Groq

Groq is an inference platform for developers and teams that need fast, low-cost model serving through the Groq LPU and GroqCloud. It offers OpenAI-compatible API access, on-demand model pricing, prompt caching, batch processing, and an enterprise path for larger deployments.

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What Groq is

Groq is an inference platform built around the Groq LPU, a custom chip and software stack focused on running AI models quickly and at a predictable cost. The site positions GroqCloud as the developer-facing service for accessing models and inference, with OpenAI-compatible API access and support for starting quickly from existing code.

The product is aimed at developers and teams that need low-latency model responses, scalable inference, and pricing that is described as linear and predictable. The pricing page shows on-demand access to openly available models, prompt caching, built-in tools for compound systems, and a Batch API for large workloads, while the enterprise pages add deployment optionality and dedicated support for larger organizations.

Core capabilities

LPU-based inference architecture

Groq’s LPU is a custom inference chip designed for deterministic, token-based execution. The architecture page says the design removes traditional software complexity and aims to keep performance predictable.

Model access across text, audio, and vision

The pricing page shows on-demand access to multiple openly available models, including GPT-OSS, Llama, Qwen, Kimi, and Whisper variants, with model-specific token pricing.

Prompt caching pricing

Groq documents prompt caching with separate cached and uncached input token pricing. The page notes there is no extra fee for the caching feature itself, and the discount applies when a cache hit occurs.

Built-in tool use for compound systems

Compound AI systems can use built-in tools such as web search, visit website, code execution, and browser automation. Pricing is passed through to the underlying models and server-side tools.

Asynchronous batch processing

Batch API supports asynchronous large-scale request processing, with a stated 50% lower cost, no impact to standard rate limits, and a 24-hour to 7 day processing window.

OpenAI-compatible API access

The site states Groq’s API is OpenAI compatible and can be started with just a few lines of code using the Groq base URL and API key.

Common ways teams use Groq

Real-time conversational apps
Teams building chat or assistant products can use GroqCloud to serve model responses with low latency and predictable per-token pricing, especially when response time affects the user experience.
Fast API migration
Developers who already use OpenAI-style client libraries can switch to Groq by changing the base URL and using the Groq API key, which lowers migration friction.
Tool-using AI workflows
Products that need retrieval, web lookup, or code execution can use compound AI systems with built-in tools such as web search, visit website, and code execution.
High-volume batch workloads
Organizations running large jobs can use the Batch API to process requests asynchronously at lower cost without affecting standard rate limits.
Enterprise inference deployments
Enterprises with custom capacity, deployment, or support needs can route through the Enterprise API Solutions flow for larger-scale inference planning.

Pros and Cons

Pros

Provides fast inference infrastructure with a clear focus on latency and cost.
Supports multiple openly available models with model-specific pricing.
Includes prompt caching to reduce input-token cost on cache hits.
Offers built-in tools and batch processing for larger or more complex workloads.
Provides an enterprise path for larger deployments and deployment optionality.

Cons

The public pages do not provide detailed integration coverage beyond OpenAI-compatible access and a few code lines.
The site does not publish a complete list of supported SDKs, cloud integrations, or deployment patterns on the pages provided.
Enterprise API Solutions and some models require contacting sales rather than self-serve checkout.

FAQ

What is Groq used for?

Groq provides inference infrastructure for developers and teams that need fast, low-cost model serving. The site shows OpenAI-compatible access and supports starting with a small code change using the Groq API base URL.

What can developers do with GroqCloud?

The pricing page lists core model access, enterprise-only models, prompt caching, built-in tools, and batch API processing. The home page also points to GroqCloud as the place developers use for inference.

Does Groq offer only the models shown on the pricing page?

The pricing page shows on-demand pricing for several openly available models and indicates that other models are available for specific customer requests, including fine-tuned models.

Is there an enterprise option?

Yes. The enterprise page offers an Enterprise API Solutions flow for larger deployments, custom solutions, and dedicated support, and it also mentions deployment optionality.

Can teams get started without an enterprise contract?

The site says you can start for free and upgrade as needs grow, and the pricing page includes a contact path for enterprise API solutions or on-prem deployments.