GPT-5 Nano

Tool callingStructured outputReasoningImage input

Launch post Website Docs

Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs

Context: 400K
Released: 1y ago
Input / 1M tokens: $0.05
Output / 1M tokens: $0.40
Cached input / 1M tokens: $0.005

Sources:models.devOpenRouter

Benchmarks

DeepSWE is the primary coding benchmark where an exact model evaluation exists. Other sourced evaluations appear below; missing scores are not zero.

Not evaluated in DeepSWE 1.1 as of 2026-09-22. Results are only shown for exact model versions in the official dataset. Official leaderboard.

No benchmark results have been matched to this model yet.

Specifications

Developer: OpenAI
Model family: GPT
Type: Language model
Predecessor: —
Successor: —
Released: August 7, 2025
Model ID: openai/gpt-5-nano
Openness: Closed
License: —
Input modalities: text, image, file
Output modalities: text
Modality: text+image+file->text
Tokenizer: GPT
Max output tokens: 128K
Knowledge cutoff: 2024-05-30
Hugging Face: —
Source freshness: Metadata synced Oct 8, 2026, 10:17 PM UTC

Additional source evidence

Source model: openai/gpt-5-nano
Source family: gpt-nano
Last updated: 2025-08-07
Knowledge cutoff: 2024-05-30
Model context: 400K
Maximum input: 272K
Model output limit: 128K
Open weights: No
File attachments: Yes
Reasoning: Yes
Tool calling: Yes
Structured output: Yes
Temperature control: No

Complete source record (JSON)

{
  "id": "openai/gpt-5-nano",
  "name": "GPT-5 Nano",
  "description": "Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs",
  "family": "gpt-nano",
  "last_updated": "2025-08-07",
  "knowledge": "2024-05-30",
  "attachment": true,
  "reasoning": true,
  "tool_call": true,
  "structured_output": true,
  "temperature": false,
  "modalities": {
    "input": [
      "text",
      "image"
    ],
    "output": [
      "text"
    ]
  },
  "limit": {
    "context": 400000,
    "input": 272000,
    "output": 128000
  },
  "release_date": "2025-08-07",
  "open_weights": false
}

Infrastructure

Provider availability

All providers

Provider	Endpoint	Context	Input /M tokens	Output /M tokens	Cached input /M tokens	Cache write /M tokens	Uptime 1d	Data handling
OpenAI	openai/flex	400K	$0.02	$0.20	$0.0025	—	100.00%	ZDR: No Training: Unknown Prompt logging: Unknown Retention: Unknown ZDR source Privacy policy Checked 2026-10-15
OpenAI	openai/flexBatch pricing	400K	$0.02	$0.20	$0.0025	—	100.00%	ZDR: No Training: Unknown Prompt logging: Unknown Retention: Unknown ZDR source Privacy policy Checked 2026-10-15
Azure	azure	400K	$0.05	$0.40	$0.01	—	98.75%	ZDR: Yes Training: Unknown Prompt logging: Unknown Retention: Unknown ZDR source Privacy policy Checked 2026-10-15
Azure	azureBatch pricing	400K	$0.05	$0.40	$0.01	—	100.00%	ZDR: No Training: Unknown Prompt logging: Unknown Retention: Unknown ZDR source Privacy policy Checked 2026-10-15
OpenAI	openai	400K	$0.05	$0.40	$0.005	—	100.00%	ZDR: No Training: Unknown Prompt logging: Unknown Retention: Unknown ZDR source Privacy policy Checked 2026-10-15
OpenAI	openaiBatch pricing	400K	$0.05	$0.40	$0.005	—	100.00%	ZDR: No Training: Unknown Prompt logging: Unknown Retention: Unknown ZDR source Privacy policy Checked 2026-10-15
Azure	azure/swedencentral	400K	$0.06	$0.44	$0.01	—	100.00%	ZDR: Yes Training: Unknown Prompt logging: Unknown Retention: Unknown ZDR source Privacy policy Checked 2026-10-15
Azure	azure/swedencentralBatch pricing	400K	$0.06	$0.44	$0.01	—	100.00%	ZDR: No Training: Unknown Prompt logging: Unknown Retention: Unknown ZDR source Privacy policy Checked 2026-10-15

Provider data:OpenRouter

Text provenance

EU · product-scoped

OpenAI textGrain watermarking

In the EU, ChatGPT-generated text uses textGrain. OpenAI says API customers can opt in globally for select models, so watermarking depends on the product surface and configuration.

Official explanation