Eric Hinzpeter
NOTE· 2026-03-22· 5 min

ChatGPT vs. Claude: A Practitioner's Comparison

I work with both models every day. Neither is better at everything. What I use ChatGPT for, what I use Claude for, and why the split matters.

Anyone who starts taking AI models seriously ends up at the same question sooner or later: ChatGPT or Claude? The honest answer is that there isn't one, at least not one that fits everyone. What does exist is different strengths that matter more or less depending on the task. I use both, and here is how I split them in practice.

Why "ChatGPT" is almost a generic term

ChatGPT has a head start no other model can simply close: it was there earlier and burned its name deep into public awareness. Ask someone without AI experience which model they know, and they almost always say ChatGPT, even if they have never used it. The name has become a synonym for AI chatbot, similar to how "google" became a verb for search.

That has practical consequences. Introducing AI to a team is easier with ChatGPT, less convincing required. The app is known, the on-ramp is low, and the basic version does not even need an account. That is not a technical advantage, but in daily work the "people already know this" factor counts.

Anyone who has been at it for a while has also built an ecosystem: Custom GPTs, Memory, App Store integrations. That is invested time, hard to carry over to another model. What Custom GPTs deliver and where their limits are, covered in a separate post.

What ChatGPT does better in practice

I use ChatGPT mainly for tasks where speed matters more than depth, and where I do not need heavy reasoning.

In n8n automations, I reach for the vision model when screenshots or images need analysis. It works reliably, and the API costs are low, which matters for automations with many runs. For simple tasks like sorting lists, quick evaluations, or categorization without reasoning, OpenAI's small, fast models are convenient. Claude would be overkill there.

Codex is its own category: a programming tool that runs cloud-based in a sandbox environment, with a local CLI variant. I have not integrated it deeply into my workflow yet, but I am watching it. For developers with a lot of boilerplate or repetitive code tasks, it is a useful tool, especially for anyone who does not use Claude Code.

Image and video generation with Sora rounds out the OpenAI ecosystem. Claude does not have that, which may or may not matter depending on the task.

Where Claude works differently

Claude answers more slowly than ChatGPT, especially without thinking mode, which is not always a disadvantage because the answers come back less superficial. Claude does ask follow-up questions when something is unclear instead of just writing ahead (sometimes annoying), but the answer then lands closer to what you actually needed.

Since 13 March 2026, Sonnet 4.6 and Opus 4.6 have a 1-million-token context window, generally available from that date. That is a different order of magnitude than anything before. According to Anthropic's model documentation, Opus 4.6 scores 76% on the MRCR v2 needle-in-haystack test at full context, which means: the model loses very little accuracy even with very large context. Hallucinations on long documents are a real weakness in many models. With Opus 4.6 the result is clearly better than expected so far.

What that means in practice: I can load a large project with many files, notes, and background information into context without the model starting to forget or mix things up near the end. Not a theoretical benefit, it shows up in daily work with Claude Code and Claude Cowork.

Claude Code and Cowork: where agentic work actually works

I use Claude Code daily to build my own website and web tools. The ability to deploy sub-agents, skills, and the Skill Creator 2.0 is a qualitative step beyond anything I built with AI tools before. The Skill Creator 2.0 improves skills on its own based on feedback, which means the system gets better over time, not just stays constant.

Anthropic invests heavily in learning material for agentic workflows: guides for sub-agents, best practices, training videos. You notice that once you go deeper. The documentation is better than at most comparable tools, which lowers the bar to more complex setups. More on this in the Claude Code Skills field report.

Claude Cowork is a different product than Claude Code, but similar in philosophy: it treats AI as an active colleague, not a passive answer tool. I use it for planning, especially with Opus 4.6, when I want to think through complex decisions. The quality of the follow-up questions and the depth of the answers are especially good there.

For anyone who wants to look closer at agentic AI: the line between assistant and agent is a useful starting point.

The real weaknesses of Claude

An honest comparison has to name the downsides too. Claude has a 5-hour token window per session and a weekly token cap. Anyone working intensively hits it faster than expected. With the $20 plan and Opus 4.6, the cap arrives especially fast, because the model burns more tokens per request. Anyone who wants to use Claude Code or Claude Cowork needs the paid tier anyway.

Claude also requires an account, even for the basic version. For quickly trying something without signing up, ChatGPT is the better option. Sounds small, but it is a real difference at the entry point.

Image generation and video are not in Claude. For workflows that need both, ChatGPT stays the obvious choice, at least until Anthropic catches up.

How I have it split right now

The largest share of my daily work runs through Claude Sonnet 4.6. For more complex planning tasks I use Opus 4.6, usually inside Claude Code or Cowork. Claude is my main tool, because sub-agents, skills, and the context window currently give more than comparable tools, especially on larger projects.

I use ChatGPT for fast API tasks in automations, for vision in workflows with images, and for simple tasks where the small models are enough and cost matters. The OpenAI ecosystem stays relevant, especially for anything around image generation or simple, scalable automations.

Anyone starting with prompting basics will do fine with either model. Anyone going deeper and seriously building agentic workflows will get further with Claude today. That can change, but that is the state as of March 2026.

FAQ

Is ChatGPT or Claude better?
Neither wins at everything. Claude is stronger for agentic work, long context, and deep reasoning. ChatGPT is faster, cheaper on API calls, and the only one of the two with image and video generation. The right pick depends on the task.
How big is Claude's context window?
Since 13 March 2026, Sonnet 4.6 and Opus 4.6 have a 1-million-token context window. Opus 4.6 keeps 76% accuracy on the MRCR v2 needle-in-haystack test even at full length, so it loses little on long documents.
What are Claude's main downsides?
A 5-hour token window per session plus a weekly cap, which heavy users hit fast, especially on the $20 plan with Opus 4.6. It also requires an account and has no image or video generation.

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Eric Hinzpeter

Eric Hinzpeter, Senior B2B Content Strategist. He builds production AI agents and marketing automation, and documents the results here.

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