Wispr Flow - Don’t type, just speak
Mini tools| Model | Input | Cached input | Output | Unit |
|---|---|---|---|---|
|
rerank 2.5
Voyage AI
|
$0.05 | - | $0 | per 1M tokens |
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Rerank 2.5 lite
Voyage AI
|
$0.02 | - | $0 | per 1M tokens |
|
Voyage 4
Voyage AI
|
$0.06 | - | $0 | per 1M tokens |
|
Voyage 4 large
Voyage AI
|
$0.12 | - | $0 | per 1M tokens |
|
Voyage 4 lite
Voyage AI
|
$0.02 | - | $0 | per 1M tokens |
|
Voyage code 2
Voyage AI
|
$0.12 | - | $0 | per 1M tokens |
|
Voyage code 3
This model
Voyage AI
|
$0.18 | - | $0 | per 1M tokens |
|
Voyage context 3
Voyage AI
|
$0.18 | - | $0 | per 1M tokens |
|
Voyage finance 2
Voyage AI
|
$0.12 | - | $0 | per 1M tokens |
|
Voyage law 2
Voyage AI
|
$0.12 | - | $0 | per 1M tokens |
|
Voyage multilingual 2
Voyage AI
|
$0.12 | - | $0 | per 1M tokens |
|
Voyage multimodal 3
Voyage AI
|
$0.12 | - | $0 | per 1M tokens |
|
Voyage multimodal 3.5
Voyage AI
|
$0.12 | - | $0 | per 1M tokens |
Voyage code 3
By Voyage AI
voyage-code-3 is an embedding model built for code retrieval workloads including text-to-code, code-to-code, and docstring-to-code retrieval. It supports a 32K-token context window, compared to 8K for OpenAI alternatives. Matryoshka learning enables nested embeddings at 256, 512, 1024, and 2048 dimensions from a single vector, allowing dimension reduction without re-embedding. Quantization options include float32, int8, uint8, binary, and ubinary formats, enabling up to 32x storage reduction. Trained on a diverse corpus covering 300+ programming languages with real-world query-code pairs. Available via Voyage API, AWS SageMaker marketplace, and on-premises deployment. Binary rescoring further recovers retrieval quality when needed.
Coding
Gen 2
Overview
Text embedding model optimized for code retrieval. Supports Matryoshka embeddings at 256, 512, 1024, and 2048 dimensions with quantized formats (float, int8, uint8, binary, ubinary) for up to 32x storage reduction. Features a 32K-token context window. Outperforms OpenAI text-embedding-3-large by 13.80% on 32 code retrieval datasets covering text-to-code, code-to-code, and docstring-to-code tasks.
Pricing
Compare Voyage code 3 with other models listed in the same vendor pricing tiers and context lengths.
Tier
Standard
Batch
| Model | Input | Cached input | Output | Unit |
|---|---|---|---|---|
|
rerank 2.5
Voyage AI
|
$0.0335 | - | $0 | per 1M tokens |
|
Rerank 2.5 lite
Voyage AI
|
$0.0134 | - | $0 | per 1M tokens |
|
Voyage 4
Voyage AI
|
$0.0402 | - | $0 | per 1M tokens |
|
Voyage 4 large
Voyage AI
|
$0.0804 | - | $0 | per 1M tokens |
|
Voyage 4 lite
Voyage AI
|
$0.0134 | - | $0 | per 1M tokens |
|
Voyage code 2
Voyage AI
|
$0.0804 | - | $0 | per 1M tokens |
|
Voyage code 3
This model
Voyage AI
|
$0.1206 | - | $0 | per 1M tokens |
|
Voyage context 3
Voyage AI
|
$0.1206 | - | $0 | per 1M tokens |
|
Voyage finance 2
Voyage AI
|
$0.0804 | - | $0 | per 1M tokens |
|
Voyage law 2
Voyage AI
|
$0.0804 | - | $0 | per 1M tokens |
|
Voyage multilingual 2
Voyage AI
|
$0.0804 | - | $0 | per 1M tokens |
|
Voyage multimodal 3
Voyage AI
|
$0.0804 | - | $0 | per 1M tokens |
|
Voyage multimodal 3.5
Voyage AI
|
$0.0804 | - | $0 | per 1M tokens |
About Voyage AI
Voyage AI provides best-in-class embedding models and rerankers for search and retrieval over unstructured data, used to power retrieval-augmented generation (RAG) and AI applications. It offers general-purpose, domain-specific (finance, legal, code) and company-specific fine-tuned models. Founded in 2023 and based in Palo Alto, the company was acquired by MongoDB, Inc. in February 2025 and now operates as a MongoDB subsidiary.
View Company Profile
Last updated: June 24, 2026
