Claude 3.5 Haiku vs GPT-4o
Head-to-head specifications
| Metric | Claude 3.5 Haiku | GPT-4o | Difference |
|---|---|---|---|
| MMLU (general capability) | 80.0% | 88.7% | -8.7% |
| Context window | 200K tokens | 128K tokens | — |
| Price (input / output per 1M) | $1 / $5 | $2.5 / $10 | — |
| Access | Proprietary API | Proprietary API | — |
- GPT-4o leads general capability (MMLU 88.7% vs 80.0%).
- Claude 3.5 Haiku offers the larger context window, useful for long documents and codebases.
Verdict: Claude 3.5 Haiku or GPT-4o?
Claude 3.5 Haiku advantages
- Context window (+36%)
- Input cost (+60%)
- Output cost (+50%)
GPT-4o advantages
- General capability (+10%)
Which should you choose?
- Choose the Claude 3.5 Haiku if you work with long documents or large codebases.
- Choose the GPT-4o if you need the strongest reasoning and accuracy.
- Choose the Claude 3.5 Haiku if you process large volumes of input and want the lowest cost.
Value for money
Claude 3.5 Haiku offers more capability per dollar — a better value pick for high-volume use, delivering 1.88× the MMLU-per-cost of the alternative.
Claude 3.5 Haiku vs GPT-4o: which should you choose?
Claude 3.5 Haiku — Anthropic large language model (2024) with a 200K-token context window and an MMLU score of 80.0%.
GPT-4o — OpenAI large language model (2024) with a 128K-token context window and an MMLU score of 88.7%.
Claude 3.5 Haiku vs GPT-4o: GPT-4o scores higher on the MMLU benchmark. GPT-4o leads general capability (MMLU 88.7% vs 80.0%). Claude 3.5 Haiku 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 GPT-4o scores 88.7% versus 80.0%. 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 Haiku 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 Haiku is proprietary api and GPT-4o 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 Haiku better than the GPT-4o?
Claude 3.5 Haiku takes the overall edge, though GPT-4o wins in specific areas worth weighing. GPT-4o leads general capability (MMLU 88.7% vs 80.0%).
What is the main difference between the Claude 3.5 Haiku and the GPT-4o?
GPT-4o leads general capability (MMLU 88.7% vs 80.0%). Claude 3.5 Haiku offers the larger context window, useful for long documents and codebases.
Which is better value?
Claude 3.5 Haiku offers more capability per dollar — a better value pick for high-volume use, delivering 1.88× the MMLU-per-cost of the alternative.
Which should I choose?
Choose the Claude 3.5 Haiku if you work with long documents or large codebases. Choose the GPT-4o if you need the strongest reasoning and accuracy.
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.