Fireworks AI vs Voyage AI: Token Pricing, Speed & Intelligence
Full comparison of Fireworks AI and Voyage AI — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
Fireworks AI
Production-grade open-source inference with fast cold starts
Fireworks AI provides optimised inference for open-weight models with a focus on production reliability and low latency. They host Llama, DeepSeek R1, and other popular open-source models with competitive per-token pricing and a serverless deployment model that minimises cold-start times.
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
Fireworks AI
Voyage AI
Key differentiators
Production-grade reliability with 320+ tokens/sec throughput and DeepSeek R1 reasoning at $3/1M input — a strong balance of speed and capability.
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
Fireworks AI FAQs
What models does Fireworks AI offer?
Fireworks AI hosts Llama 3.3 70B, DeepSeek R1, Mixtral, and other popular open-weight models. They focus on production-ready models with optimised inference rather than the broadest possible catalog.
How much does Fireworks AI cost?
Llama 3.3 70B costs $0.90/1M tokens (input and output). DeepSeek R1 is $3.00/1M input and $8.00/1M output. Pricing is competitive with other inference API providers.
How does Fireworks AI compare to Together AI?
Fireworks AI offers faster throughput (320 vs 190 tokens/sec on Llama 3.3 70B) and stronger production reliability. Together AI has a larger model catalog and fine-tuning support. Choose Fireworks for production speed, Together for model variety.
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
Fireworks AI — Production-grade open-source inference with fast cold starts
Fireworks AI provides optimised inference for open-weight models with a focus on production reliability and low latency. They host Llama, DeepSeek R1, and other popular open-source models with competitive per-token pricing and a serverless deployment model that minimises cold-start times.
Production-grade reliability with 320+ tokens/sec throughput and DeepSeek R1 reasoning at $3/1M input — a strong balance of speed and capability.
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
Fireworks AI
- ▸320+ tokens/sec on Llama 3.3 70B — fast GPU inference
- ▸DeepSeek R1 hosting with strong reasoning capability
- ▸Production-grade reliability with SLAs
Voyage AI
- ▸Top MTEB leaderboard performance
- ▸Multimodal embedding support
- ▸Very competitive pricing
Provider category context
Fireworks 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 Fireworks 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.