Groq vs Together AI: Inference & Compute Comparison
Compare Groq and Together AI side by side. Both are tools in the Inference & Compute category.
Updated March 9, 2026
The short answer
Choose Groq if exceptional inference speed with ultra-low latency using custom LPU hardware.
Choose Together AI if competitive pricing starting at USD 0.10 per million tokens.
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Quick Comparison
| Category | Inference & Compute | Inference & Compute |
| Pricing | Freemium | Usage-based |
| Best For | Developers building real-time AI applications where inference speed is the top priority | Developers and companies deploying open-source AI models in production |
| Website | groq.com | together.ai |
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Pros & Cons: Groq vs Together AI
- +Exceptional inference speed with ultra-low latency using custom LPU hardware
- +Highly competitive pricing—among the lowest per-token costs in the market
- +Batch API and Prompt Caching offer significant cost savings (50% discounts)
- +Linear, predictable pricing model with no hidden costs or idle infrastructure fees
- −Limited model fine-tuning options compared to training-focused platforms
- −Smaller model selection compared to comprehensive cloud providers
- −Enterprise features like GroqRack require custom contracts and sales engagement
- −Newer platform with less extensive documentation than established providers
- +Competitive pricing starting at USD 0.10 per million tokens
- +50 percent discounts on batch inference and prompt caching
- +Strong backing from NVIDIA and Salesforce Ventures
- +Flexible deployment with both serverless and dedicated options
- −Focused on open-source models may limit access to proprietary models
- −Per-minute billing for dedicated GPUs can be complex to predict
- −Newer platform with less extensive documentation than established providers
- −Pricing varies significantly by model making cost planning difficult
Pricing: Groq vs Together AI
- · Limited usage
- · Pay-per-token
- · Access to multiple models
- · Community support
- · No minimum spend
- · Batch API (50% discount)
- · Prompt Caching (50% off cache hits)
- · Linear, predictable pricing
- · GroqRack deployment
- · Custom-tuned models
- · Dedicated support
- · Custom contracts
- · Pay-as-you-go
- · Multiple open-source models
- · USD 5 free credit
- · Llama 3 70B at USD 0.90/M tokens
- · Bulk processing discount
- · Async execution
- · Cost optimization
- · H100, H200 GPUs
- · Reserved capacity
- · Production workloads
- · Custom pricing
When to Choose Groq vs Together AI
- Real-time AI applications needing lowest latency
- Interactive conversational AI
- High-throughput batch inference
- Hosting open-source LLMs in production
- Fine-tuning models on custom data
- Cost-efficient inference at scale
About Groq
Groq is an AI infrastructure company founded in 2016 by former Google engineers, including Jonathan Ross (one of the designers of Google's Tensor Processing Unit) and Douglas Wightman. Headquartered in Mountain View, California, Groq provides specialized AI compute solutions focused on accelerating AI inference workloads using its custom-built Language Processing Unit (LPU) hardware. The company's platform offers some of the most competitive pricing in the AI inference market, with ultra-low latency and exceptional throughput. Groq provides access to models from multiple providers including OpenAI, Anthropic, Google, Cohere, and Mistral through a pay-as-you-go model charging per token consumed. The company offers three billing tiers—Free, Developer, and Enterprise—with additional cost-saving features like Batch API (50% discount) and Prompt Caching (50% discount on cache hits). With offices across North America and Europe, Groq has established itself as a leading alternative to traditional cloud GPU providers, particularly for teams optimizing for inference speed and cost efficiency.
About Together AI
Together AI is a cloud-based platform for building with open-source generative AI, founded on June 11, 2022 in San Francisco by Ce Zhang, Chris Re, Percy Liang, and Vipul Ved Prakash. The company raised USD 305 million in Series B funding in 2025 with participation from industry leaders including NVIDIA and Salesforce Ventures. Together AI provides serverless inference with pay-as-you-go pricing starting from USD 0.10 per million tokens for small models and USD 0.90 for Llama 3 70B, with a free USD 5 credit to start. The platform offers a 50 percent discount on batch inference and 50 percent savings on prompt caching for repetitive queries. For teams requiring dedicated resources, Together AI provides GPU endpoints billed per minute, with high-end H100 and H200 GPUs available. The platform specializes in open-source model deployment and provides instant GPU clusters for training and inference workloads. Together AI has become a leading platform for teams building with open-source AI models, offering both serverless convenience and dedicated infrastructure options.
What is Inference & Compute?
Platforms that provide GPU compute, model hosting, and inference APIs. These companies serve open-source and third-party models, offer optimized inference engines, and provide cloud GPU infrastructure for AI workloads.
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