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Model details

GPT-5.4-Nano

GPT-5.4 nano represents OpenAI's most compact model within the GPT-5.4 family, designed as a lightweight alternative that inherits key capabilities from its larger sibling while emphasizing speed and efficiency. The model is purpose-built for edge deployments and scenarios where minimizing latency is critical, filling a gap for developers who need capable AI but cannot accommodate the resource demands of frontier models. Its architecture supports text and image inputs with tool-calling functionality, making it suitable for responsive applications ranging from customer service automation to on-device processing where round-trip latency matters.

The release of GPT-5.4 nano in March 2026 rounds out a tiered model strategy that began with the full GPT-5.4, expanded with the mid-tier GPT-5.4 mini, and culminated in this ultra-efficient variant. OpenAI positions these smaller models as a "fast lane" for high-volume workloads where cost-per-query and throughput are primary concerns alongside quality. The nano model particularly targets scenarios with strict latency requirements, offering developers a path to integrate capable language intelligence into workflows where faster response times outweigh the need for maximum benchmark performance. This makes it a practical choice for subagent orchestration, real-time applications, and cost-sensitive production environments requiring a balance between capability and operational efficiency.

Poeopenai/gpt-5.4-nano

Quick Info

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Provider
Poe
Model key
openai/gpt-5.4-nano
Release date
Mar 11, 2026
Last updated
Mar 11, 2026
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.18
Output token cost
$1.10

Limits

Input tokens
272,000 tokens
Output tokens
128,000 tokens
Context window
400,000 tokens

Latest news about GPT-5.4-Nano

Poe

CoverageRelease Notes

EdTech Innovation Hub reports OpenAI's release of GPT-5.4 mini and nano, sourced from an OpenAI for Business LinkedIn post, positioning the models for high-volume workloads where organizations need to balance performance, cost, and latency. The article notes the models extend GPT-5.4's capabilities into more efficient The piece quotes OpenAI directly stating that GPT-5.4 nano is the smallest, cheapest GPT-5.4 model, optimized for classification, data extraction, ranking, and coding subagents. It discusses how nano and mini fit into a multi-model architecture where larger models handle planning and decision-making while smaller model

302.AI

CoverageBenchmark

Roboflow Playground maintains a model profile page for GPT-5.4 Nano with concrete technical specifications. The model is listed as a high-throughput, efficiency-optimized entry in the GPT-5.4 family, developed by OpenAI and released on March 17, 2026. It features a 400,000-token context window enabling processing of la The profile describes GPT-5.4 nano as a text-first worker optimized for high-volume classification, data extraction, ranking, and lightweight sub-agent orchestration where speed and low per-token cost are primary requirements. While it supports text and image inputs, it is not positioned as a specialized visual reasoni

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