Groq - Fast low cost AI inference with dedicated LPU chip

What is Groq: AI Inference Built for Speed and Scale

If you've ever struggled with slow AI response times or unpredictable costs when running language models in production, you're not alone. These challenges are exactly why Groq exists—and why over 300,000 developers and teams have already made the switch.

Traditional GPU-based inference was never designed for the real-time demands of modern AI applications. When you're building chatbots that need instant responses, detection systems that must analyze content in milliseconds, or interactive experiences where every millisecond counts, the limitations of repurposed training hardware become painfully obvious. Costs spiral unpredictably, latency varies wildly, and scaling feels like fighting against the architecture itself.

Groq is different. We're the creators of the world's first LPU (Language Processing Unit)—a chip specifically engineered from the ground up for AI inference, not an adaptation of graphics processing technology. This isn't a incremental improvement; it's a fundamental architectural shift that delivers the speed and cost predictability that production AI applications demand.

The LPU advantage starts with our unique design: a single-core architecture paired with hundreds of megabytes of on-chip SRAM as the primary weight storage, eliminating the memory bottlenecks that plague GPU solutions. Our proprietary compiler handles static scheduling, ensuring deterministic execution—meaning you get consistent, predictable latency every single time, not the variable performance that makes capacity planning a nightmare.

This architecture has earned the trust of industry leaders. Companies like Dropbox, Vercel, Canva, Robinhood, Riot Games, Workday, Ramp, and Volkswagen rely on Groq for their most demanding AI workloads. The market has taken notice: in September 2025, we closed a $7.5 billion funding round to accelerate our mission of making fast, low-cost inference accessible to every developer.

Whether you're a startup building your first AI product or an enterprise migrating from legacy solutions, Groq delivers the performance edge that separates exceptional user experiences from frustrating ones.

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Groq's Core Features: What You Can Actually Use

Every feature at Groq exists to solve a real problem. Here's how our capabilities translate into practical value for your projects.

GroqCloud is our inference platform—global data center deployment powered by LPU architecture delivering the low-latency responses your users expect. Whether you're running customer service chatbots, content moderation systems, or real-time analytics, GroqCloud scales with your needs without the infrastructure headaches.

The LPU chip itself represents everything we believe inference hardware should be: a purpose-built processor with single-core architecture and on-chip SRAM that handles weights directly, eliminating external memory bottlenecks. Our self-developed compiler performs static scheduling, giving you deterministic execution—same latency for the same request, every time. This predictability transforms how you design and deploy AI systems.

OpenAI Compatible API makes migration surprisingly simple. If you're already using OpenAI, switching to Groq takes just two lines of code—change your base URL to https://api.groq.com/openai/v1 and you're ready. No rewrites, no refactoring, just better performance and lower costs.

Prompt Caching addresses a common pain point: repeated context in long conversations. When your cached prompts hit, you get a 50% discount automatically. For applications with extensive system prompts or multi-turn dialogues, this adds up quickly.

Need to process large batches asynchronously? Batch API offers 50% off standard pricing with processing windows from 24 hours to 7 days—perfect for offline inference workloads that don't need immediate results.

For voice applications, our Whisper V3 models deliver transcription at 217-228x speed, while Orpheus TTS synthesizes speech at 100 characters per second across multiple languages.

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Who Is Using Groq: Real Results Across Industries

Don't just take our word for it—here's how teams across sectors are actually using Groq to solve real problems.

AI Detection & Verification is where Groq truly shines. GPTZero, the popular AI detection platform, migrated to GroqCloud and achieved 7x faster inference while cutting costs by 50%—and maintained their 99% accuracy standard. Today they serve over 10 million users with Groq powering their real-time detection. If you're building any AI detection system, this level of performance directly translates to better user experiences.

In financial services, Fintool transformed their customer experience. After switching to Groq, chat speed improved 7.41x and costs dropped by 89%. For financial applications where every second of delay impacts user satisfaction and ultimately revenue, these improvements are transformative.

Sports analytics demands real-time insights, and Stats Perform found exactly that with Groq—their inference runs 7-10x faster than any competitor solution. When you're processing sports data for live applications, that speed difference means the difference between insights that arrive in time and ones that arrive too late.

Gaming companies face unique challenges: players expect instant responses. ReBlink uses Groq to power AI voice interactions in games, achieving 7x faster command response times, 60% higher user adoption rates, and—remarkably—14x lower costs per game session. That's the kind of efficiency that changes business models.

News and intelligence teams at Perigon process millions of articles daily using Groq, achieving 5x performance improvements. For any application dealing with large-scale content processing, Groq's throughput directly enables capabilities that would otherwise be cost-prohibitive.

Mem0, which handles AI memory and context management, reduced latency by nearly 5x using Groq—critical when you're building real-time applications where context retrieval speed directly impacts response quality.

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The Technology Behind Groq: Why LPU Changes the Game

Understanding why Groq performs so differently requires understanding our architecture. This isn't a chip designed for graphics rendering that got repurposed for AI—it's something entirely new.

We invented the LPU in 2016 specifically to solve the inference problem. While others were building bigger GPUs and trying to make training chips handle inference, we saw a fundamental opportunity: inference has different characteristics than training, and dedicated hardware could deliver dramatically better results.

The single-core + on-chip SRAM architecture is central to this. We built hundreds of megabytes of SRAM directly onto the chip to store model weights. This eliminates the most significant bottleneck in GPU inference—the constant back-and-forth with external memory. Your weights are right there where the computation happens, not waiting to be fetched across a memory bus.

Our proprietary compiler handles the orchestration. Unlike GPU solutions that rely on dynamic scheduling (figuring out what to do next as they go), Groq's compiler performs static analysis ahead of time. It knows exactly what needs to happen and when, ensuring deterministic execution. Send the same request, get the same latency—every time. This predictability is revolutionary for production systems that need to make guarantees to their users.

Scaling is equally innovative. We developed a plesiosynchronous protocol that coordinates hundreds of LPU chips working in parallel, connected directly to each other without complex switching infrastructure. Our air-cooling design means you don't need the exotic liquid cooling setups that GPU clusters require—simpler infrastructure, lower costs, easier deployment.

The performance numbers speak for themselves:

• Llama 3.1 8B Instant: 840 tokens per second
• GPT-OSS 20B: 1,000 tokens per second—our fastest model
• Llama 4 Scout: 594 tokens per second
• Qwen3 32B: 662 tokens per second
• Whisper V3 Large: 217x transcription speed
• Whisper Large v3 Turbo: 228x transcription speed

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Groq Pricing: Transparent Costs You Can Plan With

One of the most refreshing aspects of Groq is our commitment to complete pricing transparency. No hidden fees, no surprise bills, no complicated tier structures that require a spreadsheet to understand. What you see is what you pay.

LLM Pricing (Pay-As-You-Go)

Voice Model Pricing

Tools & Utilities

Cost-Saving Options

Batch API: Need to process large volumes without real-time requirements? Batch processing delivers 50% off standard pricing with flexible 24-hour to 7-day processing windows.

Prompt Caching: Automatically applied when your cached prompts hit—50% discount on repeat context without any configuration.

Choosing Your Plan

• Individual Developers: Start with pay-as-you-go pricing—free API keys available at console.groq.com, and the free tier lets you experiment before scaling
• Growing Teams: The cost savings from Batch API and Prompt Caching compound quickly at volume
• Enterprise: Custom pricing with dedicated support, guaranteed capacity, and tailored SLAs

Our pricing philosophy is simple: you should be able to calculate your costs before running a single token. No surprises, no mysteries—just straightforward pricing for high-performance inference.

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Frequently Asked Questions