G
Groq
development
Blazing-fast AI inference using custom LPU hardware. Run Llama, Mixtral, and other models at 800+ tokens per second.
Rating
4.6/5
Pricing
Free tier or open source
Trial
Free trial available
Developer comparison
Groq vs Together AI
Compare pricing, setup effort, workflow fit, privacy and control, feature depth, and the tradeoffs that matter when software teams add AI tools to a real stack.
T
Together AI
development
Platform for running, fine-tuning, and building with open-source AI models. Fast inference and training.
Rating
4.7/5
Pricing
Free tier or open source
Trial
Free trial available
Decision matrix
The comparison is about fit, not a universal winner.
Workflow Fit
Developer, automation, API, agent, and repo-context signals.
Groq9/10
Together AI9/10
Feature Depth
Breadth of listed features and capabilities in the tool index.
Groq8/10
Together AI8/10
Pricing Clarity
Free/open-source availability, listed starting price, and relative cost.
Groq10/10
Together AI10/10
Control and Privacy
Open-source, local, self-hosted, deployment, and privacy signals.
Groq9/10
Together AI9/10
Index Rating
Current NeuralStackly rating normalized to a 10-point scale.
Groq9/10
Together AI9/10
At a glance
Quick comparison table
Factor
Groq
Together AI
Category
development
development
Starting Price
Free tier or open source
Free tier or open source
Free Trial
Free trial available
Free trial available
Best Fit
Real-time chat applications
Production LLM inference
Primary Watchout
Limited model selection compared to competitors
Can be overwhelming choice paralysis
Choose Groq if...
Real-time chat applications
High-throughput batch processing
Latency-sensitive AI features
Production LLM inference at scale
Watchouts
Limited model selection compared to competitors
Rate limits on free tier can be restrictive
Enterprise pricing not transparent
Choose Together AI if...
Production LLM inference
Custom model fine-tuning
AI product development
Research with open models
Watchouts
Can be overwhelming choice paralysis
Some models still maturing
Enterprise features require contact
Rollout checklist
Validate the stack before rollout.
Run a real workflow
Test the tool on one actual repo, prompt set, or automation path.
Check data boundaries
Confirm retention, permissions, private context, and admin controls.
Estimate operating cost
Model subscription, token, seat, hosting, and support costs together.
Define review points
Decide where humans approve changes before the tool affects production.
Need help turning the comparison into a working stack?
Use the stack builder for a shortlist, or request setup help if the decision involves agents, provider routing, messaging apps, or automation.