GPT-5.4 mini vs GPT-5.1
Head-to-head specifications
| Metric | GPT-5.4 mini | GPT-5.1 | Difference |
|---|---|---|---|
| Intelligence Index | 40.0 | 37.0 | +8.1% |
| Coding Index | 56.1 | 49.4 | +13.6% |
| Agentic Index | 30.2 | 21.0 | — |
| Context window | 922K tokens | 512K tokens | — |
| Blended price ($/1M tokens) | $0.52 | $0.77 | -32.5% |
| Output speed (tokens/s) | 170 | 106 | +60.4% |
| Access | Proprietary API | Proprietary API | — |
- GPT-5.4 mini leads overall capability (Intelligence Index 40.0 vs 37.0).
- GPT-5.4 mini is the cheaper model to run at $0.52/1M blended tokens — about 1.5× cheaper.
- GPT-5.4 mini offers the larger context window (922K tokens), useful for long documents and codebases.
Verdict: GPT-5.4 mini or GPT-5.1?
GPT-5.4 mini advantages
- General intelligence (+8%)
- Coding ability (+12%)
- Agentic task performance (+30%)
- Context window (+44%)
- Affordability (+32%)
- Output speed (+38%)
GPT-5.1 advantages
- No decisive advantage on the tracked metrics.
Which should you choose?
- Choose the GPT-5.4 mini if you need the strongest overall reasoning and accuracy.
- Choose the GPT-5.4 mini if coding and software development are your main workload.
Value for money
GPT-5.4 mini offers more intelligence per dollar (1.6× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
GPT-5.4 mini vs GPT-5.1: which should you choose?
GPT-5.4 mini — OpenAI multimodal model with an Intelligence Index of 40, a 922K-token context window and a blended price of $0.52/1M tokens.
GPT-5.1 — OpenAI multimodal model with an Intelligence Index of 37, a 512K-token context window and a blended price of $0.77/1M tokens.
GPT-5.4 mini vs GPT-5.1: GPT-5.4 mini scores higher on the Intelligence Index. GPT-5.4 mini leads overall capability (Intelligence Index 40.0 vs 37.0). GPT-5.4 mini is the cheaper model to run at $0.52/1M blended tokens — about 1.5× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the GPT-5.4 mini scores 40.0 versus 37.0. For software development, the Coding Index puts GPT-5.4 mini ahead (56.1 vs 49.4). On agentic, multi-step tool-use tasks, GPT-5.4 mini measures stronger. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The GPT-5.4 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-5.4 mini generates faster (170 vs 106 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, GPT-5.4 mini is the cheaper model to run ($0.52 vs $0.77 per 1M tokens). GPT-5.4 mini is proprietary api and GPT-5.1 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 GPT-5.4 mini better than the GPT-5.1?
GPT-5.4 mini is the clearly stronger overall choice, winning most of the dimensions that matter. GPT-5.4 mini leads overall capability (Intelligence Index 40.0 vs 37.0).
What is the main difference between the GPT-5.4 mini and the GPT-5.1?
GPT-5.4 mini leads overall capability (Intelligence Index 40.0 vs 37.0). GPT-5.4 mini is the cheaper model to run at $0.52/1M blended tokens — about 1.5× cheaper.
Which is better value?
GPT-5.4 mini offers more intelligence per dollar (1.6× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Which should I choose?
Choose the GPT-5.4 mini if you need the strongest overall reasoning and accuracy. Choose the GPT-5.4 mini if coding and software development are your main workload.
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.