Free Tier
200M free tokens
- Access to all current models
- Embedding and reranking
Voyage AI builds state-of-the-art embedding models and rerankers that power search, retrieval, and RAG applications. Founded in September 2023 by Stanford CS Assistant Professor Tengyu Ma, with advisors including Fei-Fei Li, Christopher Manning, and Christopher Re, Voyage AI quickly established itself as a leader in the embedding space by consistently outperforming OpenAI and Cohere on retrieval benchmarks.
The company raised $28M in total funding including a Series A led by CRV, with participation from Snowflake and Databricks. In February 2025, MongoDB acquired Voyage AI for $220M in cash and stock — a remarkable exit after less than two years of operation and a 7.8x return on invested capital. The product and API continue to operate under the Voyage AI brand as part of MongoDB's data platform.
Voyage AI's model lineup includes the Voyage 4 family (launched January 2026), which introduced the first production-grade Mixture of Experts (MoE) architecture for embeddings. The family features shared embedding spaces across model sizes, enabling teams to use cheaper models for queries and more expensive ones for indexing. Domain-specific models for code, law, and finance outperform general-purpose alternatives by ~15% on domain tasks, and the 32K context window is 4x OpenAI's limit.
Core capabilities this platform advertises.
What this tool does well, and the limitations to keep in mind.
Pros
Cons
What's included in each plan, and how the tiers compare.
200M free tokens
$0.12/M tokens
Usage-based
$0.06/M tokens
Usage-based
$0.02/M tokens
Usage-based
$0.02-0.05/M tokens
Usage-based
Developers building search and RAG applications
Voyage AI embeddings power the retrieval layer in RAG applications, while Respan monitors the LLM calls that consume those retrieved results. Together, they provide end-to-end observability from document retrieval through final LLM response generation.
Top companies in Foundation Models you can use instead of Voyage AI (MongoDB).
OpenAI
GPT-4o and GPT-4 Turbo frontier models
Anthropic
Claude 4 and Claude 3.5 Sonnet models
Google AI
Gemini 2.0 multimodal models
Meta AI
Llama open-source model family
Mistral AI
Mistral Large and Mixtral models
Cohere
Command R+ for RAG applications
Microsoft
Small language models
xAI
Grok models with real-time data access
DeepSeek
DeepSeek-V3 and DeepSeek-R1 models
Databricks (DBRX)
Moonshot AI
Black Forest Labs
Image generation
Alibaba Qwen
Qwen2 open-source model series
Snowflake
Arctic models
Stability AI
Stable Diffusion image generation
Reka
01.AI
Zhipu AI
Guide Labs
Inherently interpretable LLM architecture
Cascade
Model distillation
Luel
Natural language to training data
Side-by-side comparisons with other tools in this category.
Companies from adjacent layers in the AI stack that work well with Voyage AI (MongoDB).
Last verified: March 27, 2026