OpenAI: o4 Mini
openai/o4-mini
Description
OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast 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 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.
How this model compares
Overall covers the full catalog. By plan covers only models available on that tier (same rules as available models in your list). Position on min–average–max. Prices use the higher of prompt or completion per token, shown per 1M tokens.
Price (per 1M tokens)
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Max
This model
339 models in this groupPrice (per 1M tokens)
- Min
- $0.04
- Avg
- $12.395447
- Max
- $750.00
This model: $4.40 / 1M tokens
Context length (tokens)
Min
Max
This model
339 models in this groupContext length (tokens)
- Min
- 4,095 tokens
- Avg
- 379,884.782 tokens
- Max
- 10,000,000 tokens
This model: 200,000 tokens
Capabilities
text+image+file->textContext: 200,000 tokens
Input:
ImageTextFile
Output:
Text