

Groq and OpenAI API are both Large Language Models tools. Compare features, pricing, and ratings below to find the best fit for your team.
The question that matters: “In what situation will I regret choosing A over B after 3 months?”
Groq's LPU delivers Llama 3 inference at 750+ tokens per second, enabling pipelines where Whisper transcription feeds directly into an LLM analysis step with a total round-trip under 500ms.
Groq's time-to-first-token under 100ms enables natural-feeling voice conversational interfaces where LLM response latency is the bottleneck, not TTS or ASR.
Groq's per-token cost on Llama 3 8B is under $0.06 per million tokens, making high-volume classification or extraction tasks that previously required GPU servers economically viable via API.
speech-to-text API transcribes inbound calls; LLM categorizes urgency and routes tickets in a single API call. Batch API handles off-peak volume spikes without extra infrastructure.
The Embeddings API indexes internal knowledge bases weekly. A team chat bot queries semantically at $0.02 per 1,000 embeddings - no infrastructure rebuild needed.
Best for: 14,400 req/day is enough for dev and low-traffic apps - start here before paying anything.
Best for: Get full access to GPT-4o and GPT-4 with token-based billing and no monthly base fee ($0/mo)
Best for: This plan offers provisioned throughput, enterprise-grade security, and custom rate limits
Batch API: 50% discount on all models. Cached input tokens: 50% discount (GPT-4o, o-series). Pricing as of May 2026.
15 differences found across 33 standardized features
Evaluative strengths and weaknesses: not feature lists
Groq added a new "Developer" plan (Custom pricing)
Plan added · May 30, 2026
Groq removed the "Pay-as-you-go" plan
Plan removed · May 30, 2026
Groq added a new "Enterprise" plan
Plan added · May 21, 2026
Plan removed · May 21, 2026
Plan added · May 21, 2026
Plan added · May 21, 2026