Head to head · Embed text · October 2026 research run

Amazon Nova Multimodal Embeddings vs Nomic Embed

Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Nomic Embed's 49.2 (D), and leads in every scored category. Both do embed text. Amazon Nova Multimodal Embeddings is cheaper for embed text, $0.0675 against $0.10 per 1M tokens.

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 38
  • Schema & documentation, 76 against 65
  • Agent ergonomics, 78 against 69
  • Security & auth, 91 against 62
  • Payments & pricing, 30 against 20
  • Maintenance & community, 50 against 28
  • Transparency & trust, 79 against 46

Also in its favour

  • Cheaper for embed text, $0.0675 against $0.10 per 1M tokens
  • 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

Nomic Embed D

Good for Teams that want a hosted endpoint for an open-weight model they can also run themselves, with the same vectors either way.

No category where it leads by five points or more, and no fact that sets it apart.

Watch for

docs.nomic.ai/llms.txt and www.nomic.ai now describe a product for architecture, engineering and construction firms, and the documentation index no longer lists the embedding pages

Score by category

CategoryWeight this runAmazon Nova Multimodal EmbeddingsNomic EmbedEdge
Reliability16%209538Amazon Nova Multimodal Embeddings +57
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27665Amazon Nova Multimodal Embeddings +11
Agent ergonomics13%16.27869Amazon Nova Multimodal Embeddings +9
Security & auth14%17.59162Amazon Nova Multimodal Embeddings +29
Payments & pricing10%12.53020Amazon Nova Multimodal Embeddings +10
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.85028Amazon Nova Multimodal Embeddings +22
Transparency & trust7%8.87946Amazon Nova Multimodal Embeddings +33
Negative events≤1500
Total75 · BB49.2 · D

Facts side by side

FactAmazon Nova Multimodal EmbeddingsNomic Embed
KindHTTP APIHTTP API
VendorAmazon Web ServicesNomic, Inc.
Hosted endpointhttps://bedrock-runtime.us-east-1.amazonaws.comhttps://api-atlas.nomic.ai/v1/embedding/text
TransportsHTTPHTTP
AuthAPI keyAPI key
PricingPay per useFreemium
Price for embed text$0.0675 per 1M tokens$0.10 per 1M tokens
x402nono
LicenceProprietary service under the AWS Service Terms. The AWS SDKs are Apache-2.0Proprietary hosted API. Model weights Apache-2.0 on Hugging Face. The Python client declares Apache in setup.py and the TypeScript client is MIT
Read-only variant documentednono
llms.txtyesno
Last release2025-10-282025-11-11
Terms last updated2026-10-01no document linked
Privacy policy last updated2026-05-18no document linked
Customer content may train modelsyes, with an opt-out
Terms restrict automated accessyes
Terms restrict benchmarkingyes
Terms or service can change without noticeyes
Arbitration or class-action waivernot found in the text
Popularity18.1M npm/wk, 573.7M PyPI/wk1.9k stars, 8.6k npm/wk, 3.8k 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.

Nomic Embed

The text models have Apache-2.0 weights and a public OpenAPI 3.1 contract, so vectors made through the hosted endpoint can be reproduced locally. Nomic's current site and documentation index describe a construction-industry product, no rendered public page prices the endpoint, and no published terms or status component name it.

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

Nomic Embed

  1. Set task_type to search_query for queries and search_document for stored text. The default is search_document
  2. Name the model in every request. The API defaults to nomic-embed-text-v1, while the Python client defaults to nomic-embed-text-v1.5
  3. Keep under 1,200 requests per five minutes per IP address. The Python client sends at most 10 texts a request
  4. Set long_text_mode to truncate or mean. Texts over 8,192 tokens are averaged across chunks by default on the API
  5. Pass dimensionality only with nomic-embed-text-v1.5, between 64 and 768

Questions

Which is better for AI agents, Amazon Nova Multimodal Embeddings or Nomic Embed?

Amazon Nova Multimodal Embeddings scores 75 (BB) on agent readiness against Nomic Embed's 49.2 (D), and leads in every scored category.

Which is cheaper for embed text, Amazon Nova Multimodal Embeddings or Nomic Embed?

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

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

Both need an API key.

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

Yes. Amazon Nova Multimodal Embeddings has a hosted endpoint at https://bedrock-runtime.us-east-1.amazonaws.com and Nomic Embed at https://api-atlas.nomic.ai/v1/embedding/text.

Other comparisons with Amazon Nova Multimodal Embeddings or Nomic Embed

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