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Cerebrium vs Together AI

CerebriumTogether AI

Bottom line: Cerebrium for mL engineers; Together AI for cost-conscious teams on open models.

CerebriumCerebrium

Python-native serverless GPU platform for real-time AI inference and custom models

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Together AITogether AI

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

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Votes00
PricingFreemiumFreemium
CategoryAi InfrastructureAi Infrastructure
Tags
serverless-gpuinferencemlopsreal-time-aipython
inferencefine-tuninggpu-cloudopen-sourcellm-api
Best for
  • ML engineers
  • Startups shipping GPU APIs
  • Real-time AI products
  • Cost-conscious teams on open models
  • ML teams that fine-tune
  • Startups scaling inference volume
Pros
  • Python-native, no container pipelines needed
  • Pay-per-second billing with no idle cost
  • Fast low single-digit second cold starts
  • 12+ GPU types including A100 and H100
  • Separate GPU/CPU/memory line items
  • 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
Cons
  • Smaller than major inference clouds
  • No self-hosting option
  • Cold starts still matter for ultra-low latency
  • Thinner ecosystem and enterprise tooling
  • Python-focused workflow only
  • 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

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