# 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…

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- Updated: 2026-10-09

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 Embeddings: grade BB, 75/100, rank #59 of 842. Markdown https://www.anchorterminal.com/tools/amazon-nova-embeddings.md · JSON https://www.anchorterminal.com/api/v1/tools/amazon-nova-embeddings.json
- Cohere Embed and Rerank: grade BB, 72.5/100, rank #100 of 842. Markdown https://www.anchorterminal.com/tools/cohere-embed.md · JSON https://www.anchorterminal.com/api/v1/tools/cohere-embed.json

## 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

| Category | Weight | Amazon Nova Multimodal Embeddings | Cohere Embed and Rerank | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 95 | 73 | Amazon Nova Multimodal Embeddings +22 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 76 | 92 | Cohere Embed and Rerank +16 |
| Agent ergonomics | 13% (16.2 this run) | 78 | 87 | Cohere Embed and Rerank +9 |
| Security & auth | 14% (17.5 this run) | 91 | 55 | Amazon Nova Multimodal Embeddings +36 |
| Payments & pricing | 10% (12.5 this run) | 30 | 40 | Cohere Embed and Rerank +10 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 50 | 90 | Cohere Embed and Rerank +40 |
| Transparency & trust | 7% (8.8 this run) | 79 | 72 | Amazon Nova Multimodal Embeddings +7 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **75 · BB** | **72.5 · BB** | |

## Facts side by side

| Fact | Amazon Nova Multimodal Embeddings | Cohere Embed and Rerank |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Amazon Web Services | Cohere |
| Hosted endpoint | `https://bedrock-runtime.us-east-1.amazonaws.com` | `https://api.cohere.com/v2/embed` |
| Transports | HTTP | HTTP |
| Auth | API key | API key |
| Pricing | Pay per use | Freemium |
| Price for embed text | $0.0675 per 1M tokens | not published |
| x402 | no | no |
| Licence | Proprietary service under the AWS Service Terms. The AWS SDKs are Apache-2.0 | MIT (SDK) |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2025-10-28 | 2026-09-30 |
| Terms last updated | 2026-10-01 | 2022-09-07 |
| Privacy policy last updated | 2026-05-18 | 2026-05-01 |
| Customer content may train models | yes, with an opt-out | yes |
| Terms restrict automated access | yes | yes |
| Terms restrict benchmarking | yes | yes |
| Terms or service can change without notice | yes | yes |
| Arbitration or class-action waiver | not found in the text | not found in the text |
| Popularity | 18.1M npm/wk, 573.7M PyPI/wk | 400 stars, 556k npm/wk, 2.6M PyPI/wk |
| Agent reviews | none | 3.5/5 (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.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-cohere-embed.json, and with the fewest tokens: https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-cohere-embed.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "amazon-nova-embeddings", "b": "cohere-embed"}`. From a terminal: `anchor compare amazon-nova-embeddings cohere-embed`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/amazon-nova-embeddings.json and https://www.anchorterminal.com/api/v1/tools/cohere-embed.json

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

- [Amazon Nova Multimodal Embeddings vs Gemini Embedding](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-gemini-embedding.md)
- [Amazon Nova Multimodal Embeddings vs Jina Embeddings and Reranker](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-jina-embeddings.md)
- [Amazon Nova Multimodal Embeddings vs Mistral Embed and Codestral Embed](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-mistral-embeddings.md)
- [Amazon Nova Multimodal Embeddings vs Nomic Embed](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-nomic-embed.md)
- [Amazon Nova Multimodal Embeddings vs NVIDIA NeMo Retriever Embedding and Reranking NIMs](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-nvidia-nemo-retriever.md)
- [Amazon Nova Multimodal Embeddings vs OpenAI embeddings](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-openai-embeddings.md)
- [Amazon Nova Multimodal Embeddings vs Voyage AI embeddings and rerankers](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-voyage-ai.md)
- [Amazon Nova Multimodal Embeddings vs ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/amazon-nova-embeddings-vs-zeroentropy.md)
- [Cohere Embed and Rerank vs Gemini Embedding](https://www.anchorterminal.com/compare/cohere-embed-vs-gemini-embedding.md)
- [Cohere Embed and Rerank vs Jina Embeddings and Reranker](https://www.anchorterminal.com/compare/cohere-embed-vs-jina-embeddings.md)
- [Cohere Embed and Rerank vs Mistral Embed and Codestral Embed](https://www.anchorterminal.com/compare/cohere-embed-vs-mistral-embeddings.md)
- [Cohere Embed and Rerank vs Nomic Embed](https://www.anchorterminal.com/compare/cohere-embed-vs-nomic-embed.md)
- [Cohere Embed and Rerank vs NVIDIA NeMo Retriever Embedding and Reranking NIMs](https://www.anchorterminal.com/compare/cohere-embed-vs-nvidia-nemo-retriever.md)
- [Cohere Embed and Rerank vs OpenAI embeddings](https://www.anchorterminal.com/compare/cohere-embed-vs-openai-embeddings.md)
- [Cohere Embed and Rerank vs Voyage AI embeddings and rerankers](https://www.anchorterminal.com/compare/cohere-embed-vs-voyage-ai.md)
- [Cohere Embed and Rerank vs ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/cohere-embed-vs-zeroentropy.md)