Groq vs Together AI

Detailed side-by-side comparison to help you choose the right tool

Groq

🔴Developer

AI Model Hosting & Inference

AI inference cloud built on Groq's own LPU (Language Processing Unit) chips that serves open-weight LLMs, Whisper, and vision models at the lowest latency in the market, with an OpenAI-compatible API.

Was this helpful?

Starting Price

Custom

Together AI

🔴Developer

AI Model Hosting & Inference

AI-native cloud for inference, fine-tuning, and dedicated GPU clusters, offering 200+ open-source and frontier-class models behind an OpenAI-compatible API plus reserved H100/H200/B200 capacity.

Was this helpful?

Starting Price

$0.02/1M tokens

Feature Comparison

Scroll horizontally to compare details.

FeatureGroqTogether AI
CategoryAI Model Hosting & InferenceAI Model Hosting & Inference
Pricing Plans171 tiers142 tiers
Starting Price$0.02/1M tokens
Key Features
  • Very low-latency LLM inference through GroqCloud
  • OpenAI-compatible style developer workflows for chat and agents
  • Support for popular open models such as Llama, Mixtral-style, and Whisper-class workloads as available
  • Serverless inference APIs for open and proprietary model workloads
  • Batch Inference API for large asynchronous token processing jobs
  • Fine-tuning platform for shaping open models with private or domain data

Groq - Pros & Cons

Pros

  • Custom LPU silicon delivers tokens-per-second that is typically 5–10x faster than GPU baselines on open LLMs
  • OpenAI-compatible API plus a generous free developer tier make adoption a base-URL change away
  • Per-token pricing on Llama-class models is at or below the open-model market while latency stays predictably low

Cons

  • Model catalog is curated, not exhaustive — niche fine-tunes are easier to find on Together or Fireworks
  • No first-party fine-tuning service today, so custom models must be trained elsewhere and may not port to LPU
  • Capacity for popular models can be rate-limited during demand spikes; dedicated/Enterprise mitigates but adds cost

Together AI - Pros & Cons

Pros

  • Breadth of open-weight model catalog (200+) with one OpenAI-compatible API
  • One account spans serverless, dedicated endpoints, fine-tuning, and reserved GPU capacity
  • Transparent per-token pricing — easy to model unit economics against closed providers
  • InfiniBand-backed GPU Clusters are credible for real training, not just inference

Cons

  • Frontier-class reasoning still lags closed models on the hardest benchmarks
  • Fastest single-model latency is sometimes beaten by Groq or Cerebras
  • Many model variants means model selection itself becomes a project
  • Dedicated endpoint cost calculations require attention to GPU type and utilization

Not sure which to pick?

🎯 Take our quiz →

🔒 Security & Compliance Comparison

Scroll horizontally to compare details.

Security FeatureGroqTogether AI
SOC2✅ Yes
GDPR✅ Yes
HIPAA
SSO
Self-Hosted❌ No
On-Prem❌ No
RBAC
Audit Log
Open Source❌ No
API Key Auth✅ Yes
Encryption at Rest✅ Yes
Encryption in Transit✅ Yes
Data ResidencyUS
Data Retentionconfigurable
🦞

New to AI tools?

Read practical guides for choosing and using AI tools

🔔

Price Drop Alerts

Get notified when AI tools lower their prices

Tracking 2 tools

We only email when prices actually change. No spam, ever.

Get weekly AI agent tool insights

Comparisons, new tool launches, and expert recommendations delivered to your inbox.

No spam. Unsubscribe anytime.

Ready to Choose?

Read the full reviews to make an informed decision