GPT-5 Nano — OpenAI | Modeldex

GPT-5 Nano

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GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger...

Updated 4 days agoStructured data from Modeldex catalog

VisionAgenticLong contextBudget

Knowledge cutoff

May 31, 2024(1.9 years ago)

API release

Aug 7, 2025(8 months ago)

Not enough benchmark coverage yet for an Intelligence Index — needs at least 3 results across 2 categories.

Overview

History

GPT-5 Nano became available via the OpenAI API on 2025-08-07.

Training & availability

Training data has a knowledge cutoff of 2024-05-31 — information about events after that date is unlikely to appear in the model's responses. OpenAI has not released the underlying model weights — access is via their hosted API only.

Capabilities

Context window: 272K tokens.
Max output: 128K tokens.
Input modalities: text, image, file.

Recommended for: vision, agentic, long-context, cheap.

Limitations

The knowledge cutoff is 22 months old — this model will not know about recent events, releases, or API changes.

Pricing

Input: $0.0500 per 1M tokens
Output: $0.4000 per 1M tokens

Use the cost calculator above to estimate monthly spend for your workload.

Quick start

Minimal example using the openai API. Copy, paste, replace the key.

from openai import OpenAI

client = OpenAI(api_key="sk-...")
resp = client.chat.completions.create(
    model="gpt-5-nano",
    messages=[{"role": "user", "content": "Explain quantum computing in one sentence."}],
)
print(resp.choices[0].message.content)

Cost calculator

Estimate your monthly bill. Presets are typical workload sizes.

Input tokens / month5.0M

@ $0.05/1M

Output tokens / month2.0M

@ $0.4/1M

Input cost

$0.25

5.0M × $0.05/1M

Output cost

$0.8

2.0M × $0.4/1M

Total / month

$1.05

$12.6 / year

Integrations & tooling support

Tool calling: Supported
Structured outputs: Not supported

Price vs quality

Budget pricing

Priced low — good for high-volume tasks. Quality tier pending more benchmark coverage.