Fireworks AI vs Groq: LLM APIs Comparison (2026)
Fireworks AI offers more granular control over model deployment and customization, while Groq emphasizes speed and predictable pricing. Both provide a free tier for initial exploration.
AI Citation Scorecard
How often each is cited by major AI engines when buyers ask llm apis questions. Last 90 days across ChatGPT, Perplexity, Gemini, Claude, and Copilot.
Probes run hourly; each (engine × query) combo retests every ~3 days.
Pricing
Key Features
- ✓Serverless Inference
- ✓Fine Tuning
- ✓On Demand Deployments
- ✓High rate limits
- ✓Batch inference priced at 50%
- ✓Pay per token pricing
- ✓Pay per GPU second
- ✓Customizable open models
- ✓Fast responses
- ✓Scalable performance
- ✓Predictable pricing
- ✓No surprise inference bills
When to choose Fireworks AI
You require features like serverless inference, fine-tuning, on-demand deployments, and customizable open models. Fireworks AI also offers specific pricing models such as pay-per-token and pay-per-GPU second, with batch inference priced at 50%.
When to choose Groq
You prioritize fast responses, scalable performance, and predictable pricing, with a focus on avoiding surprise inference bills. Groq also highlights affordable token pricing and support for multiple AI models.