OpenAI: o3

Public pricingIntelligence 81/100Large memory视觉深度思考工具调用

OpenAI: o3 是一款多模态模型，适合编码、调试和技术工作。它结合了多模态输入处理、强大的编码能力、200K tokens上下文和均衡成本定位，可在coding, debugging, and technical writing中提供可靠表现。它适合重视准确性、上下文与控制的团队，能带来稳定输出、灵活部署与扩展空间。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。

Input

$2.00/1M

Output

$8.00/1M

Cached

$0.50/1M

Batch

$1.00/1M

Calculate your o3 bill.

Set your workload — see cost at your exact volume.

What would o3 cost you?

Adjust the workload to see your monthly bill.

1,00010,00050,000250,0001M10M

Technical specifications

o3 at a glance.

Memory

200,000

tokens

Max reply

100,000

tokens

Memory tier

Large

an entire book or large codebase

Tokenizer

tiktoken-o200k

Released

Apr 2025

Training cutoff

Jun 2024

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • frontiermath_tier_4

    2.08

  • gpqa_diamond

    82.7

  • humanitys_last_exam

    20.32

  • mmlu

    85.3

  • scipredict

    17.94

  • swe_bench_verified

    69.1

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick o3

  • Multi-step reasoning, research agents, or hard math.
  • Screenshot analysis, image understanding, or document OCR.
  • Agentic workflows that call tools or APIs.
  • Long documents, full codebases, or extensive chat histories.

When to look elsewhere

  • Very latency-sensitive, real-time apps where every millisecond counts.

Alternatives

Similar models to compare.

FAQ

o3 — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, o3 costs roughly $470 per month. Input is $2.00 /1M tokens and output is $8.00 /1M tokens.
o3 has a 200,000-token context window (large memory — an entire book or large codebase). That means you can fit about 37,500 words of input and history in a single call.
Beyond text generation, o3 supports understanding images, deep step-by-step reasoning, calling functions / tools, strict JSON output. It streams replies by default.
o3 was released in April 2025, with training data cut off around June 2024.
Models in a similar class include o4 Mini Deep Research, GPT-5.2, GPT-5.2-Codex. The "Similar models" section below this FAQ links into each.

Still unsure?

Compare o3 against 100+ other models.

Open the full wizard — pick a use case, set your usage, and see side-by-side monthly costs in under a minute.

Open the comparison wizard