ChatGPT vs Claude vs Qwen

ChatGPT, Claude and Qwen are three AI assistants from different companies: OpenAI, Anthropic and Alibaba respectively. Each has different strengths, different apps and different underlying model families. Understanding those differences is useful before choosing one for a task. Tools like fenbs keep your task brief and evaluation record in one place so you can try all three on the same work without losing what you learn from each comparison.

An important distinction before comparing them: the model and the app are not the same thing. Qwen refers to a family of AI models, not a single product. Those models run in different apps and platforms: Alibaba's Tongyi app, various open-source deployments and third-party services. That distinction affects what features are available, how you access the model and what the experience is like.

Understanding the model-versus-app distinction

When someone says "ChatGPT," they usually mean the ChatGPT application at openai.com, which runs OpenAI's GPT-4o and other models. When someone says "Claude," they usually mean the Claude application at claude.ai, running Anthropic's Claude models. These are apps with specific features, interfaces and plans.

Qwen is different. Qwen is a family of models published by Alibaba Research. Those models are accessible through Alibaba's Tongyi app, through the API via Alibaba Cloud, and through open-source releases on platforms like Hugging Face. Depending on which deployment you use, the features, speed and safety behavior may differ significantly.

This distinction matters when comparing capabilities. A Qwen model running in one deployment may not behave identically to the same model in another. Compare the tools you will actually use for your work rather than comparing models in the abstract.

Writing and analysis tasks

ChatGPT is fast and versatile across writing tasks: drafting, editing, tone adjustment and format changes. It responds quickly to iterative prompts and handles a wide variety of tones. For content creation, marketing copy and rapid iteration on a first draft, ChatGPT's speed is a practical advantage.

Claude tends to be more careful and precise in analytical writing. It is particularly useful for tasks that require structured reasoning: producing a detailed critique, developing an argument step by step, or writing technical documentation where accuracy and clarity matter more than speed. For longer analytical documents, Claude's thoroughness is often the deciding factor.

Qwen is particularly strong in multilingual tasks and in Chinese-language writing. For work that spans Chinese and English, for international business communication or for markets where Chinese-language quality matters, Qwen is worth comparing directly against ChatGPT and Claude on the same task. For English-only work, ChatGPT and Claude have longer track records and more established support.

Coding tasks

All three assistants generate code and help debug it. ChatGPT and Claude are both strong at English-language coding tasks across common languages and frameworks. Claude tends to give more detailed explanations of the code alongside the output. ChatGPT is faster for quick snippets.

Qwen's coding model variants (such as Qwen-Coder) are designed specifically for coding tasks and perform well on standard benchmarks. If you are building or evaluating a coding application and want an open-source model option, Qwen-Coder is worth testing against the commercial options. The Qwen model family has released open weights for several versions, which affects how you can deploy and customize the model.

For day-to-day coding assistance in a consumer app, the difference between the three is smaller than the difference in how you interact with them and what features the app provides. Test all three on representative tasks from your actual work before committing to one.

Multilingual and international work

Qwen's training dataset includes a larger proportion of Chinese-language content than ChatGPT or Claude, which makes it the strongest of the three for Chinese-language tasks. For businesses operating in China or working across Chinese-English communication, Qwen's multilingual quality is a meaningful advantage.

ChatGPT and Claude both handle major European and Asian languages, but their training emphasis on English means the quality is generally highest in English. For tasks in Spanish, French, German and similar languages, both perform well. For languages with smaller training data footprints, all three are less reliable, and quality varies by model version.

API access and developer use cases

For developers accessing these assistants through an API rather than a consumer app, all three have API access with different pricing structures, rate limits and available model versions. OpenAI and Anthropic both offer well-documented REST APIs with SDKs for major languages. Alibaba Cloud provides the Qwen API through its Model Studio service. Qwen models are also available as open-source weights on Hugging Face for self-hosted deployments, which is the main differentiator for organizations that need to run models on their own infrastructure or fine-tune a model on proprietary data.

For developers evaluating all three for an application, test each on representative inputs from your actual use case rather than relying on benchmark scores alone. Benchmark performance and real-world performance on specific task types often diverge significantly. Run all three on the same input set, evaluate the outputs against the criteria that matter for your application and measure latency and cost at the expected request volume before committing to one. Those numbers change with each new model release, so plan to revisit the comparison after any significant update from any of the three providers.

How to compare them fairly

To compare three assistants fairly on a task: use the same prompt, the same task description and the same evaluation criteria for all three. Do not adjust the prompt based on what you think will work for each assistant. Judge each output on the same criteria before deciding which is better.

Run the comparison on tasks from your actual work, not on test prompts designed to showcase a specific capability. An assistant that performs well on a synthetic benchmark may not be the best fit for the specific writing, analysis or coding your work requires.

Keep a record of the comparison: the task, the prompt, the output from each assistant and your evaluation. That record tells you which assistant is most reliable for your actual use cases, not for a general benchmark. Revisit the comparison after each major model update, as the relative strengths change.

How to do this with fenbs

1. Create a free account and add a project for the work you are evaluating across assistants. Describe the goal and the criteria you will use to judge outputs.
2. Add a task for each comparison you run. Note the task, the prompt and the criteria before running any of the assistants.
3. Run all three on the same prompt and record the key differences in each output. Note which assistant best met each criterion.
4. Record a decision once you have chosen the right tool for a specific task type. When you revisit the comparison after a model update, update the decision record rather than starting from scratch.
5. Connect your AI apps from Integrations. Whichever assistant you use for ongoing work, it reads the same project context and task record before starting.

Which should you use?

For English-language writing, analysis and standard coding tasks, ChatGPT and Claude are both well-established, with strong app experiences and documented capabilities. Claude is stronger for analytical depth and precise writing. ChatGPT is faster and has better data analysis tooling in its paid plans.

For multilingual work, especially Chinese-English, Qwen is worth a direct comparison. For developers wanting open-source model options, Qwen's open-weight releases are worth exploring. For current availability, plan details and model capabilities, check each vendor's own pages: openai.com, anthropic.com and qwen.ai or the relevant Alibaba Cloud documentation.