GPT-5.4 nano

OpenAI · GPT-5

OpenAI's cheapest GPT-5.4 route for fast classification, extraction, and lightweight coding subagents.

Type
language
Context
400K tokens
Max Output
128K tokens
Status
current
Input
$0.2/1M tok
Output
$1.25/1M tok
API Access
Yes
License
proprietary
classification extraction subagents low-cost multimodal automation
Released March 2026 · Updated April 4, 2026

Overview

Freshness note: Model capabilities, limits, and pricing can change quickly. This profile is a point-in-time snapshot last verified on April 4, 2026.

GPT-5.4 nano is OpenAI’s smallest GPT-5.4 model, launched alongside GPT-5.4 mini on March 17, 2026. It is intended for high-throughput supporting tasks where teams want the newest GPT-5.4-era quality improvements at the lowest possible cost.

Capabilities

GPT-5.4 nano is best for classification, extraction, ranking, lightweight coding help, and other bounded subagent tasks that do not justify a larger reasoning model. OpenAI explicitly recommends it for simpler supporting work inside multi-model systems, especially when fast turnaround matters more than deep open-ended analysis.

Technical Details

OpenAI’s current model docs list GPT-5.4 nano with a 400K context window and 128K max output. It accepts text and image input, returns text output, and supports the same modern API stack as the rest of the GPT-5.4 line, including web search, file search, image generation, code interpreter, MCP, and structured outputs.

That matters because GPT-5.4 nano is not just a cheap classifier. It can still participate in broader tool-based workflows, which makes it useful as the low-cost worker tier beneath larger coordinator models.

Pricing & Access

Published API pricing is:

  • Input: $0.20 per 1M tokens
  • Output: $1.25 per 1M tokens

Unlike GPT-5.4 mini, GPT-5.4 nano is API-only at launch. That makes it primarily a builder-facing model rather than a general ChatGPT-facing route.

Best Use Cases

Use GPT-5.4 nano for high-volume event labeling, document extraction, support-ticket triage, ranking, enrichment, and narrow coding subtasks delegated from a larger model. It is a strong fit when a system needs many cheap, parallel support calls with better reliability than the older GPT-5 nano tier.

Comparisons

  • GPT-5.4 mini (OpenAI): Better for harder coding, computer use, and agentic execution, but materially more expensive.
  • GPT-5 nano (OpenAI): Older ultra-cheap baseline that OpenAI now positions below this newer nano tier.
  • Gemini 2.5 Flash-Lite (Google): Comparable category for high-frequency lower-cost work, with tradeoffs mostly driven by ecosystem and multimodal tooling fit.