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Groq High-Speed Inference API vs Together AI API

A head-to-head look at Groq High-Speed Inference API and Together AI API across pricing, features, strengths, and weaknesses.

FeatureGroq High-Speed Inference APITogether AI API
Editorial score★ 4.6 / 5★ 4.5 / 5
PricingUsage-based; free tier to startUsage-based; fine-tuning and dedicated endpoints
Pros
  • +Among the fastest token throughput available
  • +Simple drop-in for existing OpenAI code
  • +Blazing-fast inference ideal for latency-sensitive apps
  • +Cost-effective open-model hosting
  • +Solid fine-tuning support
  • +Cost-effective hosting for open-weight models
Cons
  • −Model selection limited to supported open models
  • −Fewer frontier models than multi-provider routers
  • −Not ideal for huge offline or on-prem workloads
  • −Catalog focused on open models
  • −Catalog focuses on open, not closed frontier models
  • −Fine-tuning still needs your own dataset
VisitView full review →View full review →

Editor’s verdict

Groq runs inference on custom LPU hardware for ultra-low latency, ideal for real-time applications; Together AI offers a broader model marketplace with fine-tuning, serverless endpoints, and open-source model hosting. Choose Groq for speed-critical real-time inference; choose Together AI for model variety and fine-tuning.

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