Claude vs ChatGPT (2025)
Both are excellent. They are excellent at different things.
After 18 months of building production systems on both, here is the take we've actually shipped client work on. Not benchmarks — what they cost, what they break on, and when each one is the right pick.
| Claude (Sonnet 4) | ChatGPT (GPT-4o / 5) | |
|---|---|---|
| Best at | Writing, careful reasoning, long-context analysis, code review. | General reasoning, multi-modal (vision, voice), broad ecosystem. |
| Context window | 200K tokens (Sonnet 4) — and uses it well. | 128K tokens, with prompt caching. |
| Voice / vision | Vision yes. Voice no. | Vision and native voice (Realtime API). |
| Pricing (input/output, $/1M) | $3 / $15 (Sonnet) | $2.50 / $10 (GPT-4o) |
| Coding | Best-in-class for editing existing code; great with whole repos. | Great for new code generation; tighter agent-loop performance. |
| Refusals | Cautious by default. Easier to convince with context. | Less cautious overall. More likely to comply. |
| Tool use / functions | Strong, very reliable schema following. | Strong, with parallel function calls. |
| Where it loses | Sometimes too verbose; no native voice; no image gen. | Less consistent on long-context tasks; output quality varies more. |
Pick Claude (Sonnet 4) when
Default to Claude when: writing matters, you need long-context analysis (large docs, repos), or you're building a coding agent.
Pick ChatGPT (GPT-4o / 5) when
Default to ChatGPT when: you need voice, vision is core, you want OpenAI's ecosystem (Assistants, image gen, broad SDK), or you're cost-sensitive at scale.
Bottom line
Most production systems we ship route between both — Claude for reasoning-heavy steps, GPT for cheap classification, voice, or vision. Picking one is not the question. Knowing when to use which one is.
Need help picking — or stitching them together?
We do this for clients every week. Bring us the workflow, we'll bring the architecture.
Talk to usGlossary
- Claude Sonnet (Anthropic)Anthropic's primary workhorse model — strong writing, long context, and reliable tool use.
- GPT-4oOpenAI's flagship multimodal model — fast, cheap relative to predecessors, and supports vision and voice.
- Model RoutingSending requests to different models based on complexity, cost, or content type.
- LLM (Large Language Model)A model trained on huge amounts of text to predict the next token.