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Cerebras vs Groq

A side-by-side comparison of Cerebras and Groq, two Inference tools, drawn from Ignaite's continuously-verified listings.

Compared from listings verified as of

Cerebras

Inference

Wafer-scale inference cloud for open models.

View Cerebras

Groq

Inference

Low-latency inference for open-weights models on custom LPU chips.

View Groq

At a glance

Feature comparison of Cerebras and Groq
AttributeCerebrasGroq
CategoryInferenceInference
PricingFREEMIUMFREEMIUM
LicenseProprietaryProprietary
DeploymentCloudCloud
Platforms (differs)Web, APIAPI, Web
Model supportMulti-modelMulti-model
Vendor (differs)Cerebras SystemsGroq

The honest brief

Cerebras

Wafer-scale CS-3 hardware tops every rival on tokens/sec — fastest pure throughput for agent loops.

  • Highest tokens/sec in the market
  • Low time-to-first-token (~80-150ms)
  • 2-3x faster end-to-end in agent loops
  • OpenAI-compatible API, free daily tier
  • Smaller model catalog than Groq/Together
  • Less mature ecosystem and client libs
  • Occasional capacity limits under demand

Groq

Custom LPU silicon delivers deterministic sub-100ms TTFT, ideal for voice and latency-critical apps.

  • Hundreds of tokens/sec on open models
  • Sub-100ms time-to-first-token
  • Deterministic, low-variance latency
  • OpenAI-compatible API with free tier
  • Curated open-weight models only
  • No frontier closed models (GPT/Claude)
  • SRAM limits large context windows
  • Rate limits during peak demand