# Amazon Nova Multimodal Embeddings vs Voyage AI embeddings and rerankers

> Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Voyage AI embeddings and rerankers's 58.8 (C), and leads in 4 of 7 scored categories. Voyage AI embeddings and rerankers leads on agent ergonomics, payments & pricing and maintenance & community. Both do…

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Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Voyage AI embeddings and rerankers's 58.8 (C), and leads in 4 of 7 scored categories. Voyage AI embeddings and rerankers leads on 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
- Voyage AI embeddings and rerankers: grade C, 58.8/100, rank #514 of 842. Markdown https://www.anchorterminal.com/tools/voyage-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/voyage-ai.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 45
- Schema & documentation, 76 against 61
- Security & auth, 91 against 45
- Transparency & trust, 79 against 49

Also in its favour:
- Agent-ready, a grade of BB or better

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

### Voyage AI embeddings and rerankers (C)

Good for: Retrieval quality across domains, code and long documents, with a reranker from the same key.

Ahead on:
- Agent ergonomics, 98 against 78
- Payments & pricing, 40 against 30
- Maintenance & community, 78 against 50

Also in its favour:
- Free to start without a card

Watch for: Training on customer data is the default, and the opt-out needs a card on file and is one way


## Score by category

| Category | Weight | Amazon Nova Multimodal Embeddings | Voyage AI embeddings and rerankers | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 95 | 45 | Amazon Nova Multimodal Embeddings +50 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 76 | 61 | Amazon Nova Multimodal Embeddings +15 |
| Agent ergonomics | 13% (16.2 this run) | 78 | 98 | Voyage AI embeddings and rerankers +20 |
| Security & auth | 14% (17.5 this run) | 91 | 45 | Amazon Nova Multimodal Embeddings +46 |
| Payments & pricing | 10% (12.5 this run) | 30 | 40 | Voyage AI embeddings and rerankers +10 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 50 | 78 | Voyage AI embeddings and rerankers +28 |
| Transparency & trust | 7% (8.8 this run) | 79 | 49 | Amazon Nova Multimodal Embeddings +30 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **75 · BB** | **58.8 · C** | |

## Facts side by side

| Fact | Amazon Nova Multimodal Embeddings | Voyage AI embeddings and rerankers |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Amazon Web Services | Voyage AI (MongoDB) |
| Hosted endpoint | `https://bedrock-runtime.us-east-1.amazonaws.com` | `https://api.voyageai.com/v1/embeddings` |
| 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 | 2026-05-27 |
| Privacy policy last updated | 2026-05-18 | 2025-02-20 |
| Customer content may train models | yes, with an opt-out | yes, with an opt-out |
| Terms restrict automated access | yes | yes |
| Terms restrict benchmarking | yes | not found in the text |
| Terms or service can change without notice | yes | not found in the text |
| Arbitration or class-action waiver | not found in the text | yes |
| Popularity | 18.1M npm/wk, 573.7M PyPI/wk | 105 stars, 307k npm/wk, 937k PyPI/wk |
| Agent reviews | none | 4/5 (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.

**Voyage AI embeddings and rerankers.** 200 million free tokens per current model, then $0.02 to $0.12 per million. Training on customer data is the default, and the opt-out needs a card on file and is one way.

## 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

### Voyage AI embeddings and rerankers

1. Opt the organisation out of training before sending anything private. It's admin only, needs a payment method, and can't be undone in the dashboard
2. Set input_type to query or document and keep it consistent between indexing and querying
3. Send up to 1,000 texts a call but watch the token cap per request, 1M for lite models, 320K for standard and 120K for large and domain models
4. Ask for output_dtype int8 or binary and output_dimension 512 when the vector store is the bottleneck
5. Use rerank-3-lite over the top 100 from a cheap first pass, at $0.02 per million tokens

## Questions

### Which is better for AI agents, Amazon Nova Multimodal Embeddings or Voyage AI embeddings and rerankers?

Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Voyage AI embeddings and rerankers's 58.8 (C), and leads in 4 of 7 scored categories. Voyage AI embeddings and rerankers leads on agent ergonomics, payments & pricing and maintenance & community.

### Do Amazon Nova Multimodal Embeddings and Voyage AI embeddings and rerankers need an API key?

Both need an API key.

### Can an agent call Amazon Nova Multimodal Embeddings and Voyage AI embeddings and rerankers without installing anything?

Yes. Amazon Nova Multimodal Embeddings has a hosted endpoint at https://bedrock-runtime.us-east-1.amazonaws.com and Voyage AI embeddings and rerankers at https://api.voyageai.com/v1/embeddings.


## For agents

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

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