Groq
Fast, low‑cost AI inference powered by a purpose‑built Language Processing Unit (LPU)
What is Groq?
Groq is a U.S.-based AI infrastructure company founded in 2016 by former Google engineers, specializing in inference‑focused hardware and software. At its core is the Language Processing Unit (LPU), a purpose‑built inference ASIC designed for low latency, high throughput execution of generative AI workloads. In February 2024, Groq soft‑launched GroqCloud™, a self‑serve API platform granting real‑time access to Groq’s LPU infrastructure. Groq supports multiple input and output modalities—including text, speech-to-text, text-to-speech, and models across vision and reasoning—delivered via pay‑per‑token and tiered plans. It continues operating independently despite a December 2025 non‑exclusive IP licensing agreement with Nvidia.
What you can do with it
Real‑time chatbots and agent backends
Provides millisecond‑scale token generation that enhances responsiveness in conversational applications.
Voice assistants with rapid feedback
Handles speech‑to‑text and text‑to‑speech workloads with high throughput for fluid voice interactions.
Retrieval‑augmented systems and tool‑calling agents
Delivers consistent low latency for multi‑step, chain‑of‑thought AI workflows.
Latency‑sensitive deployment in regulated environments
Runs inference on‑prem via GroqRack for sectors requiring data localization and compliance.
Key features
- Purpose‑built Language Processing Unit (LPU) ASIC for inference
- Ultra‑low‑latency, deterministic execution with high token throughput
- Software‑first architecture enabling generic, model‑independent compilation
- Cloud and on‑prem deployment via GroqCloud and GroqRack
- OpenAI‑compatible API for seamless integration
- Supports text, audio, and vision models including LLMs, STT, TTS, image‑to‑text
- Predictable, pay‑per‑token pricing with batch‑processing discounts
Screenshots
Inputs / Outputs
Strengths & Limitations
Strengths
Dedicated inference hardware
LPU designed specifically for inference delivers dramatically lower latency and higher throughput than general‑purpose GPUs
Transparent, usage‑based pricing
Predictable cost model based on per‑token or character pricing, with free tier and volume discounts (batch, caching)
Multi‑modal support
Supports text, audio (STT/TTS), vision tasks via numerous open‑source models
High performance
Throughput benchmarks of 394–1,000 tokens/sec across models, outperforming typical GPU inference
Flexible deployment
Available via cloud (GroqCloud) or on ‑premise (GroqRack), suited for a range of environments
Developer‑friendly
Self‑serve playground, documentation, and API ease onboarding
Limitations
Open‑source model limitation
Only open‑source models supported; proprietary models like GPT‑4 or Claude not available
Free tier limits
Rate‑limited free access may constrain prototyping (e.g. 30 requests/min across models)
Enterprise complexity
Custom enterprise plans required for SLA, pricing, regional endpoints, or fine‑tuning, which may raise barriers
Dependency on LPU availability
Performance gains rely on Groq’s proprietary chips and infrastructure availability
Pricing & Plans
Model: Freemium
Free
Basic API access with community support and optional zero‑data retention
Developer
Higher token limits, chat support, batch processing, spend limits, prompt caching
Enterprise
Includes custom models, regional endpoints, performance tiers, scalable capacity, dedicated support
Free tier with rate‑limits; pay‑as‑you‑go per token/character pricing depending on model; batch API and prompt caching offer up to ~50% discounts; enterprise pricing by custom agreement
Who it's for
Ideal for
Developers or organizations needing low‑latency, cost‑efficient AI inference using open‑source models, whether for prototyping or production.
Not ideal for
Users requiring access to proprietary models (e.g. GPT‑4, Claude), or those constrained by strict rate limits without enterprise support.
What users say
- Speed and cost efficiency
- Transparent pricing
- Hardware differentiation
- Model support limitations
Prompts & Results
›Translate ‘Hello, world!’ into French.
Bonjour le monde !
›Transcribe: [audio clip of question]
(transcribed text output)
›Speak ‘Welcome to Groq’ in a natural English voice.
(audio output via Orpheus English model)
›Summarize the image [uploaded image].
(text summary of image content)
FAQ
What is GroqCloud?+
A self‑serve developer platform (soft‑launched February 19, 2024) providing API access to Groq’s LPU‑powered inference infrastructure.
What input/output formats does Groq support?+
Supports text generation, speech‑to‑text (e.g. Whisper), text‑to‑speech (e.g. Orpheus), and models with vision or multimodal capabilities.
How does Groq cost compare to alternatives?+
Input token pricing ranges from ~$0.05 to $0.59 per million tokens; output $0.08–0.79, significantly lower than proprietary LLM providers.
Can Groq handle on‑prem deployment?+
Yes—GroqRack enables on‑prem deployment of its LPU hardware for regulated or air‑gapped environments.
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