GroqvsNinjaChat

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 ↗

NinjaChat

Chat Interfaces

31+ free AI tools online — no signup required

Full review →Website ↗
FeatureGroqNinjaChat
CategoryLLM APIs & InferenceChat Interfaces
PricingFree tier available, pay-per-token for productionFree (no signup), premium plans available
GitHub Stars——
PlatformsWeb—
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
    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)
    • + No signup required
    • + 30+ tools in one place
    • + Free to use
    • + Browser-based
    Cons
    • − Cloud-only — cannot self-host LPU hardware
    • − Rate limits on free tier (1K RPM)
    • − Smaller model catalog than running locally via Ollama
    • − Cloud-only (no self-hosting)
    • − Limited customization
    Tags
    inferencefastfreehardware

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