o4-mini
OpenAI · o-series
Cost-efficient OpenAI reasoning model retained as a legacy API reference after GPT-5 mini became the newer default direction.
Overview
Freshness note: Model capabilities, limits, and pricing can change quickly. This profile is a point-in-time snapshot last verified on March 27, 2026.
o4-mini is a reasoning-capable OpenAI model designed to balance analytical strength with production-friendly cost. OpenAI’s current compare-models guide now explicitly frames it as a model that has been succeeded by GPT-5 mini, so it reads best as a legacy route rather than a current default recommendation.
That does not make it useless. It is still available and can make sense for compatibility-sensitive reasoning workflows that were already built around the older o-series behavior.
Capabilities
The model handles structured decision tasks, planning, medium-complexity technical analysis, and cost-sensitive reasoning workloads well. It is practical when teams want more reasoning depth than a plain cheap chat model, but do not need a premium route like o3 or GPT-5.4.
Technical Details
OpenAI’s current model docs still list o4-mini with a 200K context window and 100K max output tokens. It remains part of the reasoning family, but the strategic context has changed: GPT-5 mini is now the newer default direction for similar cost-conscious deployments.
Pricing & Access
Published standard API pricing (per 1M tokens):
- Input: $1.10
- Output: $4.40
Access remains available through OpenAI API model endpoints where the model is enabled for the account.
Best Use Cases
o4-mini is a good fit for compatibility-sensitive reasoning workflows, lower-cost planning and analysis, and routing setups that still depend on the older o-series behavior. For new public-facing OpenAI defaults, GPT-5 mini is the more current recommendation.
Comparisons
- o3 (OpenAI): More capable for harder reasoning, but more expensive.
- GPT-5 mini (OpenAI): Newer default route for fast, efficient OpenAI deployments.
- Gemini 2.5 Flash (Google): Comparable budget-conscious alternative, with the final choice usually driven by ecosystem fit and workflow shape.