GPT-5.5
GPT-5.5 is OpenAI's flagship frontier model with a 1M context window and five reasoning effort levels, optimized for autonomous agentic workflows and coding.
openaiGPT-5April 23, 2026About GPT-5.5
Learn about GPT-5.5's capabilities, features, and how it can help you achieve better results.
Transition to Agentic Intelligence
GPT-5.5 represents the transition from large language models to large agentic models. It is designed to function as an autonomous teammate rather than a simple chatbot, capable of planning, executing, and self-verifying complex workflows across digital environments. The model's primary innovation is the implementation of variable reasoning effort levels, which gives developers granular control over the model's thinking time and associated compute costs.
Technical Efficiency and Vision
Technically, GPT-5.5 maintains the 1-million-token context window of the GPT-5 family but introduces a 40% gain in token efficiency. This means that while per-token pricing has doubled relative to the 5.4 series, the effective cost for complex tasks is only 20% higher. The model's vision capabilities have also been significantly upgraded, now reaching near-human performance on technical diagrams and spatial reasoning tasks like ARC-AGI v2.
Optimization for Autonomy
It is particularly effective for autonomous coding, where it can manage entire repositories and verify its own bug fixes. By utilizing the new reasoning_effort parameter, users can toggle between five distinct logic depths, making it the first model to offer a sliding scale of intelligence for high-stakes problem solving.
Use Cases
Discover the different ways you can use GPT-5.5 to achieve great results.
Autonomous Software Engineering
Managing entire code repositories, fixing bugs, and deploying updates without human oversight.
Scientific Research Analysis
Processing thousands of research papers across a 1M window to synthesize novel hypotheses.
Complex Financial Modeling
Building and auditing intricate corporate finance structures with PhD-level mathematical precision.
Multi-Step Agentic Workflows
Creating and executing recursive task lists to achieve long-term digital objectives autonomously.
Technical Visual Analysis
Interpreting complex engineering blueprints and circuit diagrams for automated quality assurance.
High-Fidelity Data Compression
Converting massive datasets into token-dense summaries that preserve deep semantic nuances.
Strengths
Limitations
API Quick Start
openai/gpt-5.5
import OpenAI from "openai";
const openai = new OpenAI();
async function main() {
const response = await openai.chat.completions.create({
model: "gpt-5.5",
messages: [
{ role: "system", content: "You are an autonomous coding agent." },
{ role: "user", content: "Debug this Python repository and verify the fixes." }
],
reasoning_effort: "xhigh"
});
console.log(response.choices[0].message.content);
}
main();Install the SDK and start making API calls in minutes.
Community Feedback
See what the community thinks about GPT-5.5
“The hallucination rate is wild though, 86% on facts? It's like a genius who refuses to say 'I don't know'.”
“GPT-5.5 Pro is $180/mil output. We've officially entered the luxury era of AI.”
“The proto-AGI era has arrived. It's no longer a chatbot; it's a teammate.”
“The reasoning ladder with 5 effort levels is the most useful feature release since function calling.”
“OpenAI cooked with this one. It's expensive, but it actually works for high-end agentic work.”
“Across 20 benchmarks GPT-5.5 scores slightly higher than Opus 4.7 but it is also now $5/million tokens.”
Related Videos
Watch tutorials, reviews, and discussions about GPT-5.5
“They're calling this a new class of intelligence for real-world powering agents.”
“For ChatGPT-5.5 thinking, this is going to be available in plus, pro, business, and enterprise.”
“then the interesting thing with the API is it is going to be more expensive than GPT-5.4 at $5 per million tokens of input, $30 per million tokens of output.”
“I did not expect the tidal wave of pull requests and changes coming in as a result of engineers having so much intelligence.”
“I've seen a number of cases of this where we've had engineers run this model and work on a single task for more than 40 hours.”
“It's incredible how fast it is... we sort of expect we're gonna pay a price for more intelligence, but that has not been the case.”
“One step closer to AI that can actually help finish work.”
“It's positioning it as a more capable general worker for computers.”
“GPT-5.5 falls into a high category for cybersecurity-related risk under the company's preparedness framework.”
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Pro Tips
Expert tips to help you get the most out of GPT-5.5 and achieve better results.
Use Reasoning Effort xhigh
Set the reasoning_effort parameter to 'xhigh' for logic-heavy tasks like math and architectural design.
Leverage Large Context Window
Provide complete documentation and codebase context in the initial system prompt to take full advantage of the 1M window.
Implement Self-Critique Loops
Request a recursive review where the model critiques its first output to mitigate the native hallucination rate.
Agentic Verification
Utilize the xhigh effort level for agentic tasks to ensure the model self-verifies every step before moving to the next.
Testimonials
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Frequently Asked Questions
Find answers to common questions about GPT-5.5