AI Tool Comparison
Groq vs Together AI
A side-by-side breakdown to help you pick the right tool for your workflow.
Groq
Run Llama and Qwen 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.
Together AI
Run, fine-tune, and scale open-source models: start on cheap shared inference and graduate to dedicated GPUs (including on-demand B200s) as traffic grows.
Bottom Line
Last reviewed: August 2026
Groq and Together AI both compete in Developer Tools, overlapping most directly on developer Tools. Groq carries the higher rating (4.6 vs 4.5), but a gap that size rarely overrides a real workflow fit on its own.
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.
Choose Together AI if…
Best for developers who want to run, fine-tune, or deploy open-source models via API without managing GPU infrastructure, and its edge is a catalog of 200+ open models across major families, all accessible through one OpenAI-compatible interface. Competitive pricing and real production scale, usage costs are worth modeling before committing to heavy workloads.
| Attribute | Groq | Together AI |
|---|---|---|
| Category | Developer Tools | Developer Tools |
| Pricing | freemium | freemium |
| Pricing Detail | Free tier / pay-as-you-go from $0.05/M tokens | Pay-as-you-go from $1.04/M tokens / dedicated GPUs from $6.49/hr |
| Rating |
Key Features
Groq
- Very low-latency inference
- OpenAI-compatible API
- Popular open models hosted
- Generous free tier
Together AI
- Inference for 200+ open models
- Fine-tuning and training
- OpenAI-compatible API
- Dedicated endpoints
Pros
Groq
- •Blazing fast responses
- •Easy drop-in API
- •Cost-effective
Together AI
- •Broad open-model catalog
- •Scales for production
- •Competitive pricing
Cons
Groq
- Limited model selection
- Capacity constraints at peak
Together AI
- Usage costs add up
- Less consumer-facing