GPT-5.4 Mini by OpenAI is a fast, efficient small model optimized for coding, subagent delegation, computer use, and multimodal reasoning at 400k context.
Capabilities, design details, and architectural traits
GPT-5.4 Mini is OpenAI's distilled small model built to bring GPT-5.4's core strengths - coding, tool use, multimodal reasoning, and computer use - to a faster, lower-cost form. It runs more than 2x faster than GPT-5 Mini and approaches GPT-5.4-level performance on several evaluations, making it one of the strongest performance-per-latency tradeoffs in the small-model tier.
GPT-5.4 Mini is explicitly positioned as the execution layer in multi-model pipelines. In Codex, for example, a larger model like GPT-5.4 handles planning and coordination, while GPT-5.4 Mini runs as a subagent completing narrower parallel tasks - codebase search, file review, document processing. This division is built into how Codex allocates quota: GPT-5.4 Mini uses only 30% of the GPT-5.4 quota per task.
| Trait | Detail |
|---|---|
| Computer use at small-model speed | Interprets dense UI screenshots quickly; approaches GPT-5.4 on OSWorld-Verified while outperforming GPT-5 Mini substantially |
| Subagent-native design | Officially described as the target model for parallel subagent execution inside Codex multi-model workflows |
| 400k context window | Handles large codebase navigation and long document tasks at the mini tier |
| Multimodal reasoning | Supports text and image inputs with real-time image interpretation as a documented primary use case |
| Tool use reliability | Supports function calling, web search, file search, computer use, and skills natively via the /v1/responses endpoint |
GPT-5.4 Mini is deployed across the API, Codex (app, CLI, IDE extension, web), and ChatGPT (as the Thinking option for Free and Go users, and as a rate-limit fallback for other tiers). This cross-surface availability is unique among mini-tier models in the GPT-5.4 family - GPT-5.4 Nano, by contrast, is API-only.
Independent evaluations · Artificial Analysis
Evaluate specifications, pricing, and independent benchmark indices
| Model Details | |||
|---|---|---|---|
| General Info | |||
| Provider | OpenAI | Anthropic | Anthropic |
| Release Date | March 17, 2026 | July 24, 2026 | June 9, 2026 |
| Knowledge Cutoff | Aug 2025 | May 2026 | - |
| Context & Limits | |||
| Context Window | 400K | 1M Best Context Window | 1M Best Context Window |
| Pricing (per 1M tokens) | |||
| Input Pricing | $0.75 Best Input Pricing | $5 | $10 |
| Output Pricing | $4.50 Best Output Pricing | $25 | $50 |
| Modalities | |||
| Inputs | fileimagetext | textimage | textimagefile |
| Outputs | text | text | text |
| Benchmarks (0-100) | |||
| Intelligence Index | 30.5 | 63.1 Best Intelligence Index | 62.1 |
| Coding Index | - | 78.0 Best Coding Index | 76.5 |
| Agentic Index | - | 59.2 Best Agentic Index | 56.6 |
Graduate-level reasoning and expert Q&A evaluation.
Extremely difficult logical reasoning and knowledge.
Logical reasoning over long context windows.
Independent evaluation data provided by Artificial Analysis. To view the latest benchmarks and full details, visit their official site.
