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.
Modalities
In / Out Price
$1.10 / $4.40per 1M
Context
200K
Released
Apr 16, 2025
Knowledge Cutoff
Jun 2024
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.
o4 Mini costs $1.10/M input tokens and $4.40/M output tokens, with separate rates for Cache Read at $0.275/M tokens and Web Search at $10.00/1K calls.
o4 Mini has a 200,000 token context window. It supports up to 100,000 completion tokens.
Yes. o4 Mini accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.
o4 Mini accepts images, text and files such as PDFs as input and returns text.
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o4 Mini was released on April 16, 2025. Its knowledge cutoff is June 30, 2024.