LLMs

o4-mini API

o4-mini is a compact, high-efficiency language model optimized for fast, low-cost performance across reasoning, math, coding, and visual understanding tasks. Despite its smaller size, it delivers strong result, making it well-suited for lightweight deployments that demand intelligent task execution. o4-mini is ideal for developers building responsive AI systems, cost-aware applications, and tool-augmented workflows requiring reliable analytical capabilities.

1RPC.ai1RPC.ai
Reasoning
Speed
$1.10/$4.40
Input/Output
200,000Context Window

o4‑mini

o4‑mini is a compact, high-efficiency model in OpenAI’s "o-series," launched on April 16, 2025. It is designed for fast, low-cost reasoning and supports both text and image inputs.

Built to provide strong performance in mathematics, coding, and visual tasks, o4‑mini delivers a large 200,000‑token context window and up to 100,000 output tokens. It offers advanced reasoning at approximately one-tenth the cost of the o3 model, making it an ideal choice for high-volume and latency-sensitive applications

What it’s optimized for

o4‑mini excels in efficiency-focused reasoning workflows:

  • Fast analytical reasoning in STEM domains

  • Multimodal input handling, including image and diagram interpretation

  • Coding support with tool use (e.g., Python execution, browsing, image analysis)

  • On‑device and high‑throughput applications requiring low latency and cost

Typical use cases

o4‑mini is particularly effective in:

  • Solving math problems (e.g., American Invitational Math Exam performance: 99.5% pass @1 with Python tools)

  • Interpreting charts, whiteboard sketches, visual diagrams

  • Generating or reviewing code in real-time

  • Powering chatbots, tutoring systems, and automation pipelines

Key characteristics

  • Multimodal reasoning across text and images (e.g., visual math, whiteboard inputs)

  • Comparable benchmark performance to o3 and significantly better than o3‑mini across reasoning tests

  • Substantial cost savings: ~$1.10 per million input tokens and $4.40 per million output tokens, compared to o3’s ~$10/$40

  • Large context and output capacity: 200K input tokens, 100K output tokens

  • Configurable inference effort: “mini-high” provides improved reasoning quality at the expense of speed, without changing the underlying model

Model architecture

o4‑mini is part of OpenAI’s fourth-generation “o-series.” Released alongside o3, it uses transformer architecture fine-tuned with reinforcement learning to think before responding. It integrates multimodal input handling and support for tool chains (Python, browsing, image tools) directly within the Chat Completions and Responses APIs.

Why choose 1RPC.ai for o4-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

o4‑mini is a streamlined reasoning model designed for speed, scale, and cost efficiency. Its built-in vision capabilities, multimodal support, configurable reasoning depth, and strong performance in STEM and coding benchmarks make it an effective choice for high-throughput, structured reasoning tasks. It offers a robust alternative to larger models when performance efficiency is required.

Like this article? Share it.

Implement

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://api.1rpc.ai/v1/chat/completions",
    headers={
        "Authorization": "Bearer <1RPC_AI_API_KEY>",
        "Content-type": "application/json",
    },
    data=json.dumps({
        "model": "o4-mini",
        "messages": [
            {
                "role": "user",
                "content": "What is the meaning of life?"
            }
        ]
    })
)
print(response.json())
Pricing

Estimate Usage Across Any AI Model

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

o4-mini Token Costs Calculator

≈ 7,500 words
≈ 75,000 words
$0.4510Total cost per million tokens
Learn about Pricing