Let’s talk about the conclusion first: the functions overlap and the working methods are different.
Both Claude and ChatGPT can write, read files, search the web, analyze data, and write code. For ordinary users, the difference is no longer "one knows it and the other doesn't", but how the workbench is organized, what is open in your plan, and who reworks the same material less.
Writing comes before the revision process, long documents come before source management, and programming comes before verification; don’t decide a full-year subscription with a casual question.
Claude has Projects, Artifacts, web search, file analysis and independent Claude Code; ChatGPT has Projects, Canvas, web search, data analysis, file and image tools, and programming workflows such as Codex. The final choice should come down to the one thing you do often.
Writing: Who listens to revision requests more?
When writing, don’t just give a title and see who can write more gorgeously at one time. Prepare a true manuscript and three facts that cannot be changed. Ask both parties to point out the problems first, then only change two of the paragraphs, and finally continue to revise based on your feedback.
Claude's Artifacts will put long, reusable documents or codes in independent windows for iteration; ChatGPT's Canvas also provides separate editing space, selection modification, version viewing and document export. Both sides are better for long drafts than copying the entire text over and over in a chat bubble.
- Whether to preserve the facts and personal tone of the manuscript.
- Can I change only the specified part without rewriting the entire text?
- Is the structure becoming more and more messy after multiple rounds of revisions?
- Can you finally export or continue editing in the format you need.
Which result is more like you cannot be answered for you by the official website menu. Writing selections must be tested with your own manuscript.
Long documents: more than projects and sources, not just contextual numbers
Long document tasks should be distinguished between one-time uploads and long-term projects. Claude Projects can save project knowledge and instructions, and can enable search mode expansion when the content is close to contextual restrictions; ChatGPT Projects also puts chat, files and project instructions together, and allows the use of Canvas, search and other tools in the project.
Don’t just upload a PDF and ask “summarize it.” Prepare three overlapping and contradictory materials, and ask to list common conclusions, conflict locations and corresponding sources, and then ask for a detail that only appears in the third material.
- Can the answer point back to the correct document and paragraph.
- When asked, do you still remember the project rules and previous materials?
- Will old conclusions be misused after the material is updated?
- How many files your plan allows and whether sharing and data controls are appropriate.
Programming: Web chat and project agents should be separated
In the chat web page, both can explain code, write functions and analyze uploaded files. Both Claude's Artifacts and ChatGPT Canvas can place the code in a separate area for further modification; ChatGPT Canvas currently also supports direct execution of Python.
But real projects can’t just look at the chat web page. Anthropic provides Claude Code for working on end projects, and OpenAI provides Codex for understanding code bases, modifications, testing, and reviews. When choosing a programming tool, compare local workspaces, IDEs, terminals, permissions, and testing with Git processes.
Use the same existing minor error to try: Provide reproduction steps, requiring you to first locate the root cause, then modify, add tests, run the original check of the project and explain the diff. It doesn’t matter who has the longer code for the first time. What matters is who has more focused changes, more credible tests, and less time to review.
A set of comparison methods that makes it difficult to deceive oneself
- Prepare a real manuscript, three long documents, and a low-stakes coding assignment.
- Give both sides exactly the same materials, instructions, and time, and do not temporarily make up conditions for one side.
- Document factual errors, omissions, number of reworks and whether the final export is usable.
- Only test the currently available functions of your own account, without inferring from other people's screenshots.
- Compare the total workload of the week and draw conclusions without a single stunning answer.
If the results are close, choose the one that better fits your existing files, equipment, and collaboration methods. Tool switching itself also has costs, and using one steadily is usually better than chasing new models every day.
official information
This article comes from the following official information, verified on August 17, 2026:
