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o3 Mini vs GPT-4o

o3-mini for reasoning-optimized tasks at lower cost, GPT-4o for general-purpose and when reasoning is not the bottleneck.

Pricing source: live OpenRouter model catalog (`/api/v1/models`).

Model A

o3 Mini

OpenAI • text+file->text
Context Window200K
Knowledge CutoffJan 31, 2025
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Model B

GPT-4o

OpenAI • text+image+file->text
Context Window128K
Knowledge CutoffMay 13, 2024
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Editorial Verdict

o3-mini is OpenAI's reasoning specialist; GPT-4o is OpenAI's versatile general-purpose flagship.

o3-mini and GPT-4o are both OpenAI models but with different specializations. o3-mini is optimized for hard reasoning tasks; GPT-4o is a general-purpose multimodal model. For math, science, and hard reasoning, o3-mini outperforms GPT-4o. For general-purpose tasks, coding, and multimodal applications, GPT-4o is the more versatile choice.

o3 Mini
  • Significantly outperforms GPT-4o on math, science, and hard reasoning benchmarks
  • Configurable reasoning depth for task-appropriate cost and latency
  • Lower cost than GPT-4o for comparable general capability

Best for: Hard reasoning tasks, math, and competitive programming

GPT-4o
  • Multimodal capabilities across text, images, audio, and video in one model
  • Versatile general-purpose model for diverse production applications
  • Mature API ecosystem with function calling, JSON mode, and enterprise support

Best for: General-purpose production applications and multimodal workflows

Pricing sourced from OpenRouter — updates as their catalog changes.

Pricing Comparison

All values pull from OpenRouter and update as their catalog changes.

Metrico3 MiniGPT-4oWinner
Input (per 1M tokens)$1.10$2.50🏆 o3 Mini
Output (per 1M tokens)$4.40$10.00🏆 o3 Mini
Request feeN/AN/AN/A
Image feeN/AN/AN/A

Cost Estimator

Estimate monthly billing using real OpenRouter prices.

o3 Mini Total

$104.5

GPT-4o Total

$237.5
Estimated Monthly Savings: $133 with o3 Mini

Capability Signals

Scores are directional estimates from model metadata — not official benchmark results.

o3 MiniMMLU Signal (Reasoning)GPT-4o
87%
69%
o3 MiniHumanEval Signal (Coding)GPT-4o
76%
76%
o3 MiniAgentic Tooling SignalGPT-4o
84%
84%
o3 MiniMultimodal SignalGPT-4o
69%
78%

Capabilities Matrix

Feature highlights for architecture and production fit.

o3 Mini Strengths

  • Strong tool-calling and structured response support.
  • Large context window for long documents and codebases.
  • Strong reasoning profile for planning and analysis tasks.

GPT-4o Strengths

  • Supports image inputs for multimodal analysis workflows.
  • Strong tool-calling and structured response support.
  • Balanced general-purpose profile for chat, extraction, and automation tasks.

API Implementation

Quick start snippets for each provider style.

OpenAI (Python)

from openai import OpenAI

client = OpenAI()
response = client.chat.completions.create(
  model="openai/o3-mini",
  messages=[{"role": "user", "content": "Hello"}]
)

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

OpenAI (Python)

from openai import OpenAI

client = OpenAI()
response = client.chat.completions.create(
  model="openai/gpt-4o",
  messages=[{"role": "user", "content": "Hello"}]
)

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

Choose o3 Mini when...

  • You process large documents or code repositories in a single prompt.
  • You rely on function calling, tool chaining, and structured output contracts.
  • You want a balanced default for mixed chat and workflow automation workloads.

Choose GPT-4o when...

  • Your application includes visual reasoning and image understanding tasks.
  • You rely on function calling, tool chaining, and structured output contracts.
  • You want a balanced default for mixed chat and workflow automation workloads.

Frequently Asked Questions

Practical checks before selecting a production model.

Is o3-mini better than GPT-4o?

It depends on the workload. o3-mini and GPT-4o differ in pricing, context window, and capability mix — see the side-by-side table above for the breakdown.

What's the price difference between o3-mini and GPT-4o?

o3-mini: $1.10 per 1M input tokens. GPT-4o: $2.50 per 1M input tokens. Output token pricing typically runs 2-5x higher.

Which model is better for coding?

Coding preference depends on your stack and tool-calling needs. Compare the coding signal row, test with your repository tasks, and validate latency in your target region.

Which model is cheaper at scale?

Input and output token pricing can diverge by workload profile. Use the estimator with your monthly request count and token mix to get a realistic cost difference.

Are these official benchmark numbers?

Pricing is live from OpenRouter. Benchmark rows are ModelsAtlas metadata-based signals and should be treated as directional guidance, not official leaderboard scores.

Related Comparisons

Explore adjacent model matchups.

GPT-4o vs Claude 3.7 SonnetGPT-4o for multimodal breadth, Claude 3.7 for coding-heavy workflows.GPT-4o vs Claude 3 OpusClaude 3 Opus for highest reasoning quality, GPT-4o for production ecosystem and speed.GPT-4o vs Gemini 2.0 FlashGemini 2.0 Flash for cost efficiency and 1M context, GPT-4o for mature tool ecosystem.Claude 3.7 Sonnet vs Claude 3 OpusClaude 3 Opus for maximum capability on complex tasks, Claude 3.7 Sonnet for best price-to-performance in Claude family.
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