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Together AI vs Groq

Together AIGroq

Bottom line: Together AI for cost-conscious teams on open models; Groq for developers building latency-sensitive apps.

Inference, fine-tuning, and GPU clusters for open models.

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Very fast LLM inference on custom LPU hardware.

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Votes00
PricingFreemiumFreemium
CategoryCodingCoding
Tags
inferencefine-tuninggpu-cloudopen-sourcellm-api
inferencellm-apilow-latencyopen-sourcehardware
Best for
  • Cost-conscious teams on open models
  • ML teams that fine-tune
  • Startups scaling inference volume
  • Developers building latency-sensitive apps
  • Teams running AI agents
  • Voice and real-time product builders
Pros
  • Large catalog of open and open-weight models
  • Competitive per-token pricing
  • Fine-tuning with weight ownership
  • Dedicated GPU clusters for scale
  • OpenAI-compatible API
  • Exceptional inference speed on supported models
  • Competitive per-token pricing
  • OpenAI-compatible API is easy to adopt
  • Free tier with no credit card
  • Good fit for agents and real-time apps
Cons
  • Broad pricing surface across several product lines
  • You own quality and safety evaluation of open models
  • Dedicated clusters require commitment and planning
  • Less turnkey than closed frontier APIs
  • Model catalog and prices change over time
  • Limited to a curated catalog of open models
  • No hosting of arbitrary custom weights
  • Model lineup changes over time
  • Corporate turbulence in 2026 (Nvidia deal, down round)
  • Free-tier rate limits are modest

Comparison generated from each tool's listing. Add or remove tools above to change it.