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o3 and o4-mini API — OpenAI reasoning models via one key

How to call OpenAI's o3 and o4-mini reasoning models through InferAll's OpenAI-compatible endpoint. Same SDK, same key — no separate API access needed.

InferAll Team

3 min read
OpenAIo3o4-minireasoning modelsLLM APIAI gatewaydeveloper tools

OpenAI's reasoning model family — o1, o3, o3-mini, o4-mini — is now available through InferAll's OpenAI-compatible endpoint. Same SDK you already use, same ifu_... key.

Model Input Output Best for
o3 $10.00/M $40.00/M Hardest reasoning, math proofs, complex code
o4-mini $1.10/M $4.40/M Reasoning at lower cost — most tasks
o3-mini $1.10/M $4.40/M Previous generation (same tier)
o1 $15.00/M $60.00/M Deliberate reasoning, slower

All at OpenAI's published list rates.

Quick start

Using a new key? A no-card trial key routes to the free NIM models only, so the paid model in these snippets returns a 402 until you add a card. To get a working first call right now, keep everything below and swap the model to meta/llama-3.1-8b-instruct.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.inferall.ai/v1",
    api_key="ifu_your_key_here",  # get one at inferall.ai/keys
)

# o3 — for hard problems
response = client.chat.completions.create(
    model="openai/o3",
    messages=[
        {"role": "user", "content": "Prove that there are infinitely many prime numbers."}
    ],
)

# o4-mini — reasoning at lower cost
response = client.chat.completions.create(
    model="openai/o4-mini",
    messages=[
        {"role": "user", "content": "Debug this Python code: ..."}
    ],
)

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

The only difference from calling OpenAI directly: base_url="https://api.inferall.ai/v1". Your existing code, streaming, and tool use all work unchanged.

TypeScript

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.inferall.ai/v1",
  apiKey: process.env.INFERALL_API_KEY,
});

const response = await client.chat.completions.create({
  model: "openai/o4-mini",
  messages: [
    { role: "user", content: "Write a SQL query to find the top 10 customers by revenue in the last 90 days." }
  ],
});

console.log(response.choices[0].message.content);

When to use each model

o4-mini is the default choice for most tasks that need reasoning. It's 9× cheaper than o3 and handles most real-world problems — debugging, code generation, complex queries, structured data extraction. Most teams find o3 is only necessary for research-grade proofs, very hard math, or safety-critical reasoning where maximum accuracy matters.

o3 is for the problems where o4-mini genuinely struggles — multi-step deduction, long-horizon planning, formal proofs. If you're not sure, start with o4-mini and only step up when you see it fail.

o1 is the previous generation of deliberate reasoner. o3 is significantly more capable at similar or lower cost — there's no strong reason to use o1 in new projects.

Same key for everything else

The same ifu_... key that calls o3 also routes to:

  • GPT-4.1 / GPT-4.1-mini / GPT-4.1-nano
  • Claude Opus 4 / Sonnet 4
  • Gemini 2.5 Flash / Pro
  • 40+ NVIDIA NIM open models at our open-model rate

Switch between providers by changing one string. Useful when you want to compare o4-mini vs Claude Opus 4 on a hard task, or fall back to GPT-4.1-mini for cheaper follow-up calls after o3 generates the plan.

Note on reasoning token behavior

OpenAI's o-series models think before they respond — they generate internal reasoning tokens that count toward your usage but aren't returned in the output. InferAll passes the full response through unchanged, so usage.completion_tokens includes both reasoning and output tokens as reported by OpenAI.

Sign up at inferall.ai/keys and fund a key with the $5 starter pack — usage credit you can spend on o3, o4-mini, or any other model at the provider's published rate with zero markup.

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