This will automatically use the environment variable VOYAGE_API_KEY. changedbuild-with-claude/embeddings
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3636
3737**Previous generation**
3838
39For each model's lifecycle status and recommended replacement, see [Model deprecations, lifecycle states, and support](https://www.mongodb.com/docs/voyageai/models/lifecycle/) in the MongoDB documentation.
39For each model’s lifecycle status and recommended replacement, see [Model deprecations, lifecycle states, and support](https://www.mongodb.com/docs/voyageai/models/lifecycle/) in the MongoDB documentation.
4040
4141| Model | Context length | Embedding dimension | Description |
4242| ------------------ | -------------- | ------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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6161| `voyage-context-4` | 120,000 | 1024 (default), 256, 512, 2048 | Contextualized chunk embeddings optimized for general-purpose and multilingual retrieval quality. See the [voyage-context-4 blog post](https://blog.voyageai.com/2026/06/29/voyage-context-4/) for details. |
6262| `voyage-context-3` | 120,000 | 1024 (default), 256, 512, 2048 | Previous generation of `voyage-context-4`. See the [voyage-context-3 blog post](https://blog.voyageai.com/2025/07/23/voyage-context-3/) for details. |
6363
64The 120,000-token limit applies when you set `enable_auto_chunking` to `true`. Otherwise, the total number of tokens across all inputs can't exceed 32,000.
64The 120,000-token limit applies when you set `enable_auto_chunking` to `true`. Otherwise, the total number of tokens across all inputs can’t exceed 32,000.
6565
6666Voyage AI also offers rerankers, which take a query and a list of documents and return them ranked by relevance to the query. Call these models with `rerank()`:
6767
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164164}
165165```
166166
167Model API keys from Atlas work with `ai.mongodb.com`, except keys scoped to a geography, which use that geography's endpoint. If you have an API key from the Voyage AI platform instead, see [Migrate your applications to use the Atlas Embedding and Reranking API](https://www.mongodb.com/docs/voyageai/tutorials/migrate-to-atlas/) in the MongoDB documentation.
167Model API keys from Atlas work with `ai.mongodb.com`, except keys scoped to a geography, which use that geography’s endpoint. If you have an API key from the Voyage AI platform instead, see [Migrate your applications to use the Atlas Embedding and Reranking API](https://www.mongodb.com/docs/voyageai/tutorials/migrate-to-atlas/) in the MongoDB documentation.
168168
169169For the full request and response reference, see [Create text embeddings](https://www.mongodb.com/docs/api/doc/atlas-embedding-and-reranking-api/operation/operation-createembedding) in the Atlas Embedding and Reranking API documentation.
170170
171171### AWS Marketplace
172172
173Voyage AI models are also available on AWS Marketplace through [MongoDB's seller profile](https://aws.amazon.com/marketplace/seller-profile?id=c9032c7b-70dd-459f-834f-c1e23cf3d092). For instructions, see [Deploy Voyage AI models using AWS Marketplace](https://www.mongodb.com/docs/voyageai/management/aws-marketplace/) in the MongoDB documentation.
173Voyage AI models are also available on AWS Marketplace through [MongoDB’s seller profile](https://aws.amazon.com/marketplace/seller-profile?id=c9032c7b-70dd-459f-834f-c1e23cf3d092). For instructions, see [Deploy Voyage AI models using AWS Marketplace](https://www.mongodb.com/docs/voyageai/management/aws-marketplace/) in the MongoDB documentation.
174174
175175## Quickstart example
176176
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237237
238238<AccordionGroup>
239239 <Accordion title="Why do Voyage AI embeddings have superior quality?">
240 Embedding models rely on powerful neural networks to capture and compress semantic context, similar to generative models. Voyage AI's team of experienced AI researchers optimizes every component of the embedding process, including:
240 Embedding models rely on powerful neural networks to capture and compress semantic context, similar to generative models. Voyage AI’s team of experienced AI researchers optimizes every component of the embedding process, including:
241241
242242 * Model architecture
243243 * Data collection
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244244 * Loss functions
245245 * Optimizer selection
246246
247 Learn more about Voyage AI's technical approach on the [Voyage AI blog](https://blog.voyageai.com/).
247 Learn more about Voyage AI’s technical approach on the [Voyage AI blog](https://blog.voyageai.com/).
248248 </Accordion>
249249
250250 <Accordion title="What embedding models are available and which should I use?">
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293293 >
294294 > * Example
295295 >
296 > * When `input_type="query"`, a query such as "When is Apple's conference call scheduled?" will become "**Represent the query for retrieving supporting documents:** When is Apple's conference call scheduled?"
297 > * When `input_type="document"`, a document such as "Apple's conference call to discuss fourth fiscal quarter results and business updates is scheduled for Thursday, November 2, 2023 at 2:00 p.m. PT / 5:00 p.m. ET." will become "**Represent the document for retrieval:** Apple's conference call to discuss fourth fiscal quarter results and business updates is scheduled for Thursday, November 2, 2023 at 2:00 p.m. PT / 5:00 p.m. ET."
296 > * When `input_type="query"`, a query such as “When is Apple’s conference call scheduled?” will become “**Represent the query for retrieving supporting documents:** When is Apple’s conference call scheduled?”
297 > * When `input_type="document"`, a document such as “Apple’s conference call to discuss fourth fiscal quarter results and business updates is scheduled for Thursday, November 2, 2023 at 2:00 p.m. PT / 5:00 p.m. ET.” will become “**Represent the document for retrieval:** Apple’s conference call to discuss fourth fiscal quarter results and business updates is scheduled for Thursday, November 2, 2023 at 2:00 p.m. PT / 5:00 p.m. ET.”
298298 </Accordion>
299299
300300 <Accordion title="What quantization options are available?">
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