OpenAI

GPT 5.5

OpenAIToken-basedDynamic Pricing
Alias:gpt-5.5
Create API Key

Compare gpt-5.5 API pricing, supported endpoints, capabilities and access options on Modelsell.

textimagestreamingfunction_callingtoolsstructured_outputjson_modevisionweb_searchcachingreasoningcode_interpretercontext:1050000
Starting price
View full pricing
Context
1.1M
Maximum input window
Max output
128K
Maximum tokens per response
Modalities
→
Knowledge cutoff
Dec 2025
Released
Apr 2026

Pricing by Supplier

OpenAI
-40%
Openai官方接口
standardInput ≤ 272K tokens
Input/ 1M tokens
$3$5
Output/ 1M tokens
$18$30
Cache Read/ 1M tokens
$0.3$0.5
long_contextInput > 272K tokens
Input/ 1M tokens
$6$10
Output/ 1M tokens
$27$45
Cache Read/ 1M tokens
$0.6$1
Azure
-40%
微软云API直连,稳定可靠
standardInput ≤ 272K tokens
Input/ 1M tokens
$3$5
Output/ 1M tokens
$18$30
Cache Read/ 1M tokens
$0.3$0.5
long_contextInput > 272K tokens
Input/ 1M tokens
$6$10
Output/ 1M tokens
$27$45
Cache Read/ 1M tokens
$0.6$1
GPT官+AZ 混合
-40%
适合生产环境,az 和官 key 混合渠道
standardInput ≤ 272K tokens
Input/ 1M tokens
$3$5
Output/ 1M tokens
$18$30
Cache Read/ 1M tokens
$0.3$0.5
long_contextInput > 272K tokens
Input/ 1M tokens
$6$10
Output/ 1M tokens
$27$45
Cache Read/ 1M tokens
$0.6$1
GPT特价
-90%
适合vibe coding自用,gpt pro 号池
standardInput ≤ 272K tokens
Input/ 1M tokens
$0.5$5
Output/ 1M tokens
$3$30
Cache Read/ 1M tokens
$0.05$0.5
long_contextInput > 272K tokens
Input/ 1M tokens
$1$10
Output/ 1M tokens
$4.5$45
Cache Read/ 1M tokens
$0.1$1

Capabilities / Supported modalities

StreamingFunction callingToolsStructured outputVisionWeb searchPrompt cachingReasoningCode interpreter
Input
Output

Provider & data privacy

Provider
OpenAIDocs
Tokenizer
o200k_base
License
Proprietary (commercial)Proprietary
Data retention30 daysNot used for upstream training by default

Performance

Benchmarks

Scores on standardized evaluations. Higher percentages are better — and rank percentile shows

Metrics sourced fromArtificial Analysis 2026-09-30·GPT 5.5

This model is not included in the current benchmark snapshot.

Missing models or measurements are not zero scores.

Benchmark charts preserve the source model selection and reasoning settings. Missing models or measurements are not zero scores, and benchmark cost or speed is not this site’s service commitment.

About GPT 5.5

把复杂工作推进到可交付结果

GPT-5.5 适合需要同时理解大量材料、遵守多项约束并持续推进的任务。研发团队可以让它追踪跨文件故障、审查改动影响、制定迁移方案;产品和分析人员可以把需求、访谈、业务规则一起交给它,整理出有依据的决策建议。相比只问一个知识点,给它明确的完成目标与验收条件,更能发挥它在复杂专业工作中的作用。

它接受文本和图片,输出文字。你可以同时提供代码片段、错误日志和页面截图,让它把可见现象与实现逻辑联系起来;也可以让它检查流程图与方案说明是否一致。图片理解适合辅助分析,若要修改图片,需要另行接入相应的图像生成工具。

较大的上下文窗口便于放入长文档或较多代码,但材料仍应标明文件名、章节和优先级。要求它先建立证据索引,再执行分析,可以让结论更容易追溯。它还支持结构化输出与函数调用,适合把审核结果写成固定字段,或接入查询、计算、编辑等业务操作。

推理强度可按任务调整:简单整理可用较低强度,复杂排错、设计取舍可提高强度。联网检索、代码执行和文件操作需要在调用端配置工具与权限;如要自动处理任务,应明确哪些步骤可以执行、哪些结果需要人工复核。

