Together AI vs Voyage AI: Token Pricing, Speed & Intelligence
Full comparison of Together AI and Voyage AI — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
Together AI
Open-source model hosting with competitive inference pricing
Together AI specialises in hosting open-weight models including the full Llama family, Mixtral, and DeepSeek variants. They offer live pricing via their public API and support fine-tuning workflows. A popular choice for teams that want open-source flexibility without managing their own GPU infrastructure.
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
—
—
—
—
—
—
—
—
—
—
—
—
Live token pricing
Strengths & weaknesses
Together AI
Voyage AI
Key differentiators
The broadest open-weight model catalog with fine-tuning support — ideal for teams that need model customisation without self-hosting.
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
Together AI FAQs
What models does Together AI support?
Together AI hosts 100+ open-weight models including the full Llama 3.x family (8B, 70B, 405B), Mixtral, DeepSeek R1, Qwen, and many others. They also support custom fine-tuned model deployment.
How much does Together AI cost?
Llama 3.3 70B costs $0.88/1M tokens (input and output). Llama 3.1 405B is $3.50/1M tokens. Smaller models like Llama 3.2 11B Vision start at $0.18/1M tokens.
Does Together AI support fine-tuning?
Yes. Together AI offers supervised fine-tuning for Llama and other open-weight models. You can upload training data, run fine-tuning jobs, and deploy the resulting model via their inference API.
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
Together AI — Open-source model hosting with competitive inference pricing
Together AI specialises in hosting open-weight models including the full Llama family, Mixtral, and DeepSeek variants. They offer live pricing via their public API and support fine-tuning workflows. A popular choice for teams that want open-source flexibility without managing their own GPU infrastructure.
The broadest open-weight model catalog with fine-tuning support — ideal for teams that need model customisation without self-hosting.
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
Together AI
- ▸Largest selection of open-weight models
- ▸Fine-tuning support for custom model training
- ▸OpenAI-compatible API — easy migration
Voyage AI
- ▸Top MTEB leaderboard performance
- ▸Multimodal embedding support
- ▸Very competitive pricing
Provider category context
Together AI is a inference api, founded in 2022. Voyage AI is a inference api, founded in 2023. Both are inference api providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both Together AI and Voyage AI host open-weight models. The key differentiators are latency, throughput, and which specific model versions each provider offers. Check the speed metrics above — inference API providers often differ significantly on tokens-per-second for the same model. Pricing is typically competitive between them; availability of specific model versions (e.g., Llama 3.1 405B, DeepSeek V3) may be the deciding factor.