GroqvsPortkey

Full side-by-side comparison — features, pricing, platforms, and which one wins in 2026.

Groq

LLM APIs & Inference

The fastest AI inference platform — LPU-powered, 1000+ tokens/sec

Full review →Website ↗

Portkey

LLM APIs & Inference

AI gateway for reliable and fast LLM applications

Full review →Website ↗
FeatureGroqPortkey
CategoryLLM APIs & InferenceLLM APIs & Inference
PricingFree tier available, pay-per-token for productionFree + Pro plans
GitHub Stars—
✓ More stars
6k
PlatformsWebWeb, Docker
Key Features
  • ✓ LPU hardware — custom chips for inference, not repurposed GPUs
  • ✓ GPT OSS 120B at 500 tok/s ($0.15/M input)
  • ✓ GPT OSS 20B at 1000 tok/s ($0.075/M input)
  • ✓ Llama 4 Scout 17B at 750 tok/s with 131K context + vision
  • ✓ Qwen3-32B at 400 tok/s with 131K context
  • ✓ Compound AI systems with web search + code execution
  • ✓ Whisper transcription ($0.04-0.11/hour)
  • ✓ OpenAI-compatible API — drop-in replacement
  • ✓ Free developer tier: 250-300K TPM, 1K RPM
  • ✓ AI gateway
  • ✓ Fallbacks
  • ✓ Load balancing
  • ✓ Caching
  • ✓ Observability
Pros
  • + Fastest inference available (500-1000 tok/s)
  • + Free tier with generous limits (250K+ tokens/min)
  • + OpenAI-compatible API — swap one line of code
  • + Latest open-source models (GPT OSS, Llama 4, Qwen3)
  • + Compound AI for agentic workflows (search + code exec)
  • + Automatic fallbacks
  • + Load balancing
  • + Request caching
  • + Observability built-in
  • + Open-source gateway
Cons
  • − Cloud-only — cannot self-host LPU hardware
  • − Rate limits on free tier (1K RPM)
  • − Smaller model catalog than running locally via Ollama
  • − Added infrastructure layer
  • − Learning curve
  • − Some features need Pro
  • − Latency overhead
Tags
inferencefastfreehardware
gatewayreliabilityobservabilityapi

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