Moduck

OpenAI: GPT-5.5

Default frontier GPT for coding, computer use, research, and knowledge work

Model lab
OpenAI
Model family
gpt
Modalitiestext, image, pdf → text
Context window1,050,000
Maximum output128,000
InputUSD 4 / 1M tokens
OutputUSD 24 / 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-5-5.

import os
import requests

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

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-5.5 API Pricing

TypePrice information
InputUSD 4 / 1M tokens
OutputUSD 24 / 1M tokens

Benchmarks

High

Intelligence Index · v4.337
Coding Index71.6
Agentic Index34.3

Low

Intelligence Index · v4.330.7
Coding Index60.9
Agentic Index—

Medium

Intelligence Index · v4.333.8
Coding Index71.5
Agentic Index29.5

Non-reasoning

Intelligence Index · v4.323.2
Coding Index56.5
Agentic Index—

Xhigh

Intelligence Index · v4.338.4
Coding Index74.9
Agentic Index36.4
BenchmarkScoreMeasurementSource
SWE-Bench Pro58.6resolve rate · Date: 2026-05-28
Terminal-Bench78.2success rate · Harness: Terminus-2 · Version: 2.1 · Date: 2026-05-28
SWE-Atlas Codebase QnA45.43score · Harness: Codex
SWE-Atlas Refactoring44.79score · Harness: Codex
SWE-Atlas Test Writing42.59score · Harness: Codex
Artificial Analysis Coding Agent Index65.3average pass@1 · Variant: xhigh · Harness: Codex
SWE-Atlas Codebase QnA80.8pass@1 · Variant: xhigh · Harness: Codex
SWE-Bench Pro30.9pass@1 · Dataset: hard-aa · Variant: xhigh · Harness: Codex
Terminal-Bench84.1pass@1 · Variant: xhigh · Harness: Codex · Version: 2.1
Artificial Analysis Coding Agent Index60.4average pass@1 · Variant: medium · Harness: Codex
SWE-Atlas Codebase QnA79.1pass@1 · Variant: medium · Harness: Codex
SWE-Bench Pro26.2pass@1 · Dataset: hard-aa · Variant: medium · Harness: Codex
Terminal-Bench75.8pass@1 · Variant: medium · Harness: Codex · Version: 2.1
Artificial Analysis Coding Agent Index57.8average pass@1 · Variant: medium · Harness: Cursor CLI
SWE-Atlas Codebase QnA75pass@1 · Variant: medium · Harness: Cursor CLI
SWE-Bench Pro24.9pass@1 · Dataset: hard-aa · Variant: medium · Harness: Cursor CLI
Terminal-Bench73.4pass@1 · Variant: medium · Harness: Cursor CLI · Version: 2.1
Terminal-Bench82.7success rate · Version: 2.0 · Date: 2026-04-23
GPQA Diamond93.6accuracy · Date: 2026-04-23
Humanity's Last Exam41.4accuracy · Variant: no tools · Date: 2026-04-23
Humanity's Last Exam52.2accuracy · Variant: with tools · Date: 2026-04-23
OSWorld-Verified78.7success rate · Date: 2026-04-23
BrowseComp84.4accuracy · Date: 2026-04-23
MMMU Pro81.2accuracy · Variant: no tools · Date: 2026-04-23
ARC-AGI-285accuracy · Variant: Verified · Date: 2026-04-23
FrontierMath51.7accuracy · Dataset: Tier 1-3 · Date: 2026-04-23
FrontierMath35.4accuracy · Dataset: Tier 4 · Date: 2026-04-23
GDPval84.9wins or ties · Date: 2026-04-23
MCP Atlas75.3success rate · Date: 2026-04-23
Toolathlon55.6success rate · Date: 2026-04-23
τ²-Bench Telecom98success rate · Variant: original prompts · Date: 2026-04-23

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 · High

Output speed94.57 tokens/s
Time to first token12.64 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
High94.57 tokens/s12.64 s——
Low83.88 tokens/s1.45 s——
Medium78.57 tokens/s3.46 s——
Non-reasoning82.04 tokens/s0.87 s——
Xhigh96.28 tokens/s34.66 s——

Performance trends

Throughput94.57 tok/sCurrent
Time to first token12.64 sCurrent
End-to-end latency7.6 sCurrent
Throughput
Current94.57 tok/s
Window average93.0 tok/s
Time to first token
Current12.64 s
Window average13.7 s
End-to-end latency
Current7.6 s
Window average7.5 s
Tail latency (P99)
Current15.7 s
Window average16.7 s
Prompt cache hit rate
Current31.3%
Window average22.5%
Error rate
Current2.1%
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-5.5 Compare models

ModelInput priceOutput priceContext windowCapabilities
GPT-5.5This pageUSD 4 / 1M tokensUSD 24 / 1M tokens1,050,000Text output · Reasoning · Tool calling
GPT-5.4USD 1.44 / 1M tokensUSD 8.64 / 1M tokens1,050,000Text output · Reasoning · Tool calling
GPT-4.1USD 1.6 / 1M tokensUSD 6.4 / 1M tokens1,047,576Text output · Tool calling
GPT-4oUSD 1 / 1M tokensUSD 4 / 1M tokens128,000Text output · Tool calling
GPT-5.6 CyberUSD 10 / 1M tokensUSD 60 / 1M tokens400,000Text output · Reasoning · Tool calling

Model specifications

Input
text, image, pdf
Output
text
Context window
1,050,000
Maximum input
922,000
Maximum output
128,000
Release date
2026-04-23
Attachments
Yes
Reasoning
Yes
Tool calling
Yes
Structured output
Yes
Temperature setting
No
Open weights
No

Frequently asked questions

What is GPT-5.5 for?

Default frontier GPT for coding, computer use, research, and knowledge work

What inputs and outputs does GPT-5.5 support?

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

How is GPT-5.5 priced?

The pricing table shows the current recorded Moduck price. For example: Input USD 4 / 1M tokens; Output USD 24 / 1M tokens. See the pricing table for all units, variants, and conditions.

What specifications are recorded for GPT-5.5?

Current model records list Context window 1,050,000 tokens; Maximum output 128,000 tokens.

What model parameter does the Quickstart use?

The example uses moduck/openai/gpt-5-5. 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.