Voyage 3.5 Lite
Voyage 3.5 Lite is Voyage AI by MongoDB's cost-efficient embedding model with a context window of 0 tokens. It outperforms OpenAI text-embedding-3-large by 6.34% and achieves retrieval quality within 0.3% of Cohere Embed v4 at one-sixth the cost. Your use is subject to Voyage AI by MongoDB's Terms & Privacy Policies.
- Input price
- Input $0.02, Per 1M tokens
import { embed } from 'ai';
const result = await embed({ model: 'voyage/voyage-3.5-lite', value: 'Sunny day at the beach',})Copy link to headingProviders
Route requests across multiple providers. Copy a provider slug to set your preference. Visit the docs for more info. Using a provider means you agree to their terms, listed under Legal.
| Provider |
|---|
| — | $0.02/M | 05/20/2025 |
Copy link to headingMore models by Voyage AI by MongoDB
| Model |
|---|
| 32K | $0.12/M | — |  | 01/15/2026 | ||||||||||
| 32K | $0.06/M | — | | 01/15/2026 | ||||||||||
| 32K | $0.02/M | — | | 01/15/2026 | ||||||||||
| 32K | $0.02/M | — | | 08/11/2025 | ||||||||||
| 32K | $0.05/M | — | | 08/11/2025 | ||||||||||
| — | $0.18/M | — | | 01/07/2025 |
Copy link to headingAbout Voyage 3.5 Lite
Voyage 3.5 Lite is Voyage AI by MongoDB's cost-efficient embedding model, released May 20, 2025. It supports a context window of 0 tokens and produces embeddings in four dimensions: 2048, 1024, 512, and 256. Voyage 3.5 Lite outperforms OpenAI text-embedding-3-large by 6.34% and its predecessor voyage-3-lite by 4.28% on average across eight retrieval domains.
Voyage 3.5 Lite achieves retrieval quality within 0.3% of Cohere Embed v4 at one-sixth the cost. That makes it a practical choice for high-volume embedding workloads where per-token pricing matters. It supports the same Matryoshka dimensionality and quantization-aware training as the premium voyage-3.5, including 32-bit float, 8-bit integer, and binary precision formats. Binary rescoring yields up to 6.89% quality improvement.
If you run large-scale RAG pipelines or semantic search over millions of documents, Voyage 3.5 Lite keeps embedding infrastructure affordable without dropping to a lower quality tier. Voyage AI by MongoDB recommends it for cost-sensitive production deployments.
Copy link to headingWhat To Consider When Choosing a Provider
- Configuration: Voyage 3.5 Lite costs one-third the price of voyage-3.5 while maintaining high retrieval quality. The accuracy gap is small enough that most production workloads will not see a meaningful difference in end-user outcomes.
- Configuration: If you embed millions of documents or process high query volumes, the per-token savings compound significantly. Voyage 3.5 Lite is designed for this scale.
- Configuration: Voyage 3.5 Lite supports the same dimensionality and precision options as voyage-3.5. Combine reduced dimensions with int8 or binary precision for maximum cost savings on very large indices.
- Zero Data Retention: Zero Data Retention is offered on a per-provider and model basis. See the documentation for details.
- Authentication: AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.
Copy link to headingWhen to Use Voyage 3.5 Lite
Best for
- High-volume RAG pipelines: Per-token embedding cost scales linearly with corpus size and query volume
- Semantic search: Retrieval within 0.3% of Cohere Embed v4 at one-sixth the cost across large document collections
- Startup and growth-stage teams: Production-quality embeddings without enterprise-tier pricing
- Prototyping and experimentation: Lower cost enables faster iteration on retrieval strategies
- Multi-domain retrieval: The same eight domains as voyage-3.5 at a lower price point
Consider alternatives when
- Retrieval accuracy is the main priority: Voyage-3.5 delivers the highest retrieval accuracy among Voyage 3.5 general-purpose options
- Your corpus is exclusively source code: Voyage-code-3 is purpose-built for that domain
- You need multimodal embeddings: Voyage-3.5-lite is text-only; pick a model with native image inputs when screenshots or diagrams go into the same index
- You require the absolute lowest latency: A smaller, faster model better fits tight SLAs
Copy link to headingConclusion
Voyage 3.5 Lite balances per-token cost and retrieval quality in Voyage AI by MongoDB's embedding lineup. It outperforms OpenAI text-embedding-3-large by 6.34% while matching Cohere Embed v4 quality at a fraction of the price. If you embed at scale, it gives you production-grade retrieval without overcommitting on infrastructure costs. Access it through AI Gateway for unified provider management.
Copy link to headingFrequently Asked Questions
How does Voyage 3.5 Lite compare to voyage-3.5?
Voyage 3.5 Lite costs one-third the price of voyage-3.5. It achieves retrieval quality within 0.3% of Cohere Embed v4, while voyage-3.5 surpasses Cohere Embed v4 by 1.63%. For most production workloads, the accuracy difference is small relative to the cost savings.
What embedding dimensions does Voyage 3.5 Lite support?
Four dimensions: 2048, 1024, 512, and 256. The same Matryoshka dimensionality as voyage-3.5, with the same quantization options for further storage savings.
Is Voyage 3.5 Lite suitable for production use?
Yes. Voyage AI by MongoDB recommends it for cost-sensitive production deployments. It outperforms OpenAI text-embedding-3-large by 6.34% across eight retrieval domains.
What quantization formats does Voyage 3.5 Lite support?
32-bit float, 8-bit integer, and binary precision. Binary rescoring yields up to 6.89% quality improvement, making aggressive compression practical at scale.
How much cheaper is Voyage 3.5 Lite than competitors?
Voyage 3.5 Lite achieves retrieval quality within 0.3% of Cohere Embed v4 at one-sixth the cost. It also outperforms OpenAI text-embedding-3-large while maintaining a lower per-token price.
How do I route Voyage 3.5 Lite through Vercel AI Gateway?
Add your Voyage AI by MongoDB API key in AI Gateway settings, then send embedding requests through AI Gateway. AI Gateway authenticates requests and records usage across embedding providers.
Can I migrate from voyage-3-lite to Voyage 3.5 Lite?
Yes. Voyage 3.5 Lite outperforms voyage-3-lite by 4.28% on average. Migration requires re-embedding your corpus since the model weights are different.