模型广场

Balanced general-purpose model covering dialogue, coding, and multilingual tasks at reasonable speed and cost for assistants and routine agent workflows.

上下文

128K

输入 / 1M tokens

$2.5

输出 / 1M tokens

$10

缓存读 / 1M

$1.25

缓存写 / 1M

$0

Reliable all-rounder for everyday tasks.

上下文

400K

输入 / 1M tokens

$1.25

输出 / 1M tokens

$10

缓存读 / 1M

$0.125

缓存写 / 1M

-

ChatGPT product-line snapshot of GPT-5, tuned for natural multi-turn conversation and consistent tone rather than agentic reasoning workloads.

上下文

128K

输入 / 1M tokens

$1.25

输出 / 1M tokens

$10

缓存读 / 1M

$0.13

缓存写 / 1M

$0

The deep-reasoning flagship in the GPT-5 family, always running at high thinking effort and slower to respond, suited for hard analysis or coding where accuracy outranks speed.

上下文

400K

输入 / 1M tokens

$15

输出 / 1M tokens

$120

缓存读 / 1M

$0

缓存写 / 1M

$0

Successor to GPT-5 that scales reasoning depth to task difficulty, returning fast answers on simple prompts and slower deliberation on hard ones, fit for general assistant, coding, and tool-use work.

上下文

400K

输入 / 1M tokens

$1.25

输出 / 1M tokens

$10

缓存读 / 1M

$0.13

缓存写 / 1M

$0

Rolling snapshot of the GPT-5.1 build powering ChatGPT, tuned for natural multi-turn conversation rather than heavy reasoning workloads.

上下文

128K

输入 / 1M tokens

$1.25

输出 / 1M tokens

$10

缓存读 / 1M

$0.13

缓存写 / 1M

$0

Previous flagship. Strong reasoning at a lower price.

上下文

400K

输入 / 1M tokens

$1.75

输出 / 1M tokens

$14

缓存读 / 1M

$0.175

缓存写 / 1M

-

Snapshot pointer to the GPT-5.2 Instant model that powers ChatGPT, optimized for everyday chat, writing, and light coding.

上下文

128K

输入 / 1M tokens

$1.75

输出 / 1M tokens

$14

缓存读 / 1M

$0.175

缓存写 / 1M

$0

Flagship reasoning model tuned for agentic coding and long-context analysis, with steadier instruction following and fewer hallucinations on high-stakes workflows.

上下文

400K

输入 / 1M tokens

$21

输出 / 1M tokens

$168

缓存读 / 1M

-

缓存写 / 1M

-

Chat-tuned everyday model that talks more naturally and refuses less, with better factual accuracy on common questions.

上下文

128K

输入 / 1M tokens

$1.75

输出 / 1M tokens

$14

缓存读 / 1M

$0.175

缓存写 / 1M

$0

High-quality coding with stable refactoring.

上下文

256K

输入 / 1M tokens

$1.75

输出 / 1M tokens

$14

缓存读 / 1M

$0.175

缓存写 / 1M

$0

Lightweight variant in the gpt-5.4 family, tuned for low-latency, high-volume tasks like classification, extraction, and sub-agent execution.

上下文

1M

输入 / 1M tokens

$2.5

输出 / 1M tokens

$15

缓存读 / 1M

$0.25

缓存写 / 1M

$0

Flagship GPT-5.4 variant with chain-of-thought reasoning tuned for agentic coding and multi-step problem solving on high-stakes tasks.

上下文

1.1M

输入 / 1M tokens

$30

输出 / 1M tokens

$180

缓存读 / 1M

$0

缓存写 / 1M

$0

GPT-5.5 natively supports video comprehension, speech emotion recognition, and autonomous tool calling, delivering omni-modal foundational capabilities for agent-based execution of complex tasks.

上下文

1.1M

输入 / 1M tokens

$5

输出 / 1M tokens

$30

缓存读 / 1M

$0.5

缓存写 / 1M

$0

Reasoning-heavy GPT-5.5 tier tuned for long-horizon agentic coding and complex multi-step workflows, with image input.

上下文

1.1M

输入 / 1M tokens

$30

输出 / 1M tokens

$180

缓存读 / 1M

-

缓存写 / 1M

-

GPT-5.5 natively supports video comprehension, speech emotion recognition, and autonomous tool calling, delivering omni-modal foundational capabilities for agent-based execution of complex tasks.

上下文

1.1M

输入 / 1M tokens

$10

输出 / 1M tokens

$45

缓存读 / 1M

$1

缓存写 / 1M

$0

Top of the GPT-5.6 lineup, tuned for hard reasoning, multi-step coding, and agent runs that stretch over many turns. Well suited to CLI-driven development and problems that need to be worked through step by step.

上下文

1.1M

输入 / 1M tokens

$5

输出 / 1M tokens

$30

缓存读 / 1M

$0.5

缓存写 / 1M

$6.25

The middle rung of the GPT-5.6 lineup, tuned for daily dev work, general reasoning, and agent orchestration. Delivers reliable performance at a manageable cost for routine business workloads.

上下文

1.1M

输入 / 1M tokens

$2

输出 / 1M tokens

$12

缓存读 / 1M

$0.2

缓存写 / 1M

$2.5

Reasoning-focused variant in the o3 family that produces longer chain-of-thought traces and accepts image inputs. Suited for harder math proofs, scientific reasoning, and multi-step coding tasks, with more consistent outputs across repeated runs.

上下文

200K

输入 / 1M tokens

$20

输出 / 1M tokens

$80

缓存读 / 1M

$0

缓存写 / 1M

$0