Groq is fast.
PolarGrid is faster
where it counts.
Groq's LPU silicon delivers unmatched raw token throughput — 1,665 tok/s. But for voice AI, what matters is end-to-end latency from your user to first audio byte. PolarGrid wins that race: 205 ms e2e TTFT vs Groq's ~310 ms, plus a full co-located STT→LLM→TTS pipeline Groq simply doesn't offer.
PolarGrid numbers from live benchmarks · see full methodology →
Feature comparison
Side by side
Use cases
When to use PolarGrid
Voice AI agents
Need full STT+LLM+TTS pipeline co-located for sub-400ms e2e. Groq only offers LLM — you'd still need separate services for voice.
Real-time conversational AI
E2e latency matters more than raw throughput for conversation. 205ms vs 310ms TTFT means a noticeably more responsive user experience.
Custom model hosting
Bring your own fine-tuned models and host them on PolarGrid's edge nodes. Groq's custom model support is limited.
Honest take
When Groq might be better
We built PolarGrid for voice AI and low-latency use cases. Groq built specialized silicon for raw throughput. Here's where their approach genuinely wins:
Pure text generation at massive throughput
Groq's LPU silicon is genuinely unmatched at raw tok/s — 1,665 tok/s vs our 29.4. If you're doing batch text generation and need maximum throughput, Groq wins.
Batch processing pipelines
If you need 1000+ tok/s and don't care about voice or real-time interaction, Groq's LPU architecture is purpose-built for this workload.
Start with $500 free
No credit card required. OpenAI-compatible API. Full voice pipeline included.