Claude 3.5 Sonnet vs GPT-4o mini
Head-to-head specifications
| Metric | Claude 3.5 Sonnet | GPT-4o mini | Difference |
|---|---|---|---|
| MMLU (general capability) | 88.7% | 82.0% | +6.7% |
| Context window | 200K tokens | 128K tokens | — |
| Price (input / output per 1M) | $3 / $15 | $0.15 / $0.6 | — |
| Access | Proprietary API | Proprietary API | — |
- Claude 3.5 Sonnet leads general capability (MMLU 88.7% vs 82.0%).
- Claude 3.5 Sonnet offers the larger context window, useful for long documents and codebases.
Verdict: Claude 3.5 Sonnet or GPT-4o mini?
Claude 3.5 Sonnet advantages
- General capability (+8%)
- Context window (+36%)
GPT-4o mini advantages
- Input cost (+95%)
- Output cost (+96%)
Which should you choose?
- Choose the Claude 3.5 Sonnet if you need the strongest reasoning and accuracy.
- Choose the GPT-4o mini if you process large volumes of input and want the lowest cost.
- Choose the Claude 3.5 Sonnet if you work with long documents or large codebases.
Value for money
GPT-4o mini offers more capability per dollar — a better value pick for high-volume use, delivering 22.19× the MMLU-per-cost of the alternative.
Claude 3.5 Sonnet vs GPT-4o mini: which should you choose?
Claude 3.5 Sonnet — Anthropic large language model (2024) with a 200K-token context window and an MMLU score of 88.7%.
GPT-4o mini — OpenAI large language model (2024) with a 128K-token context window and an MMLU score of 82.0%.
Claude 3.5 Sonnet vs GPT-4o mini: Claude 3.5 Sonnet scores higher on the MMLU benchmark. Claude 3.5 Sonnet leads general capability (MMLU 88.7% vs 82.0%). Claude 3.5 Sonnet offers the larger context window, useful for long documents and codebases.
Capability and reasoning
On MMLU — a 57-subject benchmark of general knowledge and reasoning — the Claude 3.5 Sonnet scores 88.7% versus 82.0%. MMLU is a useful proxy for raw knowledge but does not capture instruction-following, coding, tool use, latency or safety, so treat it as one signal among several.
Context window
The Claude 3.5 Sonnet handles up to 200K tokens per request, which sets how much documentation, transcript or code it can reason over at once — decisive for retrieval-augmented and long-document workflows.
Pricing and access
Claude 3.5 Sonnet is proprietary api and GPT-4o mini is proprietary api. Proprietary models bill per token via API; open-weight models can be self-hosted, trading per-call cost for infrastructure you manage. For production, weigh throughput, rate limits and data-residency needs alongside headline price.
The verdict
Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.
Frequently asked questions
Is the Claude 3.5 Sonnet better than the GPT-4o mini?
These two are closely matched — the right pick comes down to which specific strengths you value and the price you actually pay. Claude 3.5 Sonnet leads general capability (MMLU 88.7% vs 82.0%).
What is the main difference between the Claude 3.5 Sonnet and the GPT-4o mini?
Claude 3.5 Sonnet leads general capability (MMLU 88.7% vs 82.0%). Claude 3.5 Sonnet offers the larger context window, useful for long documents and codebases.
Which is better value?
GPT-4o mini offers more capability per dollar — a better value pick for high-volume use, delivering 22.19× the MMLU-per-cost of the alternative.
Which should I choose?
Choose the Claude 3.5 Sonnet if you need the strongest reasoning and accuracy. Choose the GPT-4o mini if you process large volumes of input and want the lowest cost.
Methodology
Large language models are compared on the MMLU benchmark (a widely-cited 57-subject test of general knowledge and reasoning, reported as a percentage), maximum context window, and published API pricing per million input and output tokens. Open-weight models can also be self-hosted. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit.