GPT-3.5 Turbo vs OpenAI o1
Head-to-head specifications
| Metric | GPT-3.5 Turbo | OpenAI o1 | Difference |
|---|---|---|---|
| MMLU (general capability) | 70.0% | 92.3% | -22.3% |
| Context window | 16K tokens | 128K tokens | — |
| Price (input / output per 1M) | $0.5 / $1.5 | $15 / $60 | — |
| Access | Proprietary API | Proprietary API | — |
- OpenAI o1 leads general capability (MMLU 92.3% vs 70.0%).
- OpenAI o1 offers the larger context window, useful for long documents and codebases.
Verdict: GPT-3.5 Turbo or OpenAI o1?
GPT-3.5 Turbo advantages
- Input cost (+97%)
- Output cost (+98%)
OpenAI o1 advantages
- General capability (+24%)
- Context window (+88%)
Which should you choose?
- Choose the GPT-3.5 Turbo if you process large volumes of input and want the lowest cost.
- Choose the OpenAI o1 if you need the strongest reasoning and accuracy.
- Choose the GPT-3.5 Turbo if you generate a lot of output and want the lowest cost.
Value for money
GPT-3.5 Turbo offers more capability per dollar — a better value pick for high-volume use, delivering 28.44× the MMLU-per-cost of the alternative.
GPT-3.5 Turbo vs OpenAI o1: which should you choose?
GPT-3.5 Turbo — OpenAI large language model (2023) with a 16K-token context window and an MMLU score of 70.0%.
OpenAI o1 — OpenAI large language model (2024) with a 128K-token context window and an MMLU score of 92.3%.
GPT-3.5 Turbo vs OpenAI o1: OpenAI o1 scores higher on the MMLU benchmark. OpenAI o1 leads general capability (MMLU 92.3% vs 70.0%). OpenAI o1 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 OpenAI o1 scores 92.3% versus 70.0%. 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 OpenAI o1 handles up to 128K 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
GPT-3.5 Turbo is proprietary api and OpenAI o1 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 GPT-3.5 Turbo better than the OpenAI o1?
These two are closely matched — the right pick comes down to which specific strengths you value and the price you actually pay. OpenAI o1 leads general capability (MMLU 92.3% vs 70.0%).
What is the main difference between the GPT-3.5 Turbo and the OpenAI o1?
OpenAI o1 leads general capability (MMLU 92.3% vs 70.0%). OpenAI o1 offers the larger context window, useful for long documents and codebases.
Which is better value?
GPT-3.5 Turbo offers more capability per dollar — a better value pick for high-volume use, delivering 28.44× the MMLU-per-cost of the alternative.
Which should I choose?
Choose the GPT-3.5 Turbo if you process large volumes of input and want the lowest cost. Choose the OpenAI o1 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.