GPT-5.5 on Genosai — a top model for code, analysis, and agentic tasks
GPT-5.5 is OpenAI's newest flagship text model, available on Genosai with a 250,000-token context. It is smarter and more token-efficient than GPT-5.4 and scores 82.7% on Terminal-Bench 2.0. On Genosai it runs online, with no OpenAI subscription or API setup.
Updated: July 7, 2026
- Strongest agentic code — 82.7% on Terminal-Bench 2.0, as the model plans, iterates, and coordinates tools in complex scenarios.
- Deep reasoning — GPT-5.5 sees the shape of a system better: why it fails, where to fix it, and what else is affected.
- 250,000-token context — Large codebases, documents, and long conversations fit within a single context window.
- Token efficiency — The model is smarter than GPT-5.4 and spends fewer tokens on the same task.
- File support — Upload documents and images, and GPT-5.5 reads them and answers based on their content.
Contents
- What is GPT-5.5
- Capabilities
- Examples prompts and responses
- How to use on Genosai
- Prompts
- How it compares
- Limitations and tips
- FAQ
What is GPT-5.5
GPT-5.5 is OpenAI's newest flagship text model, announced on April 23, 2026 and available in the API the next day alongside GPT-5.5 Pro. It is the smartest and most intuitive model in the GPT-5.x line at launch: it understands what you are trying to do faster and carries more of the work itself. On Genosai the model is available online, so you do not need an OpenAI account, API keys, or your own infrastructure.
The main difference from GPT-5.4 is depth and efficiency. According to the developer, on the internal Expert-SWE benchmark for long-horizon coding tasks GPT-5.5 scores 73.1% versus 68.5% for GPT-5.4, and on Terminal-Bench 2.0 it reaches 82.7%, a state-of-the-art result for command-line work. At the same time the model is more token-efficient: on the same task it spends fewer tokens than GPT-5.4. So the higher price per request is partly offset by the model doing more in a single pass.
Another strength is understanding the shape of a system. Early testers noted that GPT-5.5 is better at seeing why something is failing, where the fix needs to land, and what else in the codebase it will affect. That makes the model handy for refactoring, debugging, and architecture decisions, not just writing code from scratch.
Who should reach for GPT-5.5 first. Developers and teams who trust the model with complex code tasks: architecture review, code review, and hunting down non-obvious bugs. Analysts and consultants who need depth of reasoning and well-founded conclusions, not just smooth text. And anyone for whom answer quality matters more than the cost per request: on high-stakes tasks, paying more for a smarter model pays off in the rework time you save. For simple, high-volume scenarios the model is overkill, and the junior versions of the line are better value there.
Capabilities
GPT-5.5 is a model for the most demanding text and code tasks. Here is where it is especially strong in practice.
Code and agentic scenarios
This is OpenAI's strongest agentic coding model at launch. It plans multi-step tasks, iterates, coordinates tools, and finishes tasks end-to-end in a single pass more often than previous versions. On SWE-Bench Pro the model scores 58.6%, on OSWorld-Verified 78.7%, and on Tau2-bench Telecom 98.0% without prompt tuning.
Deep reasoning and analysis
GPT-5.5 breaks complex questions into steps, compares options, and draws well-founded conclusions. On GDPval, which assesses the quality of expert knowledge work across 44 occupations, the model scores 84.9%. The 250,000-token context lets you keep a large document or codebase in view in full.
Text and structure
The model confidently writes complex text: technical articles, breakdowns, and long structured answers. It holds logic over a long distance and does not lose the thread in large material.
Working with files
GPT-5.5 accepts uploaded documents and images and answers based on their content, which is handy for reviewing specifications, reports, and code from files.
Planning and multi-step tasks
GPT-5.5's strength shows most where an answer cannot be delivered in a single reply. The model can build a plan, hold it in mind through the conversation, and carry the task to a result step by step: from decomposition to a check. That helps with feature design, preparing technical solutions, and any scenario where you need not just an answer but a path through several connected steps under constraints.
Examples prompts and responses
Below are real GPT-5.5 responses produced on Genosai. Prompts and text are shown unchanged.
Prompt: Draft a Telegram post outline for launching a new cosmetics line: 5 bullet points with short subheadings.
GPT-5.5 response:
- Meet the Line
Introducing our new cosmetics collection designed for everyday confidence and effortless beauty.
- Key Products
Highlight the must-haves: foundation, lip shades, blush, mascara, and skincare-infused essentials.
- Why You'll Love It
Lightweight textures, flattering shades, long-lasting wear, and formulas made for real routines.
- Launch Offer
Celebrate with an exclusive first-week discount, bundle deal, or limited-edition gift with purchase.
- How to Shop
Share the launch date, store link, availability, and a call to action: Tap to explore the collection._Generated on Genosai.io with the GPT-5.5 model._
The second example shows how the model explains metrics and keeps clean formulas.
Prompt: Explain in simple terms the difference between ROAS and ROMI in online advertising, with a numeric example.
GPT-5.5 response:
ROAS and ROMI are both used to measure ad performance, but they answer slightly different questions.
ROAS: Return on Ad Spend
ROAS measures how much revenue you made for every dollar spent on advertising.
Formula: ROAS = Revenue / Ad Spend
Example
If you spend $1,000 on online ads and generate $5,000 in sales:
ROAS = 5000 / 1000 = 5
So your ROAS is 5x, or 500%. For every $1 spent on ads, you made $5 in revenue.
