Amazon Bedrock vs Voyage AI: Token Pricing, Speed & Intelligence
Full comparison of Amazon Bedrock and Voyage AI — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
Amazon Bedrock
AWS-native LLM access — Nova, Claude, Llama, and more via one API
Amazon Bedrock is AWS's managed LLM service, providing access to Amazon's own Nova models alongside third-party models from Anthropic, Meta, Mistral, and others. It integrates natively with the AWS ecosystem including IAM, VPC, and CloudWatch, making it the default choice for teams already on AWS.
Voyage AI
State-of-the-art embedding and reranking models
Voyage AI specialises in embedding and reranking models for retrieval-augmented generation (RAG) and semantic search. Voyage 3.5 and its variants consistently top the MTEB leaderboard for retrieval quality.
Key metrics
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Live token pricing
Strengths & weaknesses
Amazon Bedrock
Voyage AI
Key differentiators
The only way to run Claude, Llama, and Amazon Nova within your own AWS VPC — data never leaves your account.
Voyage 3.5 Lite offers top-tier retrieval quality at just $0.02/1M tokens — the most cost-effective high-quality embedding available.
Frequently asked questions
Amazon Bedrock FAQs
What models are available on Amazon Bedrock?
Amazon Bedrock offers Amazon Nova (Micro, Lite, Pro), Anthropic Claude (Haiku, Sonnet, Opus), Meta Llama 3.x, Mistral, Cohere, and others. The catalog varies by AWS region.
How does Amazon Bedrock pricing work?
Bedrock uses on-demand pricing per 1M tokens, similar to direct provider APIs. Provisioned throughput is available for guaranteed capacity at a fixed hourly rate. Prices are generally comparable to or slightly above direct provider pricing.
Is Amazon Bedrock HIPAA-compliant?
Yes. Amazon Bedrock is covered under AWS's HIPAA BAA, making it suitable for healthcare applications that require HIPAA compliance. Data processed through Bedrock stays within your AWS account.
Voyage AI FAQs
What is Voyage AI used for?
Voyage AI provides embedding and reranking models for RAG pipelines, semantic search, and document retrieval. It does not offer chat or text generation models.
How does Voyage AI compare to OpenAI embeddings?
Voyage 3.5 consistently outperforms OpenAI text-embedding-3-large on MTEB benchmarks while being significantly cheaper. It is the preferred choice for production RAG systems.
Provider resources
Amazon Bedrock — AWS-native LLM access — Nova, Claude, Llama, and more via one API
Amazon Bedrock is AWS's managed LLM service, providing access to Amazon's own Nova models alongside third-party models from Anthropic, Meta, Mistral, and others. It integrates natively with the AWS ecosystem including IAM, VPC, and CloudWatch, making it the default choice for teams already on AWS.
The only way to run Claude, Llama, and Amazon Nova within your own AWS VPC — data never leaves your account.
Voyage AI — State-of-the-art embedding and reranking models
Voyage AI specialises in embedding and reranking models for retrieval-augmented generation (RAG) and semantic search. Voyage 3.5 and its variants consistently top the MTEB leaderboard for retrieval quality.
Voyage 3.5 Lite offers top-tier retrieval quality at just $0.02/1M tokens — the most cost-effective high-quality embedding available.
Key strengths compared
Amazon Bedrock
- ▸Native AWS integration — IAM, VPC, CloudWatch, S3
- ▸Access to Claude, Llama, Mistral, and Amazon Nova via one API
- ▸Enterprise compliance: SOC 2, HIPAA, GDPR
Voyage AI
- ▸Top MTEB leaderboard performance
- ▸Multimodal embedding support
- ▸Very competitive pricing
Provider category context
Amazon Bedrock is a cloud, founded in 2023. Voyage AI is a inference api, founded in 2023. The category difference means these providers serve partially overlapping use cases — compare the model lists and pricing tables above to find the best fit for your specific workload.
How to choose between them
Choose Amazon Bedrock if you need native aws integration — iam, vpc, cloudwatch, s3. Choose Voyage AI if you need top mteb leaderboard performance. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.