GPT-4.1 vs Grok 3 mini Reasoning
Head-to-head specifications
| Metric | GPT-4.1 | Grok 3 mini Reasoning | Difference |
|---|---|---|---|
| Intelligence Index | 24.0 | 27.0 | -11.1% |
| Context window | 1M tokens | 1M tokens | — |
| Blended price ($/1M tokens) | $0.90 | $0.16 | +462.5% |
| Output speed (tokens/s) | 103 | 66 | +56.1% |
| Access | Proprietary API | Proprietary API | — |
- Grok 3 mini Reasoning leads overall capability (Intelligence Index 27.0 vs 24.0).
- Grok 3 mini Reasoning is the cheaper model to run at $0.16/1M blended tokens — about 5.6× cheaper.
Verdict: GPT-4.1 or Grok 3 mini Reasoning?
GPT-4.1 advantages
- Output speed (+36%)
Grok 3 mini Reasoning advantages
- General intelligence (+11%)
- Affordability (+82%)
Which should you choose?
- Choose the GPT-4.1 if low latency and fast generation matter for your application.
- Choose the Grok 3 mini Reasoning if you need the strongest overall reasoning and accuracy.
Value for money
Grok 3 mini Reasoning offers more intelligence per dollar (6.3× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
GPT-4.1 vs Grok 3 mini Reasoning: which should you choose?
GPT-4.1 — OpenAI multimodal model with an Intelligence Index of 24, a 1M-token context window and a blended price of $0.9/1M tokens.
Grok 3 mini Reasoning — xAI multimodal model with an Intelligence Index of 27, a 1M-token context window and a blended price of $0.16/1M tokens.
GPT-4.1 vs Grok 3 mini Reasoning: Grok 3 mini Reasoning scores higher on the Intelligence Index. Grok 3 mini Reasoning leads overall capability (Intelligence Index 27.0 vs 24.0). Grok 3 mini Reasoning is the cheaper model to run at $0.16/1M blended tokens — about 5.6× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the Grok 3 mini Reasoning scores 27.0 versus 24.0. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The GPT-4.1 accepts up to 1 million tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, GPT-4.1 generates faster (103 vs 66 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, Grok 3 mini Reasoning is the cheaper model to run ($0.16 vs $0.90 per 1M tokens). GPT-4.1 is proprietary api and Grok 3 mini Reasoning 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-4.1 better than the Grok 3 mini Reasoning?
Grok 3 mini Reasoning takes the overall edge, though GPT-4.1 wins in specific areas worth weighing. Grok 3 mini Reasoning leads overall capability (Intelligence Index 27.0 vs 24.0).
What is the main difference between the GPT-4.1 and the Grok 3 mini Reasoning?
Grok 3 mini Reasoning leads overall capability (Intelligence Index 27.0 vs 24.0). Grok 3 mini Reasoning is the cheaper model to run at $0.16/1M blended tokens — about 5.6× cheaper.
Which is better value?
Grok 3 mini Reasoning offers more intelligence per dollar (6.3× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Which should I choose?
Choose the GPT-4.1 if low latency and fast generation matter for your application. Choose the Grok 3 mini Reasoning if you need the strongest overall reasoning and accuracy.
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.