LLM Models/GPT-5 Nano

GPT-5 Nano by OpenAI — 400K Context

Fastest, most cost-efficient version of GPT-5, ideal for summarization and classification tasks.

At a glance

Modalities

Context window

400,000

Pricing

$0.05 / $0.40

input / output per 1M

Reasoning

Standard
💸Price Calculator
Input1.0M
$0.05
Output0.5M
$0.20
Total: $0.25
0.2Coffee
🥇
0.0Gold (g)
🍕
0.1Pizza
🐄
0.0%Cow
🎮
0.0%RTX 5090

Capabilities

Streaming

Real-time token-by-token response streaming

Function calling

Connect the model to external tools and systems

Structured outputs

Return responses in JSON schema format

Web search

Search the internet for real-time information

File search

Search and retrieve from uploaded files

Code execution

Execute code in a sandboxed environment

Image generation

Generate images from text descriptions

Details

Knowledge cutoff 2024-05-31
Model ID gpt-5-nano
Provider OpenAI

Rate limits

Tier RPM TPM Batch queue
Tier1 500 200,000 2,000,000
Tier2 5,000 2,000,000 20,000,000
Tier3 5,000 4,000,000 40,000,000
Tier4 10,000 10,000,000 1,000,000,000
Tier5 30,000 180,000,000 15,000,000,000

What You Need to Know About GPT-5 Nano

Complete Overview of GPT-5 Nano by OpenAI

Get detailed information about GPT-5 Nano, including its context window of 400000 tokens, pricing per million tokens, supported input and output modalities, and benchmark scores. This model from OpenAI offers specific capabilities for natural language processing, code generation, and complex reasoning tasks that set it apart from alternatives.

Pricing and Cost Analysis for GPT-5 Nano

Compare input and output token pricing for GPT-5 Nano against other models in its class. Understanding LLM pricing is essential for budgeting your AI applications at scale. We break down the cost per million tokens for both input and output so you can estimate the total cost of your workloads and compare value across providers.

Benchmarks and Performance Metrics for GPT-5 Nano

Review benchmark performance data for GPT-5 Nano across key evaluation metrics. Compare its reasoning, coding, and language understanding capabilities against competing models to determine if it is the right fit for your specific requirements, whether that involves complex analysis, creative generation, or efficient inference at scale.