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GPT-5 Nano: Smallest, Fastest, and Most Cost-Efficient GPT-5 Model

GPT-5 nano is the smallest, fastest, and most cost-efficient variant within the GPT-5 family, designed for high-volume and resource-constrained applications. It was released on August 7, 2025 along with other models in its family, including GPT-5 and GPT-5 mini.

GPT-5 Nano emphasizes speed and low cost per token, while retaining core capabilities of GPT-5 such as reasoning and multimodal inputs in some configurations.

GPT-5 Nano Specs

The key specs of GPT-5 Nano include:

  • Context Window: 400,000 tokens, allowing it to handle very long documents and extended conversations.
  • Maximum Output Tokens: Up to 128,000 tokens, supporting multi-step, long-form content generation.
  • Speed and Efficiency: Latency around 3.13 seconds with high throughput (~92 tokens per second), making it the fastest in the GPT-5 family.
  • Cost Efficiency: Most cost-effective version with input token costs at about $0.05 per million tokens and output costs around $0.40 per million tokens.
  • Reasoning and Accuracy: Improved multi-step reasoning consistency and better domain-specific accuracy, particularly in technical, scientific, and multilingual contexts.
  • Multimodal Capabilities: Supports stable integration of text, code, and images in processing pipelines.

GPT-5 Nano Key Features

GPT-5 nano is optimized for low-latency, edge-friendly tasks while maintaining core GPT-5 capabilities like multimodal input support and structured outputs. Its core features include:

  • Edge-optimized and low latency: Designed for fast turnarounds in interactive tasks, GPT-5 nano comes with a smaller compute footprint than larger GPT-5 variants.
  • Multimodal input support: GPT-5 nano is capable of handling image inputs alongside text in prompts, aligned with GPT-5 family capabilities.
  • Smallest and fastest variant: GPT-5 nano was marketed as the entry point within GPT-5 for developers needing speed and efficiency.
  • Cost-conscious usage: GPT-5 nano offers lower input/output costs per token compared to larger models, suitable for high-frequency operations.
  • Enhanced practicality for developer tooling: GPT-5 nano focuses on rapid interactions, function calling, and structured outputs to facilitate integration into apps. ​
  • Consistent multi-task capabilities: Designed to balance prompt complexity with resource use, GPT-5 nano enables reliable performance across simple to moderately complex tasks.​

GPT-5 Nano vs GPT-5 Mini vs GPT-5

GPT-5 nano, GPT-5, and GPT-5 mini are typically presented as a tiered family with distinct trade-offs across context, speed, cost, and capabilities. Here’s a detailed, side-by-side comparison based on the latest model cards, official announcements, and industry analyses.

Aspect GPT-5 Nano GPT-5 Mini GPT-5
Context Window 400K tokens 400K tokens 400K tokens
Cost (Input / Output per 1M tokens) $0.05 / $0.40 $0.25 / $2.00 $1.25 / $10.00
Coding Performance 54.6% ★★★ ~65% ★★★★ 74.9% ★★★★★
Reasoning Performance Lower than Mini ★★ 85-95% of GPT-5 on easier tasks ★★★★ 94.6% ★★★★★
Speed/Latency Ultra-low latency, fastest ★★★★★ Faster than GPT-5 ★★★★ Standard, balanced for complex tasks ★★★
Overall Use Case Best for summarization, classification, and low-latency apps Efficient for well-defined, moderate tasks Flagship for advanced reasoning, coding, and agentic tasks

How to Access GPT-5 Nano

Accessing GPT-5 nano depends on your preferred platform. Here are the common ways:

  • OpenAI API (official): GPT-5 nano is officially available on OpenAI's API platform. Access to this model usually requires an API key and an approved usage plan. Availability can vary by region and account tier.
  • HIX AI: If you want to chat with GPT-5 nano right away, instead of accessing it through an API, you can try HIX AI. It offers GPT-5 nano with simple and smooth access with no region restrictions.

Questions and Answers

What tasks is GPT-5 nano best suited for?

What are the typical limitations of GPT-5 nano?

How does GPT-5 nano handle multimodal inputs?

How do I choose among GPT-5 nano, mini, and GPT-5 for a project?

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