Moduck

OpenAI: GPT-5.4 nano

Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation

Model lab
OpenAI
Model family
gpt-nano
Modalitiestext, image → text
Context window400,000
Maximum output128,000
InputUSD 0.16 / 1M tokens
OutputUSD 1 / 1M tokens

Quickstart

Use your Moduck API Key, set the API base URL to https://api.moduck.ai/v1, and set the model parameter to moduck/openai/gpt-5-4-nano.

import os
import requests

base_url = "https://api.moduck.ai/v1"
api_key = os.environ["MODUCK_API_KEY"]
model_id = "moduck/openai/gpt-5-4-nano"

response = requests.post(
    f"{base_url}/chat/completions",
    headers={
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/json",
    },
    json={
        "model": model_id,
        "messages": [{"role": "user", "content": "Hello!"}],
        "stream": False,
    },
    timeout=60,
)
response.raise_for_status()
print(response.json())

Use the familiar OpenAI-style chat request format to make model integration easier.

GPT-5.4 nano API Pricing

TypePrice information
InputUSD 0.16 / 1M tokens
OutputUSD 1 / 1M tokens
Cached inputUSD 0.016 / 1M tokens

Benchmarks

Medium

Intelligence Index · v4.320
Coding Index—
Agentic Index—

Non-reasoning

Intelligence Index · v4.311.7
Coding Index—
Agentic Index—

Xhigh

Intelligence Index · v4.320.7
Coding Index56.1
Agentic Index16
BenchmarkScoreMeasurementSource
SWE-Bench Pro52.4resolve rate · Variant: reasoning effort xhigh · Date: 2026-03-17
Terminal-Bench46.3accuracy · Variant: reasoning effort xhigh · Version: 2.0 · Date: 2026-03-17
MCP Atlas56.1score · Variant: reasoning effort xhigh · Date: 2026-03-17
Toolathlon35.5score · Variant: reasoning effort xhigh · Date: 2026-03-17
τ²-Bench Telecom92.5accuracy · Variant: reasoning effort xhigh · Date: 2026-03-17
GPQA Diamond82.8accuracy · Variant: reasoning effort xhigh · Date: 2026-03-17
Humanity's Last Exam37.7accuracy · Variant: with tools · Date: 2026-03-17
Humanity's Last Exam24.3accuracy · Variant: without tools · Date: 2026-03-17
OSWorld-Verified39success rate · Variant: reasoning effort xhigh · Date: 2026-03-17
MMMU Pro69.5accuracy · Variant: with Python · Date: 2026-03-17
MMMU Pro66.1accuracy · Variant: without tools · Date: 2026-03-17
OmniDocBench0.242overall edit distance · Variant: reasoning effort none · Version: 1.5 · Date: 2026-03-17
OpenAI MRCR44.2accuracy · Variant: 8-needle, 64K-128K · Version: v2 · Date: 2026-03-17
OpenAI MRCR33.1accuracy · Variant: 8-needle, 128K-256K · Version: v2 · Date: 2026-03-17
Graphwalks73.4accuracy · Variant: BFS, 0-128K · Date: 2026-03-17
Graphwalks50.8accuracy · Variant: parents, 0-128K · Date: 2026-03-17

Performance

Measured on the Moduck gateway across live traffic, hour by hour over the last 24 hours. Time to first token is how long before anything appears; throughput is how fast the answer is written after that; end-to-end latency is the whole round trip. Figures are medians unless the card says otherwise.

Artificial Analysis measurement · Medium

Output speed169.02 tokens/s
Time to first token3.06 s
Time to first answer token—
End-to-end response time—
Measurement variantOutput speedTime to first tokenTime to first answer tokenEnd-to-end response time
Medium169.02 tokens/s3.06 s——
Non-reasoning159.67 tokens/s0.64 s——
Xhigh163.46 tokens/s46.97 s——

Performance trends

Throughput169.02 tok/sCurrent
Time to first token3.06 sCurrent
End-to-end latency7.8 sCurrent
Throughput
Current169.02 tok/s
Window average163.1 tok/s
Time to first token
Current3.06 s
Window average3.2 s
End-to-end latency
Current7.8 s
Window average7.5 s
Tail latency (P99)
Current16.6 s
Window average16.5 s
Prompt cache hit rate
Current26.3%
Window average23.6%
Error rate
Current0.0%
Window average0.2%

Availability

Uptime is the share of time at least one provider serving this model responded. Availability is stricter: the share of requests actually served. A provider that answers but fails part of the traffic lowers availability without lowering uptime. Both cover the last three days.

Uptime100%At least one provider responded
Availability100%Requests actually served
Error rate0%Share of failed requests
Served requests, hour by hour
24 hours agoNow

GPT-5.4 nano Compare models

ModelInput priceOutput priceContext windowCapabilities
GPT-5.4 nanoThis pageUSD 0.16 / 1M tokensUSD 1 / 1M tokens400,000Text output · Reasoning · Tool calling
GPT-5 NanoUSD 0.02 / 1M tokens · Service tier flexUSD 0.16 / 1M tokens · Service tier flex400,000Text output · Reasoning · Tool calling
GPT-4.1 nanoUSD 0.064 / 1M tokensUSD 0.208 / 1M tokens1,047,576Text output · Tool calling
GPT-5.6 CyberUSD 10 / 1M tokensUSD 60 / 1M tokens400,000Text output · Reasoning · Tool calling
GPT-5.4 miniUSD 0.6 / 1M tokensUSD 3.6 / 1M tokens400,000Text output · Reasoning · Tool calling

Model specifications

Input
text, image
Output
text
Context window
400,000
Maximum input
272,000
Maximum output
128,000
Release date
2026-03-17
Attachments
Yes
Reasoning
Yes
Tool calling
Yes
Structured output
Yes
Temperature setting
Yes
Open weights
No

Frequently asked questions

What is GPT-5.4 nano for?

Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation

What inputs and outputs does GPT-5.4 nano support?

Recorded inputs: text, images; outputs: text.

How is GPT-5.4 nano priced?

The pricing table shows the current recorded Moduck price. For example: Input USD 0.16 / 1M tokens; Output USD 1 / 1M tokens. See the pricing table for all units, variants, and conditions.

What specifications are recorded for GPT-5.4 nano?

Current model records list Context window 400,000 tokens; Maximum output 128,000 tokens.

What model parameter does the Quickstart use?

The example uses moduck/openai/gpt-5-4-nano. This is a cataloged Moduck public or reserved ID; check your account’s available models before calling it.

Can I call this model through the Moduck API now?

This page has no verified Moduck API call for this model. A Quickstart example or reserved ID does not establish access; check the models available to your account.