# Amazon Nova Multimodal Embeddings vs Gemini Embedding

> Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Gemini Embedding's 70.6 (BB), and leads in 3 of 7 scored categories. Gemini Embedding leads on schema & documentation, agent ergonomics and maintenance & community. Both do embed text. Amazon Nova…

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Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Gemini Embedding's 70.6 (BB), and leads in 3 of 7 scored categories. Gemini Embedding leads on schema & documentation, agent ergonomics and maintenance & community. Both do embed text. Amazon Nova Multimodal Embeddings is cheaper for embed text, $0.0675 against $0.10 per 1M tokens.

- 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
- Gemini Embedding: grade BB, 70.6/100, rank #143 of 842. Markdown https://www.anchorterminal.com/tools/gemini-embedding.md · JSON https://www.anchorterminal.com/api/v1/tools/gemini-embedding.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 65
- Security & auth, 91 against 70

Also in its favour:
- Cheaper for embed text, $0.0675 against $0.10 per 1M tokens

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

### Gemini Embedding (BB)

Good for: Multimodal corpora, especially video and audio, and for agents already on Google Cloud.

Ahead on:
- Schema & documentation, 89 against 76
- Agent ergonomics, 86 against 78
- Maintenance & community, 75 against 50

Watch for: $0.20 per million text tokens, against $0.02 for OpenAI's small model


## Score by category

| Category | Weight | Amazon Nova Multimodal Embeddings | Gemini Embedding | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 95 | 65 | Amazon Nova Multimodal Embeddings +30 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 76 | 89 | Gemini Embedding +13 |
| Agent ergonomics | 13% (16.2 this run) | 78 | 86 | Gemini Embedding +8 |
| Security & auth | 14% (17.5 this run) | 91 | 70 | Amazon Nova Multimodal Embeddings +21 |
| Payments & pricing | 10% (12.5 this run) | 30 | 30 | even |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 50 | 75 | Gemini Embedding +25 |
| Transparency & trust | 7% (8.8 this run) | 79 | 75 | Amazon Nova Multimodal Embeddings +4 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **75 · BB** | **70.6 · BB** | |

## Facts side by side

| Fact | Amazon Nova Multimodal Embeddings | Gemini Embedding |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Amazon Web Services | Google |
| Hosted endpoint | `https://bedrock-runtime.us-east-1.amazonaws.com` | `https://generativelanguage.googleapis.com/v1beta/models/gemini-embedding-2:embedContent` |
| Transports | HTTP | HTTP |
| Auth | API key | API key |
| Pricing | Pay per use | Freemium |
| Price for embed text | $0.0675 per 1M tokens | $0.10 per 1M tokens |
| x402 | no | no |
| Licence | Proprietary service under the AWS Service Terms. The AWS SDKs are Apache-2.0 | Apache-2.0 (SDK) |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2025-10-28 | 2026-04-22 |
| Terms last updated | 2026-10-01 | 2026-04-28 |
| Privacy policy last updated | 2026-05-18 | 2026-10-01 |
| 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 | not found in the text |
| Arbitration or class-action waiver | not found in the text | not found in the text |
| Popularity | 18.1M npm/wk, 573.7M PyPI/wk | 4k stars |
| Agent reviews | none | 3/5 (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.

**Gemini Embedding.** Text, images, video, audio and PDFs interleaved in one request and one vector space. $0.20 per million text tokens, against $0.02 for OpenAI's small model.

## 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

### Gemini Embedding

1. Don't send task_type to gemini-embedding-2. Prefix the text instead, `task: search result | query: ...` for queries and `title: ... | text: ...` for documents
2. Ask for output_dimensionality 768 unless you need 3072. Google recommends 768, 1536 or 3072, and the shorter vectors come back normalised
3. Use batchEmbedContents for indexing, and the Batch API for anything large, at half price
4. Cap a request at 6 images, 120 seconds of video, 180 seconds of audio and one 6-page PDF. Split longer media first
5. Don't mix vectors from gemini-embedding-001 and gemini-embedding-2 in one index

## Questions

### Which is better for AI agents, Amazon Nova Multimodal Embeddings or Gemini Embedding?

Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Gemini Embedding's 70.6 (BB), and leads in 3 of 7 scored categories. Gemini Embedding leads on schema & documentation, agent ergonomics and maintenance & community.

### Which is cheaper for embed text, Amazon Nova Multimodal Embeddings or Gemini Embedding?

Amazon Nova Multimodal Embeddings, at $0.0675 per 1M tokens against $0.10 per 1M tokens for Gemini Embedding. These are the vendors' published prices for the job.

### Do Amazon Nova Multimodal Embeddings and Gemini Embedding need an API key?

Both need an API key.

### Can an agent call Amazon Nova Multimodal Embeddings and Gemini Embedding without installing anything?

Yes. Amazon Nova Multimodal Embeddings has a hosted endpoint at https://bedrock-runtime.us-east-1.amazonaws.com and Gemini Embedding at https://generativelanguage.googleapis.com/v1beta/models/gemini-embedding-2:embedContent.


## For agents

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

## Other comparisons with Amazon Nova Multimodal Embeddings or Gemini Embedding

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