OpenAI o3-mini vs DeepSeek R1: Budget Reasoning Model Showdown

TLDR

Choose o3-mini if you need: Best-in-class coding performance, faster response times, higher AIME scores, and function calling support.

Choose DeepSeek R1 if you need: 2x lower cost, open source flexibility, self-hosting capabilities, and strong mathematics performance.

Budget: DeepSeek R1 ($0.55/$2.19 per million tokens) is 2x cheaper than o3-mini ($1.10/$4.40 per million tokens).

Performance: o3-mini outperforms DeepSeek R1 on most benchmarks, particularly coding and mathematics. DeepSeek R1 offers competitive performance at half the price.

Overview

OpenAI released o3-mini on January 31, 2025, as their most cost-efficient reasoning model. o3-mini delivers 85-90% of the full o3 model's capabilities at just 11% of the cost, making advanced reasoning accessible to more developers.

DeepSeek R1, released on January 20, 2025, is an open-source reasoning model that challenges proprietary models with comparable performance at dramatically lower costs. Built for just $5.58 million, DeepSeek R1 is fully open source under the MIT license.

Both models target developers who need reasoning capabilities without the premium cost of flagship models like o1 or o3.

Basics: Model Specifications

Pricing: Cost Comparison

For a typical reasoning task using 20,000 input tokens and generating 5,000 output tokens:

• o3-mini: $0.044 per request
• DeepSeek R1: $0.022 per request

While both models are dramatically cheaper than flagship models (o1 costs $15/$60), DeepSeek R1 maintains a 2x cost advantage over o3-mini.

Performance: Benchmark Comparison

Mathematical Reasoning

o3-mini achieves higher scores on the American Invitational Mathematics Examination, outperforming DeepSeek R1 by over 7 percentage points. However, DeepSeek R1 excels on MATH-500 with an impressive 97.3% score.

Coding Performance

o3-mini dominates in competitive programming, achieving the same Codeforces rating as the full o1 model. DeepSeek R1's 1,820 rating is still impressive, surpassing most non-reasoning models.

General Knowledge

o3-mini outperforms DeepSeek R1 in logical reasoning and graduate-level question answering.

Speed & Response Time

o3-mini:

• Notably faster response times
• Optimized for low-latency applications
• Responds in a fraction of the time taken by DeepSeek R1
• Three reasoning levels (low/medium/high) to balance speed and accuracy

DeepSeek R1:

• Slower due to visible chain-of-thought reasoning
• More transparent reasoning process
• Can be optimized when self-hosted

For time-sensitive applications, o3-mini's speed advantage is significant.

Accessibility & Deployment

o3-mini:

• Available via OpenAI API (Tier 3+ required, $100+ spend)
• ChatGPT Plus and Team subscribers
• Proprietary, closed source
• First reasoning model with official function calling support

DeepSeek R1:

• Available via DeepSeek API
• Available through Fireworks AI, Together AI, and other providers
• Can be self-hosted on your own infrastructure
• Open source under MIT license (commercial use allowed)
• Can be fine-tuned for specific use cases

When to Use Each Model

Use o3-mini when you need:

• Top coding performance: Highest Codeforces rating and SWE-Bench scores
• Faster responses: Lower latency for time-sensitive applications
• Function calling: Native support for tool use and API integrations
• Flexible compute: Three reasoning levels to optimize cost vs. performance
• Best AIME performance: Superior mathematical competition results

Use DeepSeek R1 when you need:

• Lower costs: 2x cheaper than o3-mini for high-volume applications
• Open source flexibility: Self-hosting, fine-tuning, or customization
• Transparency: MIT license without vendor lock-in
• MATH-500 excellence: Superior performance on specific math benchmarks
• Commercial freedom: No usage restrictions or licensing fees

o3-mini Reasoning Levels

One unique advantage of o3-mini is its three reasoning effort levels:

This flexibility lets you optimize for speed and cost based on task complexity, something DeepSeek R1 doesn't offer.

Orchestrate Multiple AI Models with Miniloop

The choice between o3-mini and DeepSeek R1 doesn't have to be binary. o3-mini excels at coding while DeepSeek R1 offers unbeatable cost efficiency for mathematics.

With Miniloop, you can build AI workflows that use both models for different steps. Route coding tasks to o3-mini for superior performance, while using DeepSeek R1 for mathematical reasoning at 2x lower cost.

Miniloop lets you:

• Use any AI model for each workflow step
• Switch between reasoning models based on task type
• Combine o3-mini's coding prowess with DeepSeek R1's cost efficiency
• Test different reasoning levels and models to optimize performance
• Build reliable, repeatable AI pipelines with explicit orchestration

Stop choosing between cost and performance. Start building multi-model reasoning workflows with Miniloop.

Get Started with Miniloop →

Sources

• Introducing OpenAI o3 and o4-mini
• o3-mini Model Specs - Galaxy.ai
• OpenAI o3-mini vs DeepSeek R1 - Backblaze
• o3-mini vs DeepSeek R1 Comparison - Analytics Vidhya
• DeepSeek R1 on Hugging Face