Moduck

OpenAI: GPT-5.3 Codex

Coding-optimized GPT model for repository edits, reviews, and agentic software work

Model lab
OpenAI
Model family
gpt-codex
Modalitiestext, image, pdf → text
Context window400,000
Maximum output128,000
InputUSD 1.6 / 1M tokens
OutputUSD 6.4 / 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-5-3-codex.

import os
import requests

base_url = "https://api.moduck.ai/v1"
api_key = os.environ["MODUCK_API_KEY"]
model_id = "moduck/openai/gpt-5-3-codex"

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-5.3 Codex API Pricing

TypePrice information
InputUSD 1.6 / 1M tokens
OutputUSD 6.4 / 1M tokens
Cached inputUSD 0.4 / 1M tokens
Cache writeUSD 0 / 1M tokens

Benchmarks

Xhigh

Intelligence Index · v4.332.5
Coding Index—
Agentic Index—
BenchmarkScoreMeasurementSource
SWE-Atlas Codebase QnA32.6score · Harness: Codex
SWE-Atlas Refactoring42.38score · Harness: Codex
SWE-Atlas Test Writing38.98score · Harness: Codex

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 · Xhigh

Output speed97.5 tokens/s
Time to first token48.93 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
Xhigh97.5 tokens/s48.93 s——

Performance trends

Throughput97.5 tok/sCurrent
Time to first token48.93 sCurrent
End-to-end latency7.9 sCurrent
Throughput
Current97.5 tok/s
Window average96.0 tok/s
Time to first token
Current48.93 s
Window average23.7 s
End-to-end latency
Current7.9 s
Window average7.5 s
Tail latency (P99)
Current15.8 s
Window average17.2 s
Prompt cache hit rate
Current31.1%
Window average22.4%
Error rate
Current0.0%
Window average0.1%

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-5.3 Codex Compare models

ModelInput priceOutput priceContext windowCapabilities
GPT-5.3 CodexThis pageUSD 1.6 / 1M tokensUSD 6.4 / 1M tokens400,000Text output · Reasoning · Tool calling
GPT-5.2 CodexUSD 1.4 / 1M tokensUSD 11.2 / 1M tokens400,000Text output · Reasoning · Tool calling
GPT-5.2 ChatUSD 1.4 / 1M tokensUSD 11.2 / 1M tokens128,000Text output · Reasoning · Tool calling
GPT-5.1 ChatUSD 1 / 1M tokensUSD 8 / 1M tokens128,000Text output · Reasoning · Tool calling
GPT-5.1 CodexUSD 1 / 1M tokensUSD 8 / 1M tokens400,000Text output · Reasoning · Tool calling

Model specifications

Input
text, image, pdf
Output
text
Context window
400,000
Maximum input
272,000
Maximum output
128,000
Release date
2026-02-05
Attachments
Yes
Reasoning
Yes
Tool calling
Yes
Structured output
Yes
Temperature setting
Yes
Open weights
No

Frequently asked questions

What is GPT-5.3 Codex for?

Coding-optimized GPT model for repository edits, reviews, and agentic software work

What inputs and outputs does GPT-5.3 Codex support?

Recorded inputs: text, images, PDF; outputs: text.

How is GPT-5.3 Codex priced?

The pricing table shows the current recorded Moduck price. For example: Input USD 1.6 / 1M tokens; Output USD 6.4 / 1M tokens. See the pricing table for all units, variants, and conditions.

What specifications are recorded for GPT-5.3 Codex?

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-5-3-codex. 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.