GPT-5.5

GPT-5.5 is OpenAI’s current model for coding, tool use, and long multi-step work. It is available in ChatGPT, Codex, and the API, with $5 input pricing, $30 output pricing, and up to a 1M-token context window in the API.

If you are deciding whether to use GPT-5.5, the main question is not whether it is newer than GPT-5.4. It is whether your work is complex enough to justify a higher-cost model instead of GPT-5.4 or a smaller variant. This guide covers pricing, limits, access, and the jobs GPT-5.5 is best at.

GPT-5.5 at a glance

• Best for: coding, debugging, tool-heavy workflows, research, documents, and spreadsheets.
• Price: $5 input / $30 output per 1M tokens, with $0.50 cached input.
• Context window: 1M tokens in the API, with up to 128K output tokens.
• Use a smaller model if: your work is mostly fast drafts, summaries, or lower-cost repetitive tasks.

What GPT-5.5 is

GPT-5.5 is the OpenAI model to use when the task has to move across code, documents, tools, or software instead of staying inside a short chat answer. It is built for work that needs planning, follow-through, and fewer retries.

That makes it different from smaller or cheaper models. If the job is mostly summaries, drafts, or short questions, GPT-5.5 is probably too much model. If the job is messy, multi-step, or tool-heavy, it is the one to start with.

What changed from GPT-5.4

GPT-5.5 pushes OpenAI’s main work model further toward long-context reasoning, coding, and tool-heavy execution. The difference from GPT-5.4 is not just “newer model, slightly better answers.” The practical shift is that GPT-5.5 is better suited to long multi-step tasks where the model has to plan, use tools, keep context straight, and finish the job.

That also makes it a more expensive decision than GPT-5.4 for many teams. If your work is mostly short prompts and fast drafting, the difference may not justify the cost. If your work is debugging, spreadsheets, documents, coding agents, or heavy tool use, the jump is easier to justify.

• Longer context: GPT-5.5 is built for much larger working sets.
• Better tool use: stronger fit for coding, file work, search, and multi-step workflows.
• Higher cost ceiling: more capability, but also more ways to overspend if you send every task to it.

What GPT-5.5 is best at

GPT-5.5 is strongest when the work is messy, multi-step, and easier to evaluate by outcome than by single-turn brilliance. It is the model to start with when the job has to cross code, docs, spreadsheets, tools, or software surfaces instead of staying inside one neat prompt.

• Coding and debugging: especially where the model needs to inspect, plan, edit, and verify.
• Long-context analysis: large docs, large prompt histories, and multi-file source material.
• Tool-heavy workflows: search, file work, structured output, and agent-style task completion.
• Operational knowledge work: spreadsheets, documents, audits, and research that needs follow-through.

Where GPT-5.5 is available

GPT-5.5 is positioned as the main OpenAI model for work across ChatGPT, Codex, and the API. The key difference across surfaces is not the model name. It is the surrounding workflow: ChatGPT for interactive work, Codex for coding execution, and the API for product and automation use.

• ChatGPT: best when a person is still driving the task and wants reasoning plus tool support.
• Codex: best when the work is code-first and you need repo context, planning, and execution.
• API: best when you need full model control, long context, and programmatic integration.

Pricing and limits

GPT-5.5 is not the cheapest OpenAI model, and that is the point. The model is priced for serious work.

• API input: $5.00 per 1M tokens
• API output: $30.00 per 1M tokens
• Cached input: $0.50 per 1M tokens
• Context window: 1M tokens in the API
• Max output: 128K tokens
• Tools: functions, web search, file search, and computer use

The useful comparison is GPT-5.4: the base model is cheaper at $2.50 input and $15 output. That means GPT-5.5 is only the better buy when the task is complex enough that quality, persistence, or tool use matters more than raw cost.

• Context: up to 1M tokens in the API, with 128K output.
• Cost discipline: if your prompts regularly push into very large contexts, measure that workflow separately.

GPT-5.5 Pro

GPT-5.5 Pro is the higher-accuracy lane for users who want the most deliberate version of the model inside product surfaces. It is not the default recommendation for everyone. It is the option to reach for when the task is expensive to get wrong and the extra latency or spend is justified by the stakes.

If GPT-5.5 already feels like more model than your workflow needs, you probably do not need Pro. If GPT-5.5 is already the right fit and you are still pushing into harder reasoning or coding decisions, Pro is the tier to evaluate next.

GPT-5.5 vs GPT-5.4 vs smaller models

Use GPT-5.5 when the task is complex enough that fewer retries, better tool use, and longer context justify the premium. Use GPT-5.4 or a smaller model when the work is repetitive, fast, and cost-sensitive.

• Choose GPT-5.5 for: coding, long-context analysis, tool orchestration, and multi-step operational work.
• Choose GPT-5.4 for: strong general work when you do not need the full GPT-5.5 budget or context envelope.
• Choose a smaller model for: drafts, summaries, classification, extraction, and high-volume cheap tasks.

Capabilities, tools, and reasoning controls

GPT-5.5 is designed to work across structured output, tool use, search, file work, and software execution instead of behaving like a chat-only model. That matters because the model’s value is not just in the answer quality. It is in how well it stays useful once the task leaves the chat box.

The reasoning controls are equally important. If you leave the model in a deeper reasoning mode for every task, spend and latency climb fast. The better pattern is to use lighter effort for routine work and only push higher reasoning when the task is expensive to get wrong.

• Strong fit: function calling, structured outputs, file work, search, and software or agent workflows.
• Use higher reasoning for: debugging, planning, careful analysis, and tasks with multiple moving parts.
• Use lighter reasoning for: drafts, simple transformations, or other work where the main job is speed.

Who should use GPT-5.5

GPT-5.5 is built for developers, operators, analysts, and product teams doing real work with large context or tools. If the model needs to move across code, files, and software surfaces, GPT-5.5 makes sense quickly.

Who should skip GPT-5.5

Skip GPT-5.5 as your default if your workflow is mostly fast drafting, summaries, light chat, or other work where a smaller model is good enough. It is easy to overspend with GPT-5.5 if you use it as a reflex instead of a deliberate upgrade.

What to test before you commit to GPT-5.5

1. Run one real coding task that usually takes multiple retries on smaller models.
2. Run one long document or spreadsheet task that genuinely needs more context.
3. Measure tool-heavy workflows separately from plain chat so you know where the spend is coming from.
4. Compare outcome quality and end-to-end task cost, not just speed or token totals in isolation.

Final verdict

GPT-5.5 is the OpenAI model to look at when the work is serious enough that better reasoning, tool use, and task persistence matter. It is not the cheapest option, and it is not the right model for every job. But when the task is complex, GPT-5.5 is the one that makes the most sense.

If you are choosing between OpenAI models, the rule is simple: use GPT-5.5 for hard work, GPT-5.4 for cheaper work, and a smaller variant when speed and cost matter more than depth.

Frequently Asked Questions