o3-pro vs GPT-5 mini
Head-to-head specifications
| Metric | o3-pro | GPT-5 mini | Difference |
|---|---|---|---|
| Intelligence Index | 33.0 | 32.0 | +3.1% |
| Context window | 258K tokens | 922K tokens | — |
| Blended price ($/1M tokens) | $1.87 | $0.26 | +619.2% |
| Output speed (tokens/s) | 42 | 93 | -54.8% |
| Access | Proprietary API | Proprietary API | — |
- o3-pro leads overall capability (Intelligence Index 33.0 vs 32.0).
- GPT-5 mini is the cheaper model to run at $0.26/1M blended tokens — about 7.2× cheaper.
- GPT-5 mini offers the larger context window (922K tokens), useful for long documents and codebases.
Verdict: o3-pro or GPT-5 mini?
o3-pro advantages
- No decisive advantage on the tracked metrics.
GPT-5 mini advantages
- Context window (+72%)
- Affordability (+86%)
- Output speed (+55%)
Which should you choose?
- Choose the GPT-5 mini if you work with long documents or large codebases.
Value for money
GPT-5 mini offers more intelligence per dollar (7.0× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
o3-pro vs GPT-5 mini: which should you choose?
o3-pro — OpenAI multimodal model with an Intelligence Index of 33, a 258K-token context window and a blended price of $1.87/1M tokens.
GPT-5 mini — OpenAI multimodal model with an Intelligence Index of 32, a 922K-token context window and a blended price of $0.26/1M tokens.
o3-pro vs GPT-5 mini: o3-pro scores higher on the Intelligence Index. o3-pro leads overall capability (Intelligence Index 33.0 vs 32.0). GPT-5 mini is the cheaper model to run at $0.26/1M blended tokens — about 7.2× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the o3-pro scores 33.0 versus 32.0. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The GPT-5 mini accepts up to 922K tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, GPT-5 mini generates faster (93 vs 42 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, GPT-5 mini is the cheaper model to run ($0.26 vs $1.87 per 1M tokens). o3-pro is proprietary api and GPT-5 mini is proprietary api. Open-weight models can be self-hosted, trading per-call cost for infrastructure you manage; for production also weigh rate limits, throughput and data-residency requirements.
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 o3-pro better than the GPT-5 mini?
GPT-5 mini is the clearly stronger overall choice, winning most of the dimensions that matter. o3-pro leads overall capability (Intelligence Index 33.0 vs 32.0).
What is the main difference between the o3-pro and the GPT-5 mini?
o3-pro leads overall capability (Intelligence Index 33.0 vs 32.0). GPT-5 mini is the cheaper model to run at $0.26/1M blended tokens — about 7.2× cheaper.
Which is better value?
GPT-5 mini offers more intelligence per dollar (7.0× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Which should I choose?
Choose the GPT-5 mini if you work with long documents or large codebases.
Methodology
Large language models are compared on independent leaderboard metrics: an Intelligence Index (a composite of reasoning and knowledge evaluations), Coding and Agentic indices where measured, community arena Elo, maximum context window, a blended API price per million tokens (weighted across cache-hit, input and output rates), and measured output speed in tokens per second. Where a model ships multiple reasoning-effort variants, we report its strongest variant. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit — and this space moves quickly, so figures reflect the leaderboard snapshot on the page date.