o4-mini
o3-mini is OpenAI's most recent small reasoning model, providing high intelligence at the same cost and latency targets of o1-mini. o3-mini also supports key developer features, like Structured Outputs, function calling, Batch API, and more. Like other models in the o-series, it is designed to excel at science, math, and coding tasks.
Specifications
Benchmarks
Released 2025-04-16Artificial Analysis Coding Index β a composite of coding evaluations including LiveCodeBench, SciCode and Terminal-Bench.
Graduate-level physics, chemistry & biology questions designed to resist Googling.
Artificial Analysis Intelligence Index β a composite of multiple evaluations measuring overall model capability.
Scores are sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and do not capture every aspect of model quality β always test on your own workload.
Pricing
Requesty charges exactly what the upstream provider charges β no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.
Quickstart
Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to azure/o4-mini@francecentral.
123456789101112131415from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="azure/o4-mini@francecentral", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)
Other Microsoft Azure AI models
Frequently asked questions
How much does o4-mini cost?
What is the context window of o4-mini?
How does o4-mini perform on benchmarks?
What can o4-mini do?
How do I use o4-mini with the OpenAI SDK?
What region is this deployment?
Access o4-mini through Requesty
One API key, 400+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

