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Overview

Reasoning models use explicit step-by-step thinking to solve complex problems. Unlike standard models that generate immediate responses, reasoning models “think” through problems methodically, making them ideal for analytical tasks.

What Are Reasoning Models?

Reasoning models employ a different approach:
  1. Explicit Thinking - Show their thought process
  2. Multi-Step Analysis - Break problems into steps
  3. Self-Correction - Refine answers progressively
  4. Higher Token Usage - Require more tokens (2000+ minimum)
  5. Slower Response - Take longer but more accurate
Think of reasoning models as “showing their work” like in math class - they explain how they reached the answer, not just what the answer is.

Available Reasoning Models

OpenAI O-Series

O1

6 credits • Deepest reasoning
  • 200K context window
  • 3000 min completion tokens
  • Speed: Slow (10-20s)
  • Best for: Complex problems, deep analysis

O1 Mini

3 credits • Faster reasoning
  • 128K context window
  • 2000 min completion tokens
  • Speed: Medium (5-10s)
  • Best for: Balanced reasoning tasks

O3 Mini

3 credits • Next-gen compact
  • 128K context window
  • 2000 min completion tokens
  • Speed: Medium (5-10s)
  • Best for: Advanced reasoning

GPT-5.1

4 credits • Enhanced reasoning
  • 200K context window
  • 2000 min completion tokens
  • Speed: Medium
  • Best for: General reasoning tasks

Anthropic Extended Thinking

Claude 3 Opus Extended Thinking

6 credits • Deep analytical reasoning
  • 200K context window
  • 2500 min completion tokens
  • Speed: Slow
  • Best for: Strategic planning, research

Google Flash Thinking

Gemini 2.0 Flash Thinking

3 credits • Fast reasoning
  • 1,000,000 token context window
  • 2000 min completion tokens
  • Speed: Medium (4-6s)
  • Best for: Analytical tasks with large context

xAI Grok Reasoning

Grok 3 Reasoning

4 credits • Enhanced analytical
  • 128K context window
  • 2000 min completion tokens
  • Speed: Medium
  • Best for: Problem-solving, analysis

DeepSeek R1

DeepSeek R1

2 credits • Most affordable reasoning
  • 64K context window
  • 2000 min completion tokens
  • Speed: Medium
  • Best for: Cost-effective reasoning

Groq Reasoning Models

DeepSeek Llama 70B (Groq)

2 credits • Fast reasoning on LPU
  • 64K context window
  • 2000 min completion tokens
  • Speed: Fast (ultra-fast inference)
  • Best for: Efficient reasoning at speed

Qwen QWQ 32B (Groq)

2 credits • Multilingual reasoning
  • 32K context window
  • 2000 min completion tokens
  • Speed: Fast
  • Best for: Multilingual analytical tasks

Reasoning Model Comparison

When to Use Reasoning Models

Perfect For

Solving complex math, physics, or engineering problems that require step-by-step work.
Analyzing code to find bugs, understand logic, and suggest improvements.
Business analysis, market research, competitive analysis.Best models: O1, Claude 3 Opus Extended
Research paper analysis, experimental design, data interpretation.Best models: O1, Gemini 2.0 Flash Thinking
Solving riddles, logic games, complex reasoning challenges.Best models: O1 Mini, DeepSeek R1 (budget option)

Not Ideal For

Reasoning models are overkill for these tasks. Use standard models instead:
  • Simple conversations
  • Quick factual questions
  • Creative writing (use GPT-5 or Claude Opus instead)
  • High-volume simple queries (too slow and expensive)
  • Real-time chat applications (too slow)

Usage Examples

OpenAI O1 - Deep Analysis

DeepSeek R1 - Budget Reasoning

Gemini 2.0 Flash Thinking - Large Context

Override Reasoning Mode

All reasoning models support these modes:

Best Practices

Set Appropriate Token Limits

Handle Longer Wait Times

Cost Optimization

Cache Common Analyses

Performance Comparison

Speed vs Accuracy Tradeoff

Best Value: DeepSeek R1 (2 credits) or Gemini 2.0 Flash Thinking (3 credits) offer the best balance of cost and capability.

Troubleshooting

Expected: Reasoning models take longerSolutions:
  • Use O1 Mini instead of O1
  • Use DeepSeek R1 for faster reasoning
  • Try Groq’s reasoning models for ultra-fast
  • Add progress indicators for users
Cause: Reasoning models use more tokens and creditsSolutions:
  • Use only for complex tasks
  • Try DeepSeek R1 (2 credits)
  • Cache results for common queries
  • Use standard models for simple tasks
Note: Some models show thinking, others don’tDetails:
  • O1 series: Shows detailed thinking
  • DeepSeek R1: Shows reasoning steps
  • Claude Extended: Implicit thinking
  • Gemini Thinking: Shows analysis process
Cause: Insufficient max_reply_tokensSolutions:
  • Set minimum 2000 tokens
  • Use 3000+ for O1
  • Use 2500+ for Claude Extended
  • Check model-specific requirements

Real-World Use Cases

Code Review Assistant

Business Strategy Advisor

Math Tutor

Next Steps

Model Comparison

Compare all models

Provider Overview

See all providers

OpenAI O-Series

Learn about O1 models

DeepSeek R1

Budget reasoning option