o4-mini

o4-mini

Quick answer: o4-mini is OpenAI's compact, cost-efficient reasoning model, released April 16, 2025 alongside o3. It scores 74.2% on LiveCodeBench (medium), 95.9% on AI2 Reasoning Challenge, and 74.6% on Arena Hard v2 — delivering near-o3 performance on coding and reasoning tasks at 9× lower cost. Priced at $1.10 input / $4.40 output per 1M tokens with a 200K-token context window.

At a Glance

Where o4-mini leads

• 95.9% AI2 Reasoning Challenge — top-tier multi-discipline science and reasoning
• 74.2% LiveCodeBench (medium effort) — competitive with o3-high at a fraction of the cost
• 74.6% Arena Hard v2 — strong general-purpose instruction following
• Best reasoning-per-dollar in OpenAI's o-series at $1.10/$4.40 per 1M tokens
• Multimodal vision support
• Scales well with higher effort settings for harder tasks

Where it lags

• Lower ceiling than o3 on the hardest abstract reasoning tasks (ARC-AGI, frontier math)
• 200K context window — constrained vs 1M+ long-context models
• Closed API model with no open weights
• CyberGym score of 2.5% — not suited for cybersecurity tasks

Best for: Cost-sensitive production pipelines, high-throughput coding assistance, API-integrated agents, and workflows where o3's premium is not justified by task difficulty.

What o4-mini Is

o4-mini is the small, efficient tier of OpenAI's April 2025 o-series release. Like o3, it uses internal chain-of-thought reasoning before producing a final response, with low/medium/high effort settings. The key trade-off vs o3: o4-mini's capability ceiling is lower on the hardest abstract reasoning tasks, but on the coding and science benchmarks that dominate most production agent workloads, the gap is small.

The model's 95.9% AI2 Reasoning Challenge score — a multi-discipline science benchmark covering physics, chemistry, and biology — indicates that o4-mini's reasoning capability is genuinely strong, not merely fast. Its LiveCodeBench score of 74.2% at medium effort is within 1.6 points of o3-high, meaning for most coding tasks the cost premium for o3 is rarely justified.

For teams building production AI agents, o4-mini is typically the right default in the o-series: capable enough for the majority of real-world reasoning tasks, priced for at-scale operation, and responsive enough at medium effort to meet latency requirements.

Specifications

Pricing

Reasoning tokens are billed as output tokens. Cached input receives a 75% discount. Pricing per OpenAI pricing page.

Context Window

o4-mini has a 200,000-token context window — roughly 150 pages of text in a single request, matching o3. This is sufficient for most agentic workflows but constrains whole-codebase or long-document tasks where Gemini 2.5 Pro's 1M context is preferable.

Public Benchmark Scores

Scores from Benchgen evaluations or attributed third-party sources. Figures depend on effort setting and harness — see the source for methodology.

o4-mini vs Alternatives

o4-mini's strongest case: it matches o3-high on LiveCodeBench at 9× lower cost. vs Gemini 2.5 Pro, o4-mini is cheaper and slightly stronger on coding tasks, but Gemini offers a 5× larger context window.

How o4-mini Performs on Real Agent Tasks

o4-mini's 95.9% AI2 Reasoning Challenge and 74.2% LiveCodeBench position it as the default reasoning model for production workloads requiring science and coding capability. Its CyberGym score of 2.5% indicates it is not suited for cybersecurity tasks — for those, GPT-5.6 Sol is the more appropriate choice.

For most teams, o4-mini at medium effort is the right starting point. Upgrade to high effort when evaluation data shows a consistent accuracy gap; switch to o3 only when task difficulty consistently pushes past o4-mini-high's ceiling.

Use o4-mini via API

from openai import OpenAI

client = OpenAI(api_key="YOUR_API_KEY")

response = client.chat.completions.create(
    model="o4-mini",
    messages=[{"role": "user", "content": "Debug this Python function and explain the fix..."}],
    reasoning_effort="medium",
)
print(response.choices[0].message.content)

Related Models & Benchmarks

• Compare: o3 · GPT-5.6 Luna · Gemini 2.5 Pro · DeepSeek R1
• Benchmarks: LiveCodeBench · AI2 Reasoning Challenge · Arena Hard v2 · Humanity's Last Exam

Frequently Asked Questions

Specs and scores sourced from OpenAI's official o4-mini announcement (April 16, 2025) and Benchgen evaluations; third-party benchmark scores attributed inline. Pricing cited to the OpenAI pricing page. Last updated 2026-07-23.