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OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning and coding performance across benchmarks like AIME (99.5% with Python) and SWE-bench, outperforming its predecessor o3-mini and even approaching o3 in some domains. Despite its smaller size, o4-mini exhibits high accuracy in STEM tasks, visual problem solving (e.g., MathVista, MMMU), and code editing. It is especially well-suited for high-throughput scenarios where latency or cost is critical. Thanks to its efficient architecture and refined reinforcement learning training, o4-mini can chain tools, generate structured outputs, and solve multi-step tasks with minimal delay—often in under a minute.
A quick read of the model identity, commercial setup, and access footprint.
Published rates, tier transitions, and modality-specific surcharges in the current catalog entry.
| Pricing | Billing mode |
|---|---|
| Prompt | ¥0.5500/1M tokens |
| Output | ¥2.2000/1M tokens |
| Cache hit | ¥0.1375/1M tokens |
Total tokens usage across all users
Top 10 AI coding agents using this model during the last 15 days.