OpenAI o1 vs o3-mini: Flagship vs Budget Reasoning Model Comparison

TLDR

Choose o1 if you need: Absolute best performance on general knowledge (MMLU) and graduate-level reasoning (GPQA), regardless of cost.

Choose o3-mini if you need: 14x lower cost, larger context window (200K vs 128K), superior AIME performance (87.3% vs 79.2%), flexible reasoning levels, and function calling support.

Budget: o3-mini ($1.10/$4.40 per million tokens) is 14x cheaper than o1 ($15/$60 per million tokens).

Performance: o3-mini outperforms o1 on mathematics (AIME) and coding. o1 has an edge in general knowledge (MMLU) and graduate-level reasoning (GPQA).

Recommendation: For most use cases, o3-mini offers better value. It delivers 85-90% of o3's capability (which surpasses o1) at a fraction of o1's cost.

Overview

OpenAI released o1 on December 5, 2024, as their flagship reasoning model designed to solve complex problems in math, science, and coding through chain-of-thought reasoning.

Just under two months later, on January 31, 2025, OpenAI released o3-mini as their most cost-efficient reasoning model. Surprisingly, o3-mini doesn't just undercut o1 on price. It actually outperforms o1 on several key benchmarks while costing 14x less.

This comparison reveals an interesting evolution: OpenAI's newer budget model represents a significant upgrade over their previous flagship, making o1 a harder sell for most use cases.

Basics: Model Specifications

o3-mini offers more flexibility with larger context windows, higher output limits, three reasoning levels, and function calling support.

Pricing: Cost Comparison

For a typical reasoning task using 50,000 input tokens and generating 10,000 output tokens:

• o1: $1.35 per request
• o3-mini: $0.099 per request

The cost difference is dramatic. o3-mini makes advanced reasoning accessible to developers who previously couldn't afford o1's premium pricing.

Performance: Benchmark Comparison

Mathematical Reasoning

This is remarkable: o3-mini outperforms o1 on the American Invitational Mathematics Examination by over 7 percentage points. The budget model is objectively better at competition-level mathematics.

General Knowledge

o1 maintains an advantage in general knowledge and graduate-level reasoning, though o3-mini's exact scores aren't publicly available.

Coding Performance

o3-mini achieves the highest Codeforces rating of any OpenAI model and sets a new standard on SWE-Bench, making it the best coding reasoning model from OpenAI.

o3-mini Reasoning Levels: Unique Advantage

o3-mini's three reasoning effort levels give you cost-performance control that o1 doesn't offer:

You can optimize for speed when you need quick answers, or dial up reasoning effort for maximum accuracy on hard problems. o1 only offers a single (expensive) reasoning level.

Context & Output: o3-mini Wins

o3-mini's larger context window handles longer documents and more complex multi-turn conversations. The 100K max output is particularly valuable for generating long-form content or comprehensive code.

Function Calling: o3-mini Only

o3-mini is OpenAI's first reasoning model with official function calling support. This enables:

• Tool use: Call external APIs mid-reasoning
• Structured outputs: Generate JSON, XML, or other formats reliably
• Agentic workflows: Build AI agents that reason and act
• Multi-step automation: Chain reasoning with real-world actions

o1 doesn't support function calling, limiting its use in agentic and tool-based workflows.

When to Use Each Model

Use o1 when you need:

• Absolute best general knowledge: Top MMLU and GPQA scores
• Simpler API access: Available at Tier 1 ($5+ spend) vs Tier 3 ($100+)
• Maximum reasoning on all tasks: Single high-effort reasoning level
• Established track record: Launched 2 months earlier with more real-world testing

Use o3-mini when you need:

• Cost efficiency: 14x cheaper for high-volume applications
• Superior math performance: Highest AIME scores (87.3% vs 79.2%)
• Best coding performance: Top Codeforces and SWE-Bench results
• Flexible reasoning: Three effort levels to optimize cost vs accuracy
• Larger context: 200K vs 128K token window
• Function calling: Build agentic workflows with tool use
• Long outputs: Up to 100K tokens vs 32K

For most developers, o3-mini is the clear choice. It delivers better mathematical and coding performance at 1/14th the cost, with more flexibility and features.

The o3 Context

o3-mini delivers 85-90% of the full o3 model's capability at just 11% of the cost. While o3 itself isn't widely available yet, early benchmarks suggest o3 significantly outperforms o1.

This means o3-mini effectively represents:

• Better than o1 on math and coding
• Cheaper than o1 by 14x
• More flexible than o1 with reasoning levels and function calling
• Based on a stronger foundation (o3) than o1

Unless you specifically need o1's general knowledge edge, o3-mini is objectively the better reasoning model.

API Access Requirements

o3-mini requires higher API tier access ($100+ spend vs $5+), which may be a barrier for new developers. However, both models are available to ChatGPT Plus and Team subscribers.

Orchestrate Multiple Reasoning Models with Miniloop

The choice between o1 and o3-mini doesn't have to be binary. Different tasks within a workflow may benefit from different reasoning approaches.

With Miniloop, you can build AI workflows that dynamically select between o1 and o3-mini based on task requirements. Use o3-mini's high reasoning level for complex math, switch to low level for simple validation, or route general knowledge queries to o1.

Miniloop lets you:

• Mix different reasoning models in a single workflow
• Use o3-mini's reasoning levels strategically (low for speed, high for accuracy)
• Route math and coding to o3-mini, general knowledge to o1
• A/B test reasoning models to optimize performance
• Control costs by using o3-mini's cheaper tiers when possible

Stop overpaying for reasoning you don't need. Start building cost-optimized multi-model reasoning workflows with Miniloop.

Get Started with Miniloop →

Sources

• Introducing OpenAI o3 and o4-mini
• o3-mini Model Specs - Galaxy.ai
• OpenAI Pricing
• OpenAI o1 - Wikipedia
• o3-mini Performance Analysis