ROMI: Return on Marketing Investment
ROMI measures profit compared to the marketing cost. It usually accounts for the cost of the product or service, not just revenue.
Formula: ROMI = (Profit - Marketing Cost) / Marketing Cost_Generated on Genosai.io with the GPT-5.5 model._
How to use on Genosai
- Sign in to your Genosai account and open the text studio.
- In the model list, pick GPT-5.5 under the OpenAI section.
- If needed, attach a file, spec, or code snippet.
- State the task in detail: for complex code, describe the context, goal, and constraints.
- Send the request and ask the model to explain its solution or propose alternatives.
- Continue the conversation, refining details, since the model holds a long context well.
Prompts
These templates are built for GPT-5.5's strengths: complex, multi-step tasks with context. Give the model as much input as you can: code, specs, constraints, and the goal. The fuller the prompt, the deeper the analysis and the higher the return on a more expensive model.
Review this module's architecture, find weak spots, and propose a refactor with reasoning: [paste code]Build a step-by-step implementation plan for the feature [description]: stages, risks, and checkpoints.Find the root cause of a bug from the description and logs, explain the chain, and propose a fix: [paste log]Write an 800-word technical breakdown of [topic] with examples and conclusions.Compare two approaches [A] and [B] by performance, cost, and maintenance, and give a recommendation.Review this pull request: logic, bugs, style, and what to improve: [paste diff]Build a set of test cases for the function [description], including edge cases.Generation cost
On Genosai GPT-5.5 is billed by tokens — you pay for the actual size of the prompt and the answer, so a short question is cheaper than a long analysis. A typical request costs roughly 12 credits. The final amount depends on prompt length and answer size.
Starter credits after sign-up let you try GPT-5.5 for free, and top-ups work with local cards without a VPN. See current rates and balance on the Pricing page.
How it compares
GPT-5.5 is the peak of the GPT line in the catalog. If the task is simpler and you want to save, pick GPT-5.4 or the even more affordable GPT-5.4 Mini. Among top models from other developers in the same class are Claude Opus 4.8 and Gemini 2.5 Pro.
| Model | Context on Genosai | Cost per request | Strength |
|---|---|---|---|
| GPT-5.5 | 250,000 | 12 credits | Agentic code and depth |
| GPT-5.4 | 380,000 | 3 credits | Balance of accuracy and price |
| GPT-5.4 Mini | 380,000 | 2 credits | Speed and volume |
| Claude Opus 4.8 | see the model page | — | Complex reasoning |
All models run in one Genosai interface, so you can test them on your own task and pick the best fit by depth and price. A sensible pattern is to use GPT-5.5 selectively: turn it on for genuinely hard tasks where depth of reasoning directly shapes the result, and hand routine work and drafts to the junior models. That way you get the most from the flagship where it counts and avoid overpaying where a simpler model is enough.
Limitations and tips
GPT-5.5 is the most powerful but also the most expensive GPT model on Genosai: 12 credits per request. Running it on simple tasks like short posts is not cost-effective, and GPT-5.4 and Mini exist for that. Like any model, GPT-5.5 can be wrong on niche facts and recent events, so important data is worth checking against a primary source. The model has no built-in web search on Genosai.
To get the most out of the model, give it complex tasks and plenty of context: a detailed description, code, specs, and constraints. It is built for depth, so the more detailed the input, the more useful the result. Ask it to explain its solutions and propose alternatives, so you get not just an answer but the reasoning behind it.
Note the context: on Genosai GPT-5.5 has 250,000 tokens, less than GPT-5.4 with its 380,000. For very large documents that is worth keeping in mind: if the material does not fit in full, split it into parts or compress it to the essentials first. Otherwise 250,000 tokens is plenty for large codebases and long discussions. And for streaming, simple scenarios, switch to GPT-5.4 to avoid overpaying with credits, since keeping the most expensive model on drafts makes little sense.
FAQ
What is GPT-5.5 and when was it released?
GPT-5.5 is OpenAI's newest flagship text model, announced on April 23, 2026 and available in the API the next day. It is the smartest model in the line at launch. On Genosai it runs online without a separate OpenAI subscription.
How is GPT-5.5 different from GPT-5.4?
GPT-5.5 is smarter and more token-efficient: on the Expert-SWE benchmark it scores 73.1% versus 68.5% for GPT-5.4. It is stronger at agentic code and deep reasoning. GPT-5.4, meanwhile, is cheaper per request and fits everyday tasks well.
What context does GPT-5.5 have on Genosai?
On Genosai the model works with a 250,000-token context. That is enough for large codebases, long documents, and extended conversations. The model also reads uploaded files and images.
How much does one GPT-5.5 request cost?
One request to GPT-5.5 on Genosai costs 12 credits. It is the most powerful and therefore the most expensive GPT model in the catalog. You pay for actual generations, with no subscription.
What tasks is GPT-5.5 best for?
The model excels at complex code, agentic scenarios, architecture analysis, and tasks where depth of reasoning matters. For simple, high-volume work, GPT-5.4 or GPT-5.4 Mini is better value.
Do I need an OpenAI subscription for GPT-5.5?
No. Genosai gives you access to GPT-5.5 straight in the browser, with no OpenAI account, API keys, or setup. Just sign in to Genosai and pick the model in the text studio.