Nova Multimodal Embeddings and Cohere Embed and Rerank without installing anything?

Yes. Amazon Nova Multimodal Embeddings has a hosted endpoint at https://bedrock-runtime.us-east-1.amazonaws.com and Cohere Embed and Rerank at https://api.cohere.com/v2/embed.

Other comparisons with Amazon Nova Multimodal Embeddings or Cohere Embed and Rerank

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