LLMs

LLMs

o3-mini API

o3-mini is OpenAI’s compact AI model specifically designed for structured logical reasoning and analytical tasks.

1RPC.ai

Reasoning

Speed

$1.10

/

$4.40

Input/Output

200,000

Context Window

o3-mini

o3-mini is the compact yet capable variant of OpenAI’s reasoning-focused o3 family, launched on January 31, 2025. It builds on and surpasses the capabilities of the earlier o1-mini model by concentrating on deep technical reasoning with configurable effort levels to optimize performance or speed. Available to ChatGPT users including free-tier and API developers, o3-mini balances precision and accessibility in complex problem solving.

Focused on breaking down intricate STEM problems into manageable steps, o3-mini supports new developer features like function calling, structured outputs, and developer messages, making it production-ready and highly adaptable.

What it’s optimized for

o3-mini excels when tasked with:

  • Advanced step-by-step reasoning in STEM domains (science, math, coding)

  • Delivering accurate, safe, and deliberative responses via configurable reasoning effort

  • Balancing cost, speed, and quality for real-time interactive applications

  • Function calling and structured outputs for complex workflow automation

  • Scalable AI deployments requiring low latency and higher throughput

Typical use cases

o3-mini is well suited for:

  • Technical and scientific problem solving including graduate-level science questions

  • Coding assistance and competitive programming challenges

  • Automated STEM tutoring and interactive learning applications

  • Complex data analysis workflows leveraging function calls

  • Production AI systems needing robust reasoning and developer-centric features

Key characteristics

  • Adjustable reasoning effort levels: low, medium, and high to trade-off speed vs. quality

  • Supports function calling, structured outputs, and developer messages for production use

  • Streaming-enabled for responsive, interactive applications

  • Approximately 24% faster response times than its predecessor o1-mini, averaging 7.7 seconds to first token

Model architecture

o3-mini is founded on an optimized transformer architecture tailored for reasoning efficiency. It utilizes deliberative alignment methods to ensure safe and accurate answers and supports advanced developer functionalities. Its architecture enables it to break down and solve complex, multi-step tasks efficiently while maintaining responsiveness suitable for interactive AI applications.

Why choose 1RPC.ai for o3-mini

  • Every call is directly tied to the exact model and version used, ensuring traceability and trust in your outputs

  • Execution runs inside hardware-backed enclaves, so the relay can’t access or log your request

  • Connect to multiple AI providers through a single API

  • Avoid provider lock-in with simple, pay-per-prompt pricing

  • Privacy by design with our zero-tracking infrastructure that eliminates metadata leakage and protects your activity

Summary

o3-mini is OpenAI’s cost-efficient, reasoning-optimized AI model designed to democratize high-quality STEM problem-solving. With configurable reasoning effort, strong coding and math skills, developer-friendly features, and improved latency, it’s a versatile choice for applications needing technical rigor without heavy computational expense.

Perfect when you need advanced reasoning capabilities with fast, reliable, and economical performance.

o3-mini

o3-mini is the compact yet capable variant of OpenAI’s reasoning-focused o3 family, launched on January 31, 2025. It builds on and surpasses the capabilities of the earlier o1-mini model by concentrating on deep technical reasoning with configurable effort levels to optimize performance or speed. Available to ChatGPT users including free-tier and API developers, o3-mini balances precision and accessibility in complex problem solving.

Focused on breaking down intricate STEM problems into manageable steps, o3-mini supports new developer features like function calling, structured outputs, and developer messages, making it production-ready and highly adaptable.

What it’s optimized for

o3-mini excels when tasked with:

  • Advanced step-by-step reasoning in STEM domains (science, math, coding)

  • Delivering accurate, safe, and deliberative responses via configurable reasoning effort

  • Balancing cost, speed, and quality for real-time interactive applications

  • Function calling and structured outputs for complex workflow automation

  • Scalable AI deployments requiring low latency and higher throughput

Typical use cases

o3-mini is well suited for:

  • Technical and scientific problem solving including graduate-level science questions

  • Coding assistance and competitive programming challenges

  • Automated STEM tutoring and interactive learning applications

  • Complex data analysis workflows leveraging function calls

  • Production AI systems needing robust reasoning and developer-centric features

Key characteristics

  • Adjustable reasoning effort levels: low, medium, and high to trade-off speed vs. quality

  • Supports function calling, structured outputs, and developer messages for production use

  • Streaming-enabled for responsive, interactive applications

  • Approximately 24% faster response times than its predecessor o1-mini, averaging 7.7 seconds to first token

Model architecture

o3-mini is founded on an optimized transformer architecture tailored for reasoning efficiency. It utilizes deliberative alignment methods to ensure safe and accurate answers and supports advanced developer functionalities. Its architecture enables it to break down and solve complex, multi-step tasks efficiently while maintaining responsiveness suitable for interactive AI applications.

