E2BvsGroq

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

E2B

Developer Tools

Secure cloud sandboxes for AI-generated code execution

Full review →Website ↗

Groq

LLM APIs & Inference

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

Full review →Website ↗
FeatureE2BGroq
CategoryDeveloper ToolsLLM APIs & Inference
PricingFree tier, pay-per-use for productionFree tier available, pay-per-token for production
GitHub Stars
✓ More stars
8k
—
Platforms—Web
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
    • + Millisecond sandbox startup
    • + Full Linux environment per sandbox
    • + SDKs for Python and JavaScript
    • + Secure code execution for AI agents
    • + 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)
    Cons
    • − Cloud-only (no self-hosted option)
    • − Costs scale with usage
    • − Cloud-only — cannot self-host LPU hardware
    • − Rate limits on free tier (1K RPM)
    • − Smaller model catalog than running locally via Ollama
    Tags
    inferencefastfreehardware

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