DevTk.AI

GPT-5 Nano

OpenAI

Updated March 2026. GPT-5 Nano by OpenAI: $0.05/M input, $0.40/M output tokens. 128K context, 16K max output. Function Calling & JSON Mode. Free calculator + compare 40+ models.

Input Price

$0.05

per 1M tokens

Output Price

$0.40

per 1M tokens

Context Window

128K

tokens

Specifications

ProviderOpenAI
Model IDgpt-5-nano
Input Price$0.05 / 1M tokens
Output Price$0.4 / 1M tokens
Context Window128K tokens
Max Output16K tokens
Capabilities
textfunction_callingstructured_output
Release Date2026-03

Monthly Cost Estimates

Estimated monthly costs based on different daily usage levels (assuming 50% input / 50% output split).

Daily TokensMonthly CostAnnual Cost
10K $0.07 $0.81
50K $0.34 $4.05
100K $0.67 $8.10
500K $3.38 $40.50
1.0M $6.75 $81.00

About GPT-5 Nano

GPT-5 Nano is a large language model by OpenAI. It features a 128K token context window with up to 16K tokens of output per request. The model supports 3 capabilities: text, function_calling, structured_output.

At $0.05 per million input tokens and $0.4 per million output tokens, GPT-5 Nano is positioned as a cost-effective option in the OpenAI lineup. Use our Token Counter to estimate how many tokens your prompts use, and our Pricing Calculator to compare costs across all models.

GPT-5 Nano Key Details

  • Pricing: $0.05/M input tokens, $0.4/M output tokens
  • Context window: 128K tokens — good for standard conversations and tasks
  • Max output: 16K tokens per response
  • Capabilities: text, function_calling, structured_output
  • Released: 2026-03

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FAQ

How much does GPT-5 Nano cost?

GPT-5 Nano costs $0.05 per million input tokens and $0.4 per million output tokens. For a typical workload of 100K tokens/day, expect approximately $0.75/month.

What is GPT-5 Nano's context window?

GPT-5 Nano supports a context window of 128K tokens. This means your combined input prompt and output response can be up to 128K tokens. The maximum output per response is 16K tokens.

Is GPT-5 Nano good for my use case?

GPT-5 Nano supports text, function_calling, structured_output. As a budget-friendly model, it works well for high-volume tasks like classification, summarization, and simple generation. Use our Pricing Calculator to compare with alternatives.