Why choose 1RPC.ai for o3-mini

  • Every call is directly tied to the exact model and version used, ensuring traceability and trust in your outputs

  • Execution runs inside hardware-backed enclaves, so the relay can’t access or log your request

  • Connect to multiple AI providers through a single API

  • Avoid provider lock-in with simple, pay-per-prompt pricing

  • Privacy by design with our zero-tracking infrastructure that eliminates metadata leakage and protects your activity

Summary

o3-mini is OpenAI’s cost-efficient, reasoning-optimized AI model designed to democratize high-quality STEM problem-solving. With configurable reasoning effort, strong coding and math skills, developer-friendly features, and improved latency, it’s a versatile choice for applications needing technical rigor without heavy computational expense.

Perfect when you need advanced reasoning capabilities with fast, reliable, and economical performance.

o3-mini

o3-mini is the compact yet capable variant of OpenAI’s reasoning-focused o3 family, launched on January 31, 2025. It builds on and surpasses the capabilities of the earlier o1-mini model by concentrating on deep technical reasoning with configurable effort levels to optimize performance or speed. Available to ChatGPT users including free-tier and API developers, o3-mini balances precision and accessibility in complex problem solving.

Focused on breaking down intricate STEM problems into manageable steps, o3-mini supports new developer features like function calling, structured outputs, and developer messages, making it production-ready and highly adaptable.

What it’s optimized for

o3-mini excels when tasked with:

  • Advanced step-by-step reasoning in STEM domains (science, math, coding)

  • Delivering accurate, safe, and deliberative responses via configurable reasoning effort

  • Balancing cost, speed, and quality for real-time interactive applications

  • Function calling and structured outputs for complex workflow automation

  • Scalable AI deployments requiring low latency and higher throughput

Typical use cases

o3-mini is well suited for:

  • Technical and scientific problem solving including graduate-level science questions

  • Coding assistance and competitive programming challenges

  • Automated STEM tutoring and interactive learning applications

  • Complex data analysis workflows leveraging function calls

  • Production AI systems needing robust reasoning and developer-centric features

Key characteristics

  • Adjustable reasoning effort levels: low, medium, and high to trade-off speed vs. quality

  • Supports function calling, structured outputs, and developer messages for production use

  • Streaming-enabled for responsive, interactive applications

  • Approximately 24% faster response times than its predecessor o1-mini, averaging 7.7 seconds to first token

Model architecture

o3-mini is founded on an optimized transformer architecture tailored for reasoning efficiency. It utilizes deliberative alignment methods to ensure safe and accurate answers and supports advanced developer functionalities. Its architecture enables it to break down and solve complex, multi-step tasks efficiently while maintaining responsiveness suitable for interactive AI applications.

Why choose 1RPC.ai for o3-mini

  • Every call is directly tied to the exact model and version used, ensuring traceability and trust in your outputs

  • Execution runs inside hardware-backed enclaves, so the relay can’t access or log your request

  • Connect to multiple AI providers through a single API

  • Avoid provider lock-in with simple, pay-per-prompt pricing

  • Privacy by design with our zero-tracking infrastructure that eliminates metadata leakage and protects your activity

Summary

o3-mini is OpenAI’s cost-efficient, reasoning-optimized AI model designed to democratize high-quality STEM problem-solving. With configurable reasoning effort, strong coding and math skills, developer-friendly features, and improved latency, it’s a versatile choice for applications needing technical rigor without heavy computational expense.

Perfect when you need advanced reasoning capabilities with fast, reliable, and economical performance.

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Get started with an API-friendly relay

Send your first request to verified LLMs with a single code snippet.

import requests
import json

response = requests.post(
    url="https://1rpc.ai/v1/chat/completions",
    headers={
        "Authorization": "Bearer <1RPC_AI_API_KEY>",
        "Content-type": "application/json",
    },
    data=json.dumps ({
        "model": "o3-mini",
        "messages": [
            {
                "role": "user",
                "content": "What is the meaning of life?"
            }
        ]
    })
)

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import requests
import json

response = requests.post(
    url="https://1rpc.ai/v1/chat/completions",
    headers={
        "Authorization": "Bearer <1RPC_AI_API_KEY>",
        "Content-type": "application/json",
    },
    data=json.dumps ({
        "model": "o3-mini",
        "messages": [
            {
                "role": "user",
                "content": "What is the meaning of life?"
            }
        ]
    })
)

Copy and go

Copied!

Pricing

Pricing

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Adjust input and output size to estimate token usage and costs.

Token Calculator for o3-mini

Input (100)

100

Output (1000 )

1000

$0.0045

Total cost per million tokens

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