Model icon
gpt-5.5
Chat
Model:
GPT-5.5 API supports chat and coding for production assistants, coding agents, support tools, and structured reasoning workflows.
Chat

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Configuration
1.0
1.0
Pricing details

Transparent pricing with no hidden fees. Pay as you go.

OpenAIgpt-5.5
Input
PoYo price
$3.00/1M tokens
600 credits
Official price
$5.00/1M tokens
Official
You save
40%
OpenAIgpt-5.5
Output
PoYo price
$18.00/1M tokens
3600 credits
Official price
$30.00/1M tokens
Official
You save
40%

* Actual fees are based on the final output.

Introduction

Complete guide to using GPT-5.5 API for complex coding and high-value agents

GPT-5.5 API for complex coding and high-value agents

Run GPT-5.5 on PoYo when a request needs the strongest GPT layer: hard coding tasks, long professional reasoning, and tool-heavy agent workflows. Use /v1/chat/completions for existing chat clients or /v1/responses for newer reasoning and tool flows.

Available GPT-5.5 API model on PoYo

01

GPT-5.5

gpt-5.5 is available for chat, coding, reasoning, and agent workflows. PoYo meters input at 600 credits per 1M tokens and output at 3600 credits per 1M tokens.
View Documentation

Key features of GPT-5.5 API

GPT-5.5 should be reserved for the work where extra reasoning depth, long context, and tool execution quality matter more than raw request volume.

01

Flagship GPT layer for difficult work

Use GPT-5.5 as the upgrade route for codebase analysis, architecture review, multi-step planning, and tasks where weaker models usually need retries.

  • High-difficulty coding and reasoning
  • Best fit for expensive user actions
  • Clear escalation model above GPT-5.4
GPT-5.5 API

02

1M context with 128K output

The large context and long output budget fit repository-scale prompts, detailed specifications, and multi-file implementation plans without forcing early summarization.

  • 1M context window
  • 128K maximum output
  • Long-form technical answers
GPT-5.5 context and output

03

Responses API for tool-using agents

GPT-5.5 pairs well with Responses payloads when your application needs reasoning state, structured tool calls, and clearer agent orchestration.

  • /v1/responses for agent workflows
  • /v1/chat/completions for compatibility
  • Same PoYo key and usage tracking
OpenAI reasoning guide

04

Use it as an escalation route

Keep routine traffic on cheaper GPT models and route only complex, high-value requests to GPT-5.5 for better cost control.

  • Selective model routing
  • Good for premium tiers
  • 40% below official pricing on PoYo
OpenAI function calling

Best GPT-5.5 API use cases

01

Large codebase refactor agents

Ask GPT-5.5 to reason over repository context, migration goals, test failures, and staged implementation plans.

02

Multi-tool business agents

Use Responses workflows for agents that combine search, files, function calls, and structured outputs.

03

High-value professional analysis

Send legal, financial, product, or technical briefs when answer quality is worth the higher model tier.

04

Premium fallback routing

Escalate requests from GPT-5.4 or GPT-5.2 when confidence, complexity, or user tier requires a stronger model.

GPT-5.5 API model comparison

Choose by model generation, context window, latency profile, and token budget. PoYo keeps endpoint and billing workflows consistent across these chat models.

FeatureGPT-5.5GPT-5.4GPT-5.2Gemini 3.5 Flash
ProviderOpenAIOpenAIOpenAIGoogle
Endpoint supportChat + ResponsesChat + ResponsesChat + ResponsesChat + Gemini Native
Context window1M1M400K1M
Max output128K128K128K64K
PoYo input price$3.00 / 1M$1.05 / 1M$0.44 / 1M$0.90 / 1M
PoYo output price$18.00 / 1M$8.40 / 1M$3.50 / 1M$5.40 / 1M
Best fitHard coding, planning, tool-heavy agents, and high-value professional reasoning.Cost-aware GPT agentsStable previous frontier GPTFast multimodal agents

Model capabilities are summarized from official public documentation checked on May 21, 2026. PoYo prices are credit-based.

How to use GPT-5.5 API on PoYo

Step 1: Create a PoYo API key
Open the dashboard, generate an API key, and add credits for chat usage.
Create API Key

Step 2: Pick Chat Completions or Responses
Use /v1/chat/completions for existing OpenAI-compatible chat apps. Use /v1/responses for reasoning controls, tools, and newer response items.

Step 3: Send a request
curl --request POST \ --url https://api.poyo.ai/v1/responses \ --header 'Authorization: Bearer YOUR_API_KEY' \ --header 'Content-Type: application/json' \ --data '{ "model": "gpt-5.5", "input": "Design a test plan for a billing migration.", "reasoning": {"effort": "medium"} }'
View chat API docs

GPT-5.5 API pricing on PoYo

MeterPoYo creditsUSD equivalent
GPT-5.5 input600 credits / 1M tokens$3.00 / 1M tokens
GPT-5.5 output3600 credits / 1M tokens$18.00 / 1M tokens

PoYo pricing is positioned about 40% cheaper than official pricing. No subscription fees. Use one API key, dashboard usage tracking, and pay-as-you-go credits.

Frequently asked questions about GPT-5.5 API

What is GPT-5.5 best for?

Hard coding, planning, tool-heavy agents, and high-value professional reasoning.

Which endpoints does PoYo support for GPT-5.5?

PoYo supports /v1/chat/completions and /v1/responses for GPT chat models.

How much does GPT-5.5 cost on PoYo?

GPT-5.5 costs 600 credits per 1M input tokens and 3600 credits per 1M output tokens, equivalent to $3.00 input and $18.00 output per 1M tokens.

Can I test it before integrating?

Yes. The model page includes a playground for signed-in users, so you can test prompts and endpoint behavior before moving the model ID into production.

Why use PoYo for GPT-5.5 API access

01

Built for escalation routing

Keep GPT-5.5 for the requests that need the flagship GPT layer instead of paying flagship prices for every message.

02

Chat and Responses support

Use the same model through /v1/chat/completions or /v1/responses depending on how modern your client is.

03

Flagship model with usage pricing

PoYo lists GPT-5.5 at 600 input credits and 3600 output credits per 1M tokens, about 40% below official pricing.

04

Validate before production

Compare prompts in the playground, inspect usage, then move the same model ID into your production client.