ChatGPT vs Claude vs Gemini vs Grok vs Llama: AI Model Families Explained

New model names appear almost every week, which makes AI feel impossible to keep up with. The trick is to stop memorising version numbers and learn the families and the questions to ask. Version numbers change; these don’t.

The main families#

Family	Made by	Chat app	Weights	Known for
GPT	OpenAI (USA)	ChatGPT	Closed (some open-weight releases)	Started the chatbot boom in late 2022; large ecosystem of tools and plugins
Claude	Anthropic (USA)	Claude	Closed	Long documents, coding and careful writing; Constitutional AI safety approach
Gemini	Google (USA)	Gemini	Closed (open Gemma family too)	Built to be multimodal from the start; integrated with Google products
Grok	xAI (USA)	Grok, inside X	Closed (some older versions opened)	Access to posts on X; conversational style
Llama	Meta (USA)	Meta AI	Open weights	Popular base for open-source apps and fine-tuning
Mistral	Mistral AI (France)	Le Chat	Mix of open and closed	Efficient models, strong in European languages
DeepSeek	DeepSeek (China)	DeepSeek chat	Open weights for major releases	Strong reasoning models at low training cost, widely discussed in 2025
Qwen	Alibaba (China)	Qwen chat	Many open-weight sizes	Wide range of model sizes, strong multilingual support

Each family has several sizes and versions at any time, usually a large, most capable model and smaller, faster, cheaper ones. Check each provider’s models page for current names.

Closed vs open weights#

• Closed models (most GPT, Claude, Gemini, Grok versions) run only on the company’s servers. You use them through a chat app or a paid API. You get top quality and no hardware to manage, but your requests go to the provider.
• Open-weight models (Llama, Mistral’s open models, DeepSeek, Qwen, Gemma) can be downloaded and run on your own computer or server. You control the data and can fine-tune them, but you need suitable hardware and engineering effort. “Open weights” doesn’t always mean fully open source: the training data and code are often not released, and licences vary.

Chat app vs API: they’re different products#

	Chat app (ChatGPT, Claude, Gemini, Grok)	API (for developers)
Who it’s for	People chatting	Programs calling the model
How you pay	Free tier or monthly subscription	Pay per token used (prepaid credits or monthly bill)
Account	Your normal login	A developer console account and an API key
A subscription includes the other?	No. A ChatGPT Plus or Claude Pro subscription does not include API credits, and vice versa

The Gen AI Developer premium track shows how to get API keys from each provider, keep them safe, and call every major model from Python.

A simple model-choice helper#

def suggest(task, private_data=False, requests_per_day=100):
    if private_data:
        return "open-weight model on your own server (e.g. a Llama, Mistral or Qwen size that fits your GPU)"
    if task in ("hard reasoning", "complex coding", "long documents"):
        return "a large frontier model (top GPT, Claude or Gemini tier)"
    if requests_per_day > 10_000:
        return "a small fast tier (mini / flash / haiku-class) to keep costs low"
    return "a mid-size model from any major provider; test 2-3 on real examples"

print(suggest("complex coding"))
print(suggest("sort support emails", requests_per_day=50_000))
print(suggest("summarise contracts", private_data=True))

Output:

a large frontier model (top GPT, Claude or Gemini tier)
a small fast tier (mini / flash / haiku-class) to keep costs low
open-weight model on your own server (e.g. a Llama, Mistral or Qwen size that fits your GPU)

Benchmarks: useful, but not the whole story#

Leaderboards test models on exam-style questions, coding problems and maths. They help you shortlist, but:

• models can be tuned to do well on popular benchmarks;
• your task (Hindi customer emails, your company’s PDFs, your codebase) may behave differently;
• speed, price, context length and reliability matter as much as a few percentage points of accuracy.

AI tools built on these models#

Most AI products you hear about are built on top of these families through their APIs: coding assistants in your editor (for example GitHub Copilot, Cursor, Claude Code), writing tools, browser extensions, meeting note-takers and customer-support bots. When a tool says “powered by GPT” or “powered by Claude”, it is calling that company’s API, exactly what you’ll learn to do in the premium track.

Summary#

• Learn the families (GPT, Claude, Gemini, Grok, Llama, Mistral, DeepSeek, Qwen), not version numbers.
• Closed models = best convenience via app or API; open-weight = control and privacy, more work.
• Chat subscriptions and API usage are separate products and bills.
• Choose by task, data privacy, volume and your own tests, not leaderboards alone.

🎉 You’ve finished How AI Models Are Built. You now understand data, tokens, pretraining, fine-tuning, alignment and serving, which is more than most people who use these tools every day.