---
type: entity
subtype: organization
title: "Groq"
description: "A fast inference provider Cole recommends (with a Llama model) when you need speed over raw power."
resource: "https://groq.com"
tags: [inference, provider, llama, speed]
videos: [10-n8n-tips-in-10-minutes-to-10x-your-ai-automations, this-boltnew-fork-is-exploding-dont-miss-out-on-whats-happening, i-forked-boltnew-and-made-it-way-better, llama-32-is-insane-but-does-it-beat-gpt-as-an-ai-agent, the-hard-truth-about-hosting-your-own-llms, complete-guide-to-langserve-make-your-ai-agent-actually-useful, i-found-the-limits-of-the-most-popular-llms, ai-is-too-expensive-if-you-dont-do-this, new-llama-3-model-beats-gpt-and-claude-with-function-calling, i-will-win-the-nvidia-ai-agents-developer-contest]
created: 2026-07-21
updated: 2026-07-21
---

# Groq

Groq is the inference provider Cole reaches for when speed and cost matter more than raw model power, almost always paired with an open [Meta AI](./meta.md) Llama model. His rule of thumb is blunt: "if you need something that's absolutely fast and you don't need something that's super powerful I would go with Groq and go with a llama model" ([0:02:02]). It is "an AI company that builds infrastructure to help you work with any local model" ([0:00:00]), serving open weights at extreme throughput rather than training frontier models of its own.

Groq's pitch across the catalog is speed and price. "1,200 tokens per second that is insane... this is about 1,000 words per second roughly" ([0:04:21]), and "for using llama 370b we are going to be using Gro it is so cheap... it's like 11% of the price of GPT-4o for the input tokens and then 5% of the price for the output tokens" ([0:04:13]). Because "a lot of providers like Groq for example actually make their API for using their llms open AI compatible" ([0:06:12]), swapping to it is trivial, which is the practical face of [Provider Independence](../../concepts/provider-independence.md): "you don't have to change any code to go from Groq to anthropic or anthropic to open AI it is so so easy" ([0:03:43]). Cole uses it as the default LLM in projects like his Nvidia contest agent, "right now I'm just using Groq uh with llama for the llm" ([0:05:52]), and in his Bolt.new fork alongside "a bunch of Groq models here if you wanted to use like llama 3.1 or 3.2." He also stress-tests it: Groq shipped a Llama fine-tune "specifically designed for function calling," but in his limits video "this finetune version llama 3 even though it is meant for function calling is failing here it's not giving good arguments" ([0:28:01]), a reminder that raw speed does not guarantee reliable [Tool Use](../../concepts/tool-use.md).

## Works with

- [Meta AI](./meta.md) - Cited as an example of a model trained with ~10x fewer parameters than GPT, pointing toward faster/cheaper training.

## Contrasts with

- [OpenAI](./openai.md) - Maker of GPT-4o mini (affordable-but-strong chat model) and text-embedding-3-small (recommended RAG embedding model).
- [Anthropic](./anthropic.md) - Maker of Claude and Claude Code, creator of MCP, and Cole's pick for the best coding LLM and the lab whose research most shapes his practice.
- [Together AI](./together-ai.md) - Pay-per-token inference provider serving open models like Llama 3.1; cheaper on its lite 70B variant but pricier than Groq once you want turbo-speed inference.

## Related

- [Model Selection](../../concepts/model-selection.md) - Choosing the right LLM per task by trading off quality, speed, and cost, often routing easy requests to cheap models and hard ones to expensive models.
- [Provider Independence](../../concepts/provider-independence.md) - Architecting agents so the underlying model, framework, or client can be swapped without a rewrite, avoiding lock-in through low-level abstractions.
- [Tool Calling](../../concepts/tool-use.md) - Letting an LLM invoke external functions and APIs so it can take actions and fetch data beyond its parametric knowledge.
- [Local & Self-Hosted AI](../../concepts/local-ai.md) - Running open-weight models on your own hardware or cloud for privacy, cost control, and independence from API providers.
- [Agentic Workflow Engineering](../../concepts/agentic-workflow-engineering.md) - Designing repeatable AI workflows as engineered systems with defined steps, orchestration, and background execution rather than ad-hoc prompting.
- [Retrieval-Augmented Generation (RAG)](../../concepts/rag.md) - Grounding an LLM's answers by retrieving relevant documents from an external knowledge base and injecting them into the prompt at query time.
- [Nvidia](./nvidia.md) - Co-sponsor of the AI agents developer contest whose technologies Cole must integrate to qualify.
- [Mistral](./mistral.md) - French AI lab and LLM provider whose models were added to the bolt.new fork as a first-class API integration by popular community request.

## Sources

- [10 n8n Tips in 10 Minutes to 10x Your AI Automations](../../sources/10-n8n-tips-in-10-minutes-to-10x-your-ai-automations.md) - "[0:02:02] if you need something that's absolutely fast and you don't need something that's super powerful I would go with Groq and go with a llama model."
- [The HARD Truth About Hosting Your Own LLMs](../../sources/the-hard-truth-about-hosting-your-own-llms.md) - "[0:04:21] 1,200 tokens per second that is insane just for reference one word is about 1.25 tokens and so this is about 1,000 words per second roughly."
- [AI is TOO EXPENSIVE if You Don't Do This](../../sources/ai-is-too-expensive-if-you-dont-do-this.md) - "[0:04:13] for using llama 370b we are going to be using Groq it is so cheap using llama 3 with Groq it's like 11% of the price of GPT-4o for the input tokens and then 5% of the price for the output tokens."
- [Llama 3.2 is INSANE - But Does it Beat GPT as an AI Agent?](../../sources/llama-32-is-insane-but-does-it-beat-gpt-as-an-ai-agent.md) - "[0:03:43] you don't have to change any code to go from Groq to anthropic or anthropic to open AI it is so so easy."
- [New Llama 3 Model BEATS GPT and Claude with Function Calling!?](../../sources/new-llama-3-model-beats-gpt-and-claude-with-function-calling.md) - "[0:00:00] Groq an AI company that builds infrastructure to help you work with any local model has recently developed their own version of llama 3 which is specifically designed for function calling."
- [I Found the Limits of the Most Popular LLMs](../../sources/i-found-the-limits-of-the-most-popular-llms.md) - "[0:28:01] this finetune version llama 3 even though it is meant for function calling is failing here it's not giving good arguments."
- [This Bolt.new Fork is EXPLODING - Don't Miss out on What's Happening!](../../sources/this-boltnew-fork-is-exploding-dont-miss-out-on-whats-happening.md) - "[0:06:12] a lot of providers like Groq for example actually make their API for using their llms open AI compatible."
- [I Forked Bolt.new and Made it WAY Better](../../sources/i-forked-boltnew-and-made-it-way-better.md) - "[0:07:38] we have a bunch of Groq models here if you wanted to use like llama 3.1 or 3.2."
- [I Will Win the Nvidia AI Agents Developer Contest](../../sources/i-will-win-the-nvidia-ai-agents-developer-contest.md) - "[0:05:52] right now I'm just using Groq uh with llama for the llm."
- [COMPLETE Guide to LangServe - Make Your AI Agent Actually Useful](../../sources/complete-guide-to-langserve-make-your-ai-agent-actually-useful.md) - "[0:02:54] it's going to use either an open AI anthropic or Groq model depending on the llm model environment variable."
