Atlas / Models / OpenAI / OpenAI: o3 Mini

OpenAI: o3 Mini✓ Catalog verified

openai/o3-mini

OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. This model supports the `reasoning_effort` parameter, which can be set to "high", "medium", or "low" to control the thinking time of the model. The default is "medium". OpenRouter also offers the model slug `openai/o3-mini-high` to default the parameter to "high". The model features three adjustable reasoning effort levels and supports key developer capabilities including function calling, structured outputs, and streaming, though it does not include vision processing capabilities. The model demonstrates significant improvements over its predecessor, with expert testers preferring its responses 56% of the time and noting a 39% reduction in major errors on complex questions. With medium reasoning effort settings, o3-mini matches the performance of the larger o1 model on challenging reasoning evaluations like AIME and GPQA, while maintaining lower latency and cost.

Input price
$1.10 /1M
Output price
$4.40 /1M
Context
200K
Modalities
textfile
Released
Jan 31, 2025
Tool calling
✓ Yes
Atlas signal
92/100
01

Overview

OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. This model supports the `reasoning_effort` parameter, which can be set to "high", "medium", or "low" to control the thinking time of the model. The default is "medium". OpenRouter also offers the model slug `openai/o3-mini-high` to default the parameter to "high". The model features three adjustable reasoning effort levels and supports key developer capabilities including function calling, structured outputs, and streaming, though it does not include vision processing capabilities. The model demonstrates significant improvements over its predecessor, with expert testers preferring its responses 56% of the time and noting a 39% reduction in major errors on complex questions. With medium reasoning effort settings, o3-mini matches the performance of the larger o1 model on challenging reasoning evaluations like AIME and GPQA, while maintaining lower latency and cost.

Access: available through the official OpenAI API. Context window: 200K.

Pricing and metadata from the ModelsAtlas catalog.Last refreshed Aug 5, 2026
02

Specifications

API identifieropenai/o3-mini
ProviderOpenAI
Model typeText LLM
Context window200K catalog
Input modalitiestext · file
Output modalitiestext
ReleasedJan 31, 2025
TokenizerGPT
ModeratedYes
Architecture modalitytext+file->text
Supported parameters
include_reasoningmax_tokensreasoningresponse_formatseedstructured_outputstool_choicetools
Source: provider documentation + catalog feedMethodology →

API defaults

Default parameters
{
  "top_k": null,
  "top_p": null,
  "temperature": null,
  "presence_penalty": null,
  "frequency_penalty": null,
  "repetition_penalty": null
}
03

Pricing

Live pricing components for openai/o3-mini as published in the catalog.

$1.10
Input /1M
$4.40
Output /1M
Per request
Per image
Pricing componentRaw unit priceNormalizedUnit
Prompt tokens$0.0000011$1.10 / 1MPer input token
Completion tokens$0.0000044$4.40 / 1MPer output token
Request feeN/AN/APer request
Image feeN/AN/APer image unit
Web search feeN/AN/APer search request
Source: catalog pricing feedCompare all pricing →Cheapest models →
04

Cost calculator

Estimate monthly spend from your own token volumes.

Scale / Volume

Estimated Total Cost

$1.43Calculated from current list pricing in the ModelsAtlas catalog.
05

Capabilities

CapabilityStatusWhat it means
Visual UnderstandingNot advertisedImage and document analysis support
Audio ProcessingNot advertisedSpeech and voice aligned flows
Tool Calling✓ SupportedSupports tools / function calling
Self-HostingNot advertisedDeploy outside managed APIs
Derived from catalog capability tags and supported parameters
06

Capability signals

Directional signals derived from model metadata and capability tags — not official benchmark submissions.

OpenAI: o3 Mini
MMLU Signal (Reasoning)
97signal
Coding Signal (HumanEval proxy)
97signal
Math Signal (GSM8K proxy)
92signal
Science Signal (GPQA proxy)
83signal
Estimated from metadata — not an official benchmark runAll benchmarks →Methodology →
07

Quick start

Call OpenAI: o3 Mini through an OpenAI-compatible client.

from openai import OpenAI

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="openai/o3-mini",
    messages=[{"role": "user", "content": "Explain quantum physics."}]
)

print(response.choices[0].message.content)
08

Alternatives

Closest models by context window from a different provider.

09

Sources & attribution

Pricing and metadata are maintained in the ModelsAtlas catalog.

Capability bars use metadata tags — directional estimates onlyHow we source and verify data →
10

Frequently asked questions

How much does OpenAI: o3 Mini cost?

$1.10 per 1M input tokens and $4.40 per 1M output tokens on the official OpenAI API.

What is the context window of OpenAI: o3 Mini?

OpenAI: o3 Mini supports up to 200K tokens of context.

Does OpenAI: o3 Mini support tool / function calling?

Yes, OpenAI: o3 Mini supports tool / function calling — you can register tools and the model will emit structured tool calls.

How do I access OpenAI: o3 Mini?

Use the official OpenAI API with the model id `openai/o3-mini`. See the Quick start section above for code examples.