Groq vs Mistral AI
Comparing two ai & llm apis platforms on pricing, features, free tier, and trade-offs.
Quick summary
Groq — Ultra-fast LLM inference with LPU hardware. Groq runs open-source LLMs (Llama 3.3, Mixtral, Gemma) on custom LPU hardware, delivering 10-20x faster inference than GPU-based providers.
Mistral AI — European open-weight and commercial LLMs. Mistral AI offers both commercial API access (Mistral Large, Codestral) and open-weight models (Mistral 7B, Mixtral). EU-based with strong privacy posture.
Feature comparison
| Feature | Groq | Mistral AI |
|---|---|---|
| Pricing model | Freemium | Freemium |
| Starting price | Pay per token | Pay per token |
| Free tier | Yes | Yes |
| Open source | No | Yes |
| Vision | Yes | Yes |
| Streaming | Yes | Yes |
| Embeddings | No | Yes |
| Max Output | 8K | 8K |
| Fine-tuning | No | Yes |
| Context Window | 128K | 128K |
| Flagship Model | Llama 3.3 70B | Mistral Large 2 |
| Reasoning Model | Llama 3.3 70B | Mistral Large 2 |
| Function Calling | Yes | Yes |
| EU Data Residency | No | Yes |
Groq
Ultra-fast LLM inference with LPU hardware
Pros
- Insanely fast inference (500+ tokens/sec)
- Cheapest for open-source model inference
- Generous free tier
- Great for real-time UX
Cons
- No proprietary models — OSS only
- Lower peak quality vs GPT-4o/Claude
- Limited availability during demand spikes
Mistral AI
European open-weight and commercial LLMs
Pros
- Open-weight models available
- EU-based, strong GDPR posture
- Dedicated code model (Codestral)
- Competitive pricing
Cons
- Less capable than GPT-4o on most benchmarks
- Smaller ecosystem
- Documentation thinner
Which should you choose?
Choose Groq if a free tier is important for your stage. Choose Mistral AI if you value open source and want the option to self-host, and a free tier is important for your stage.