常见问题

适合整个仓库的修改吗? 可以参与跨文件分析与实现,建议提供目录、入口、相关测试和改动边界,并用实际测试验证结果。

怎样避免长材料中的结论混淆? 为每份材料编号,要求逐项列出结论对应的证据,未提供的事实单独标记为待确认。

Use cases and prompting

一次给清楚任务边界

提供目标、相关材料、允许的操作和完成标准。复杂工作可要求先列出依赖与待验证假设,随后逐步执行。

请审查这次订单幂等改造。材料包含接口代码、表结构、并发日志和现有测试。
目标:找出重复扣款仍可能发生的路径。
按触发条件、执行顺序、数据库状态和修复建议逐项说明;每项引用文件或日志位置。
最后给出最小修改方案和能复现问题的测试,不要改动结算规则。

如需程序消费结果,预先定义 JSON 字段与缺失值规则;如允许调用工具,写明可读写范围,并要求完成后报告执行结果和验证证据。

API access

API documentation

Code samples

RequestPOST/v1/chat/completions
Example request
Parameters
ParameterTypeDefault / rangeDescription
temperature
number
=10 ~ 2
Sampling temperature; lower is more deterministic
top_p
number
=10 ~ 1
Nucleus sampling probability mass
max_tokens
integer>= 1Maximum number of tokens in the response
frequency_penalty
number
=0-2 ~ 2
Penalises repetition of frequent tokens
presence_penalty
number
=0-2 ~ 2
Encourages introducing new topics
stop
array—Up to 4 strings that stop generation
seed
integer—Deterministic sampling seed (best-effort)
n
integer
=1>= 1
Number of completions to generate
stream
boolean
=false
Stream tokens via Server-Sent Events
response_format
object—Force JSON object or schema-conforming output
tools
array—Tool / function declarations the model may call
tool_choice
string
autononerequired
Tool-choice policy or specific tool name
logprobs
boolean
=false
Return per-token log probabilities
top_logprobs
integer0 ~ 20Number of top log probabilities returned per token
logit_bias
object—Per-token logit bias map
user
string—End-user identifier for abuse monitoring

Replace <YOUR_API_KEY> with the API key from your token settings.

Authentication

All requests must include Authorization: Bearer <TOKEN> header. Anthropic-formatted endpoints accept the x-api-key header instead.

Generate tokens from the Tokens page; you can scope them to specific models, groups, IPs, and rate-limits.

Supported parameters

Generation parameters
ParameterTypeDefault / rangeDescription
temperature
number
=10 ~ 2
Sampling temperature; lower is more deterministic
top_p
number
=10 ~ 1
Nucleus sampling probability mass
max_tokens
integer>= 1Maximum number of tokens in the response
frequency_penalty
number
=0-2 ~ 2
Penalises repetition of frequent tokens
presence_penalty
number
=0-2 ~ 2
Encourages introducing new topics
stop
array—Up to 4 strings that stop generation
seed
integer—Deterministic sampling seed (best-effort)
n
integer
=1>= 1
Number of completions to generate
stream
boolean
=false
Stream tokens via Server-Sent Events
response_format
object—Force JSON object or schema-conforming output
tools
array—Tool / function declarations the model may call
tool_choice
string
autononerequired
Tool-choice policy or specific tool name
logprobs
boolean
=false
Return per-token log probabilities
top_logprobs
integer0 ~ 20Number of top log probabilities returned per token
logit_bias
object—Per-token logit bias map
user
string—End-user identifier for abuse monitoring

Rate limits

SupplierRPMTPMRPD
AzureUnlimitedUnlimitedUnlimited
defaultUnlimitedUnlimitedUnlimited
GPT官+AZ 混合UnlimitedUnlimitedUnlimited
GPT特价UnlimitedUnlimitedUnlimited
OpenAIUnlimitedUnlimitedUnlimited

No restriction

Frequently asked questions about gpt-5.5

What is gpt-5.5?

Compare gpt-5.5 API pricing, supported endpoints, capabilities and access options on Modelsell.

How do I call gpt-5.5?

Create an API key with access to gpt-5.5, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.

How is gpt-5.5 priced?

Pricing depends on the selected provider group and the model billing unit. The current input, output, request, or media prices are shown on this page before sign-up.

What is the context window of gpt-5.5?

The model catalog lists a context window of 1050000 tokens. Check the selected endpoint for request limits.

What is the maximum output of gpt-5.5?

The model catalog lists a maximum output of 128000 tokens. Your request settings may set a lower limit.

How should I evaluate gpt-5.5 for my project?

Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.