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What is GPT-5.5?

GPT-5.5 is OpenAI's reasoning model for coding and professional work, released April 23, 2026, with API availability announced April 24. It accepts text and images and returns text; browsing, execution and file creation depend on connected tools. Checked September 8, 2026: the API model page still lists gpt-5.5-2026-04-23 as its snapshot. GPT-5.5 Pro and Instant are distinct variants. Later OpenAI releases do not change this page's subject or the specifications of standard GPT-5.5.

Context, Reasoning and API Cost

Bring a substantial evidence packet: The API documents a 1,050,000-token context window and a 128,000-token output limit. Give the model the relevant files and ask it to cite exact passages. Capacity does not guarantee complete recall; split the work when sources conflict or the answer becomes hard to inspect.
Choose reasoning effort explicitly: Supported API effort levels are none, low, medium, high and xhigh; medium is the default. Compare settings on the same task and measure accepted results and elapsed time. A higher setting is a trial option, not a guarantee of a better answer.
Budget for the whole session: Standard provider rates are USD $5 input, $0.50 cached input and $30 output per million tokens. Above 272,000 input tokens, the full session uses 2x input and 1.5x output pricing for standard, batch and flex. Regional processing adds 10%. These are API rates, not Ottermind prices.

Put GPT-5.5 to Work

Start with a deliverable whose correctness you can check, then expand the scope after a successful trial.

Find the cause of a recurring failure
Supply a failing test, logs and the relevant call path. Ask for competing explanations, a minimal reproduction and a patch tied to the observed failure. Run the reproduction before and after the fix; a plausible story is not evidence that the bug is gone.
Review a patch beyond passing tests
Provide the diff and the original requirement. Ask which assumptions about concurrency, object lifetime or permissions the tests do not cover. Request a concrete failure example for each finding, then inspect the affected code before accepting the recommendation.
Reconcile a spreadsheet report
Provide source rows, metric definitions and the current report. Ask for a reconciliation of totals, duplicate records and missing periods, with formulas or runnable checks. Inspect a sample against the source and verify the exported file in the application that will use it.
Build a decision memo from conflicting sources
Attach proposals, constraints and dated notes. Request options, evidence for each tradeoff and unresolved questions, with source references. Keep documented facts separate from assumptions so a reviewer can see what would change the recommendation.

GPT-5.5 vs GPT-5.4

Decision point	GPT-5.5	GPT-5.4
Standard API input / output per million tokens	USD $5 / $30	USD $2.50 / $15
Context / maximum output tokens	1,050,000 / 128,000	1,050,000 / 128,000
Default API reasoning effort	medium	none
When to evaluate it	Difficult diagnosis or review where fewer correction rounds could justify the higher rate	A lower-cost baseline for bounded tasks that already pass your acceptance checks

Decide by Accepted Work

Reasons to try GPT-5.5

Multi-step work with a clear finish: OpenAI's launch emphasizes tool-based coding and knowledge work. Test a complete loop: inspect evidence, propose a change and verify the result. Supply a stopping condition, such as a reproduced bug fixed with the existing checks passing.
A measurable upgrade trial: The GPT-5.4 documentation lists half the standard input and output rates. OpenAI reports fewer tokens on evaluated Codex tasks for 5.5. Compare total billed tokens, retries and review time before concluding that the higher-priced model saves money.

Where judgment still matters

Tests can miss the real requirement: Review invariants as well as test output. A patch can pass the current suite while breaking cleanup, concurrent requests or an undocumented compatibility requirement. Add the missing acceptance case before trusting the change.
Fresh facts need fresh evidence: The documented knowledge cutoff is December 1, 2025. Supply current documents or use a host with browsing for recent events and changing APIs. Ask for sources that can be opened; confident wording does not establish freshness.

What Community Users Report

These are individual workflows and a small community evaluation, not a consensus or a controlled model ranking.

Use the expensive reasoning where it matters

One coding-workflow author uses GPT-5.5 for architecture, debugging direction and review, with cheaper models handling repetitive implementation. Replies question costs and limits. This suggests a workflow to test, not a guaranteed saving or a transferable subscription allowance.

Passing tests and matching intent can diverge

A 21-task GraphQL evaluation reported 18 rather than 19 resolved tasks in a later run, and highlighted missed lifecycle and concurrency requirements. It used one run per condition, while some AI-grader review scores improved. The evidence supports checking deep assumptions, not declaring a universal quality collapse.

Continue the Work in Ottermind

Describe the outcome

Bring your source material, constraints and expected deliverable. Define the checks that make the result acceptable and the point at which work should stop.

Check access in Studio

Continue to Studio and sign in if needed. Select GPT-5.5 if available to your account and check tools and usage terms. This page does not automatically select the model or confirm its availability.

Verify and carry the result forward

Inspect sources, run the relevant checks and correct specific gaps. Keep the accepted output with its evidence so the next step starts from a reliable record.

GPT-5.5 FAQ

Is GPT-5.5 Instant the same API model?

No. The Instant announcement describes a separate conversational variant. The release notes also record product updates. Do not apply Instant features or GPT-5.5 Pro pricing to standard gpt-5.5.

Which API version does this page describe?

Standard gpt-5.5, with documented snapshot gpt-5.5-2026-04-23, checked September 8, 2026. The product's visible model picker and API snapshot list are separate sources of availability information.

Can it generate images or execute a spreadsheet?

Its native output is text. Image generation and code execution require supported tools in the host application. Describe the required file and verify the actual output rather than accepting a written claim of completion.

Is it faster or cheaper than GPT-5.4?

OpenAI reports comparable per-token latency and lower token use on evaluated Codex tasks, but standard token rates are twice GPT-5.4's. Total time and cost depend on effort, output length, tools, caching and retries. Measure your own completed task.

Turn a difficult task into a checked result

Bring the evidence, define the outcome and continue the work in Ottermind Studio.