GPT-5 mini

OpenAI · GPT-5

Cost-efficient GPT-5 variant for high-volume production workflows needing strong reasoning at lower cost.

Type
language
Context
400K tokens
Max Output
128K tokens
Status
current
Input
$0.25/1M tok
Output
$2/1M tok
API Access
Yes
License
proprietary
reasoning cost-efficient tool-use coding production
Released August 2025 · Updated February 15, 2026

Overview

Freshness note: Model capabilities, limits, and pricing can change quickly. This profile is a point-in-time snapshot last verified on February 15, 2026.

GPT-5 mini is designed as a lower-cost member of the GPT-5 family for teams that need strong baseline quality with tighter budget control. It fits production scenarios where request volume matters more than absolute frontier depth.

Capabilities

The model is effective for structured summarization, extraction, routing logic, and general coding assistance in medium-complexity tasks. It typically performs well when prompts include clear constraints and output format requirements.

Technical Details

GPT-5 mini is positioned for production throughput with large-context handling and practical tool-use support. It is best treated as a generalist tier for scalable workflows that do not always require flagship-level reasoning depth.

Pricing & Access

Access is available via OpenAI API surfaces. Public pricing and feature availability may vary by region, plan, and product surface, so teams should verify current pricing in official OpenAI docs before rollout.

Best Use Cases

Choose GPT-5 mini for high-volume assistants, internal knowledge operations, triage workflows, and standardized document processing pipelines where cost predictability and stable output quality are key.

Comparisons

Compared with GPT-5, GPT-5 mini trades some top-end reasoning headroom for significantly better cost efficiency. Compared with o4-mini, GPT-5 mini is generally a stronger general-purpose default for mixed enterprise workloads. Compared with Gemini 2.5 Flash, selection usually depends on ecosystem integration and workload characteristics.