DeepSeek vs Groq
Comparing two ai & llm apis platforms on pricing, features, free tier, and trade-offs.
Quick summary
DeepSeek — Chinese open-weight frontier models. DeepSeek R1 is an open-weight reasoning model competitive with OpenAI's o1, at a fraction of the price. DeepSeek V3 is a strong general-purpose LLM.
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.
Feature comparison
| Feature | DeepSeek | Groq |
|---|---|---|
| Pricing model | Paid | Freemium |
| Starting price | Pay per token (cheap) | Pay per token |
| Free tier | No | Yes |
| Open source | Yes | No |
| Vision | No | Yes |
| Streaming | Yes | Yes |
| Embeddings | No | No |
| Max Output | 8K | 8K |
| Fine-tuning | No | No |
| Context Window | 128K | 128K |
| Flagship Model | DeepSeek V3 | Llama 3.3 70B |
| Reasoning Model | DeepSeek R1 | Llama 3.3 70B |
| Function Calling | Yes | Yes |
| EU Data Residency | No | No |
DeepSeek
Chinese open-weight frontier models
Pros
- Frontier reasoning at ~5% of OpenAI prices
- Open weights — can self-host
- Very competitive benchmarks
Cons
- China-based (geopolitical/compliance concerns for some)
- No vision yet
- Smaller SDK ecosystem
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
Which should you choose?
Choose DeepSeek if you value open source and want the option to self-host, and you need production-grade features and are ready to pay. Choose Groq if a free tier is important for your stage.