GPT-4o vs Claude 3.5 Sonnet: price and performance

GPT-4o and Claude 3.5 Sonnet are the two models most teams actually deploy in production today. They sit in the same price range, target the same use cases, and have meaningful differences that show up in real workloads.

This post is a clear-eyed comparison.

Pricing at a glance

Both models are billed per 1M tokens. As of this writing, GPT-4o input is $2.50 / 1M and output is $10.00 / 1M; Claude 3.5 Sonnet input is $3.00 / 1M and output is $15.00 / 1M. On a 4:1 input-heavy chat workload, that's roughly:

• GPT-4o: $0.0125 per 1k-token interaction
• Claude 3.5 Sonnet: $0.0150 per 1k-token interaction

In other words, Claude 3.5 Sonnet is about 20% more expensive on typical workloads. For some teams that's nothing; for others, at scale, that's the difference between a profitable feature and a money-losing one.

For up-to-date numbers, the comparison table is refreshed daily.

Context windows

• GPT-4o: 128k tokens
• Claude 3.5 Sonnet: 200k tokens

Sonnet's 200k window matters more than the raw number suggests, because Anthropic's long-context recall is genuinely strong. If you are pushing 100k+ tokens of context (legal documents, large codebases, long support transcripts), Sonnet usually wins on quality even when GPT-4o would technically fit.

Where GPT-4o wins

• Speed. Time-to-first-token on GPT-4o is consistently lower.
• Multimodal. GPT-4o handles vision and audio natively. Sonnet handles vision but not audio.
• Tooling maturity. Function calling, structured outputs (JSON Schema enforced server-side), the Realtime API, the Assistants API. OpenAI's developer surface is wider.
• Cost. As above, ~20% cheaper at typical input/output ratios.

Where Claude 3.5 Sonnet wins

• Long-form writing. Sonnet's prose is better. Less filler, fewer clichés, more precise word choice.
• Long context. 200k tokens, with strong recall in the back third of the window.
• Coding. On real-world refactoring and multi-file changes, Sonnet has been measurably better than GPT-4o for most of 2024 and 2025. This is the single biggest reason to choose Sonnet today.
• Refusal behaviour. Sonnet refuses fewer reasonable requests than GPT-4o. If your product surfaces edge cases — security research, medical queries, creative writing with conflict — this matters.

Which to pick

A pragmatic decision rule:

• Building a coding agent or doing a lot of code generation? Sonnet.
• Building a voice or vision-heavy product? GPT-4o.
• Long-context document processing where recall matters? Sonnet.
• Latency-sensitive consumer chat? GPT-4o.
• Cost-sensitive at scale, quality is comparable on your eval? GPT-4o.

If you genuinely cannot tell, run both on 50 examples from your real traffic and look at the outputs side by side. It will be obvious within an hour.

What about the cheap tier?

Before paying flagship-tier prices, always ask: would GPT-4o mini or Claude 3 Haiku actually be enough? On classification, summarisation, simple Q&A, and most RAG, the answer is yes — and it's 20x cheaper. See Cheapest LLM APIs in 2025 for the full breakdown.