# Amazon Nova Multimodal Embeddings vs NVIDIA NeMo Retriever Embedding and Reranking NIMs

> Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against NVIDIA NeMo Retriever Embedding and Reranking NIMs's 61 (C), and leads in 4 of 7 scored categories. NVIDIA NeMo Retriever Embedding and Reranking NIMs leads on payments & pricing and maintenance &…

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- Updated: 2026-10-09

Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against NVIDIA NeMo Retriever Embedding and Reranking NIMs's 61 (C), and leads in 4 of 7 scored categories. NVIDIA NeMo Retriever Embedding and Reranking NIMs leads on 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
- NVIDIA NeMo Retriever Embedding and Reranking NIMs: grade C, 61/100, rank #439 of 842. Markdown https://www.anchorterminal.com/tools/nvidia-nemo-retriever.md · JSON https://www.anchorterminal.com/api/v1/tools/nvidia-nemo-retriever.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 53
- Agent ergonomics, 78 against 73
- Security & auth, 91 against 55
- Transparency & trust, 79 against 71

Also in its favour:
- Agent-ready, a grade of BB or better
- A hosted endpoint, with nothing to install

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

### NVIDIA NeMo Retriever Embedding and Reranking NIMs (C)

Good for: Teams that already run NVIDIA GPUs and need embedding and reranking inside their own network, including page-image retrieval with the VL models.

Ahead on:
- Payments & pricing, 40 against 30
- Maintenance & community, 57 against 50

Also in its favour:
- No key needed to call it

Watch for: The API has no authentication and no rate limiting. The security page leaves both to a proxy the deployer runs


## Score by category

| Category | Weight | Amazon Nova Multimodal Embeddings | NVIDIA NeMo Retriever Embedding and Reranking NIMs | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 95 | 53 | Amazon Nova Multimodal Embeddings +42 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 76 | 78 | NVIDIA NeMo Retriever Embedding and Reranking NIMs +2 |
| Agent ergonomics | 13% (16.2 this run) | 78 | 73 | Amazon Nova Multimodal Embeddings +5 |
| Security & auth | 14% (17.5 this run) | 91 | 55 | Amazon Nova Multimodal Embeddings +36 |
| Payments & pricing | 10% (12.5 this run) | 30 | 40 | NVIDIA NeMo Retriever Embedding and Reranking NIMs +10 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 50 | 57 | NVIDIA NeMo Retriever Embedding and Reranking NIMs +7 |
| Transparency & trust | 7% (8.8 this run) | 79 | 71 | Amazon Nova Multimodal Embeddings +8 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **75 · BB** | **61 · C** | |

## Facts side by side

| Fact | Amazon Nova Multimodal Embeddings | NVIDIA NeMo Retriever Embedding and Reranking NIMs |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Amazon Web Services | NVIDIA |
| Hosted endpoint | `https://bedrock-runtime.us-east-1.amazonaws.com` | no (local only) |
| Transports | HTTP | HTTP |
| Auth | API key | None |
| 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 | Proprietary containers under the NVIDIA Software Licence Agreement and Product-Specific Terms for AI Products. Models carry their own licences, such as OpenMDW 1.1 for `nvidia/nemotron-3-embed-1b` and the NVIDIA Open Model Licence for the Llama Nemotron models |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2025-10-28 | 2026-08-05 |
| Terms last updated | 2026-10-01 | 2026-05-07 |
| Privacy policy last updated | 2026-05-18 | no date given |
| Customer content may train models | yes, with an opt-out | not found in the text |
| Terms restrict automated access | yes | not found in the text |
| 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 | 134k PyPI/wk |

## 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.

**NVIDIA NeMo Retriever Embedding and Reranking NIMs.** Self-hosted containers with OpenAPI 3.1 files, typed request fields, five embedding output types and a dated end-of-life list. The API has no authentication or rate limiting of its own, production use needs an NVIDIA AI Enterprise licence at $4,500 a GPU a year, and the release notes carry no dates.

## 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

### NVIDIA NeMo Retriever Embedding and Reranking NIMs

1. Send `input_type` as `query` or `passage` on every embedding call. Asymmetric models return HTTP 400 without it, and the wrong value lowers retrieval accuracy per the docs
2. Do not send `dimensions` and `embedding_type` together, and send only 2048 or nothing for `dimensions` on `nvidia/nemotron-3-embed-1b`
3. Poll `/v1/health/ready` before the first call. The Docker health check can report unhealthy while the NIM is ready, per the 2.3 known issues
4. Check the image tag on NGC before pulling. The guide uses `nemotron-3-embed-1b:2.3`, and NGC's record for that image listed tags up to 2.2.2 on 8 October 2026
5. Put a proxy with authentication and TLS in front of port 8000, and sort `/v1/ranking` results yourself as the request has no top-n field

## Questions

### Which is better for AI agents, Amazon Nova Multimodal Embeddings or NVIDIA NeMo Retriever Embedding and Reranking NIMs?

Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against NVIDIA NeMo Retriever Embedding and Reranking NIMs's 61 (C), and leads in 4 of 7 scored categories. NVIDIA NeMo Retriever Embedding and Reranking NIMs leads on payments & pricing and maintenance & community.

### Do Amazon Nova Multimodal Embeddings and NVIDIA NeMo Retriever Embedding and Reranking NIMs need an API key?

Amazon Nova Multimodal Embeddings needs an API key. NVIDIA NeMo Retriever Embedding and Reranking NIMs needs no key.

### Can an agent call Amazon Nova Multimodal Embeddings and NVIDIA NeMo Retriever Embedding and Reranking NIMs without installing anything?

Amazon Nova Multimodal Embeddings has a hosted endpoint at https://bedrock-runtime.us-east-1.amazonaws.com. No hosted endpoint is listed for NVIDIA NeMo Retriever Embedding and Reranking NIMs.


## For agents

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

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- [Mistral Embed and Codestral Embed vs NVIDIA NeMo Retriever Embedding and Reranking NIMs](https://www.anchorterminal.com/compare/mistral-embeddings-vs-nvidia-nemo-retriever.md)
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