Groq vs Together AI: Comparison for Fast LLM Inference
Compare Groq and Together AI on speed, model selection, and price. Discover which inference platform best fits your real-time AI applications.
Groq
Groq uses custom LPU (Language Processing Unit) hardware for extremely fast inference. Known for Llama and Mixtral with very low latency — often 10x faster than GPU. Free tier available, popular for real-time chat.
Together AI
Together AI offers inference for open-source models (Llama, Mistral, DeepSeek, Qwen, etc.) on their cloud. Broad model selection, RedPajama datasets, and Together Inference for low latency. Pay-per-use pricing.
Comparison table
| Feature | Groq | Together AI |
|---|---|---|
| Hardware | LPU — custom inference chips | GPU cloud — NVIDIA, custom |
| Speed | Extreme — often fastest inference | Fast — competitive with other GPU providers |
| Models | Llama, Mixtral — limited selection | 100+ models — Llama, Mistral, DeepSeek, Qwen |
| Free tier | Free tier, rate limits | Free credits, then pay-per-use |
| Fine-tuning | Not directly | Together Fine-tuning available |
| API compatibility | OpenAI-like API | OpenAI-compatible, own endpoints |
Verdict
Groq wins on pure inference speed for Llama/Mixtral. Together AI wins on model choice and fine-tuning. For real-time chat with Llama: Groq. For breadth and custom models: Together AI.
Our recommendation
AVARC Solutions uses Groq for real-time chat and demos where latency matters. Together AI for projects needing multiple models or fine-tuning. Both are excellent complements alongside OpenAI/Anthropic.
Frequently asked questions
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