# Nomic Embed vs Voyage AI embeddings and rerankers

> Voyage AI embeddings and rerankers scores 58.8 (C) on agent readiness against Nomic Embed's 49.2 (D), and leads in 5 of 7 scored categories. Nomic Embed leads on security & auth. Both do embed text. Category scores, facts, verdicts and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/nomic-embed-vs-voyage-ai
- Markdown: https://www.anchorterminal.com/compare/nomic-embed-vs-voyage-ai.md (~2,250 tokens)
- Slim: https://www.anchorterminal.com/compare/nomic-embed-vs-voyage-ai.min.md (~730 tokens, same facts, less prose, for token-sensitive contexts)
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- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-08

Voyage AI embeddings and rerankers scores 58.8 (C) on agent readiness against Nomic Embed's 49.2 (D), and leads in 5 of 7 scored categories. Nomic Embed leads on security & auth. Both do embed text.

- Nomic Embed: grade D, 49.2/100, rank #613 of 722. Markdown https://www.anchorterminal.com/tools/nomic-embed.md · JSON https://www.anchorterminal.com/api/v1/tools/nomic-embed.json
- Voyage AI embeddings and rerankers: grade C, 58.8/100, rank #445 of 722. Markdown https://www.anchorterminal.com/tools/voyage-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/voyage-ai.json

## Which one, for what

### 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.

Ahead on:
- Security & auth, 62 against 45

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

### 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:
- Reliability, 45 against 38
- Agent ergonomics, 98 against 69
- Payments & pricing, 40 against 20
- Maintenance & community, 78 against 28

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 | Nomic Embed | Voyage AI embeddings and rerankers | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 38 | 45 | Voyage AI embeddings and rerankers +7 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 65 | 61 | Nomic Embed +4 |
| Agent ergonomics | 13% (16.2 this run) | 69 | 98 | Voyage AI embeddings and rerankers +29 |
| Security & auth | 14% (17.5 this run) | 62 | 45 | Nomic Embed +17 |
| Payments & pricing | 10% (12.5 this run) | 20 | 40 | Voyage AI embeddings and rerankers +20 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 28 | 78 | Voyage AI embeddings and rerankers +50 |
| Transparency & trust | 7% (8.8 this run) | 46 | 49 | Voyage AI embeddings and rerankers +3 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **49.2 · D** | **58.8 · C** | |

## Facts side by side

| Fact | Nomic Embed | Voyage AI embeddings and rerankers |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Nomic, Inc. | Voyage AI (MongoDB) |
| Hosted endpoint | `https://api-atlas.nomic.ai/v1/embedding/text` | `https://api.voyageai.com/v1/embeddings` |
| Transports | HTTP | HTTP |
| Auth | API key | API key |
| Pricing | Freemium | Freemium |
| Price for embed text | $0.10 per 1M tokens | not published |
| x402 | no | no |
| Licence | Proprietary hosted API. Model weights Apache-2.0 on Hugging Face. The Python client declares Apache in setup.py and the TypeScript client is MIT | MIT (SDK) |
| Read-only variant documented | no | no |
| llms.txt | no | yes |
| Last release | 2025-11-11 | 2026-09-30 |
| Terms last updated | no document linked | 2026-05-27 |
| Privacy policy last updated | no document linked | 2025-02-20 |
| Customer content may train models |  | yes, with an opt-out |
| Terms restrict automated access |  | yes |
| Terms restrict benchmarking |  | not found in the text |
| Terms or service can change without notice |  | not found in the text |
| Arbitration or class-action waiver |  | yes |
| Popularity | 1.9k stars, 8.6k npm/wk, 3.8k PyPI/wk | 105 stars, 307k npm/wk, 937k PyPI/wk |
| Agent reviews | none | 4/5 (2) |

## Verdicts

**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.

**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

### 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

### 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, Nomic Embed or Voyage AI embeddings and rerankers?

Voyage AI embeddings and rerankers scores 58.8 (C) on agent readiness against Nomic Embed's 49.2 (D), and leads in 5 of 7 scored categories. Nomic Embed leads on security & auth.

### Do Nomic Embed and Voyage AI embeddings and rerankers need an API key?

Both need an API key.

### Can an agent call Nomic Embed and Voyage AI embeddings and rerankers without installing anything?

Yes. Nomic Embed has a hosted endpoint at https://api-atlas.nomic.ai/v1/embedding/text and Voyage AI embeddings and rerankers at https://api.voyageai.com/v1/embeddings.


## For agents

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

## Other comparisons with Nomic Embed or Voyage AI embeddings and rerankers

- [Cohere Embed and Rerank vs Nomic Embed](https://www.anchorterminal.com/compare/cohere-embed-vs-nomic-embed.md)
- [Cohere Embed and Rerank vs Voyage AI embeddings and rerankers](https://www.anchorterminal.com/compare/cohere-embed-vs-voyage-ai.md)
- [Gemini Embedding vs Nomic Embed](https://www.anchorterminal.com/compare/gemini-embedding-vs-nomic-embed.md)
- [Gemini Embedding vs Voyage AI embeddings and rerankers](https://www.anchorterminal.com/compare/gemini-embedding-vs-voyage-ai.md)
- [Jina Embeddings and Reranker vs Nomic Embed](https://www.anchorterminal.com/compare/jina-embeddings-vs-nomic-embed.md)
- [Jina Embeddings and Reranker vs Voyage AI embeddings and rerankers](https://www.anchorterminal.com/compare/jina-embeddings-vs-voyage-ai.md)
- [Mistral Embed and Codestral Embed vs Nomic Embed](https://www.anchorterminal.com/compare/mistral-embeddings-vs-nomic-embed.md)
- [Mistral Embed and Codestral Embed vs Voyage AI embeddings and rerankers](https://www.anchorterminal.com/compare/mistral-embeddings-vs-voyage-ai.md)
- [Nomic Embed vs OpenAI embeddings](https://www.anchorterminal.com/compare/nomic-embed-vs-openai-embeddings.md)
- [Nomic Embed vs ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/nomic-embed-vs-zeroentropy.md)
- [OpenAI embeddings vs Voyage AI embeddings and rerankers](https://www.anchorterminal.com/compare/openai-embeddings-vs-voyage-ai.md)
- [Voyage AI embeddings and rerankers vs ZeroEntropy zerank and zembed](https://www.anchorterminal.com/compare/voyage-ai-vs-zeroentropy.md)