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AI Tool Comparison
Fireworks AI vs Groq
A side-by-side breakdown to help you pick the right tool for your workflow.
Review Score assesses product quality; Fit Score is specific to a use case. Limited reviews do not establish overall product quality. How reviews work.
Fireworks AI
Run Llama, Mixtral, and 50+ open-source models at production speed: model-specific token billing with the same SDK you're already using.
Models
paid
Groq
Run Llama, Qwen, and open GPT-OSS models on custom LPU chips for very low-latency, high-throughput inference at a fraction of typical GPU token costs. Reports of a $20B Nvidia asset acquisition surfaced in 2026, though Groq continues operating independently.
Developer Tools
freemium
Bottom Line
Catalog updated: August 2026
Fireworks AI (Models) and Groq (Developer Tools) come from different corners of the market, so this usually comes down to which job you're actually hiring a tool for, not a head-to-head on the same task. Fireworks AI runs on a paid-only plan while Groq runs on a freemium model, which alone may settle it if budget or a free tier is a hard requirement.
Choose Fireworks AI if…
Best for developers who need fast, cheap inference on open-source models without sacrificing production reliability, and its edge is latency that consistently beats cloud providers, with model- and serving-tier-specific token pricing. A genuinely strong value pick for open-source inference, the free credit is too small to test real production load. Lean toward Groq instead if custom inference chips that generate tokens 10 to 25 times faster than typical GPU-based inference matters more for your use case.
Choose Groq if…
Best for developers building applications where response speed matters more than model selection breadth, and its edge is custom inference chips that generate tokens 10 to 25 times faster than typical GPU-based inference. A genuine speed advantage worth building around, the model selection is narrower than a general-purpose API. Lean toward Fireworks AI instead if latency that consistently beats cloud providers, with model- and serving-tier-specific token pricing matters more for your use case.
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| Attribute | Fireworks AI | Groq |
|---|---|---|
| Category | Models | Developer Tools |
| Pricing | paid | freemium |
| Pricing Detail | GPT OSS 120B Serverless Standard (USD) / $0.15/1M uncached input tokens / $0.015/1M cached-input tokens / $0.60/1M output tokens | Free tier / pay-as-you-go from $0.05/M tokens |
| TWF Review Score | Not yet reviewed | Not yet reviewed |
Key Features
Fireworks AI
- OpenAI-compatible API for instant drop-in replacement
- 50+ open-source models including Llama, Mixtral, and Gemma
- Compound AI system deployment (multiple models in one call)
- Function calling and JSON mode across all supported models
- Fine-tuning API for custom model specialization
- Sub-100ms time-to-first-token on most models
Groq
- Very low-latency inference
- OpenAI-compatible API
- Popular open models hosted
- Generous free tier
Pros
Fireworks AI
- •Best-in-class latency for open-source model inference
- •Separate input, cached-input, and output token rates support cost estimation
- •OpenAI-compatible API means zero migration effort
Groq
- •Blazing fast responses
- •Easy drop-in API
- •Cost-effective
Cons
Fireworks AI
- Smaller model selection than OpenRouter
- Fine-tuning has limited base model options vs dedicated platforms
- Free credit is small, production workloads require billing setup
Groq
- Limited model selection
- Capacity constraints at peak
