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:- Explicit Thinking - Show their thought process
- Multi-Step Analysis - Break problems into steps
- Self-Correction - Refine answers progressively
- Higher Token Usage - Require more tokens (2000+ minimum)
- 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
A reasoning model spends tokens thinking before it answers, so it needs a highermax_reply_tokens
than a standard model — each one below declares its own minimum. Credits are charged per step.
OpenAI
GPT-6 Astra
39 credits • OpenAI’s most capable model, with state-of-the-art coding, computer use and reasoning.
- 1.05M context window
- Needs at least 3000 completion tokens
- Speed: Medium • Cost: High
- Vision: images supported
- Model id:
gpt-6-astra
GPT-6.1 Sol
8 credits • Near-Astra performance for complex work at a lower cost.
- 1.05M context window
- Needs at least 3000 completion tokens
- Speed: Medium • Cost: Medium
- Vision: images supported
- Model id:
gpt-6.1-sol
GPT-6 Sol
8 credits • GPT-6 reasoning at half the cost of GPT-5.6 Sol, for coding and complex professional work.
- 1.05M context window
- Needs at least 3000 completion tokens
- Speed: Medium • Cost: Medium
- Vision: images supported
- Model id:
gpt-6-sol
GPT-6 Luna
1 credit • The fastest, most affordable GPT-6 model, for high-volume tasks with a clear goal.
- 1.05M context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Low
- Vision: images supported
- Model id:
gpt-6-luna
GPT-5.6 Sol
16 credits • Previous-generation frontier model, built for complex professional work requiring deep reasoning.
- 1.05M context window
- Needs at least 3000 completion tokens
- Speed: Medium • Cost: High
- Vision: images supported
- Model id:
gpt-5.6-sol
GPT-5.6 Terra
8 credits • Previous-generation balanced tier offering strong reasoning and multimodal input at moderate cost.
- 1.05M context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Medium
- Vision: images supported
- Model id:
gpt-5.6-terra
GPT-5.6 Luna
1 credit • Previous-generation cost-efficient tier, designed for high-volume, cost-sensitive workloads.
- 1.05M context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Low
- Vision: images supported
- Model id:
gpt-5.6-luna
GPT-5.5
20 credits • Previous-generation frontier GPT model with strong reasoning and a 1M+ context window.
- 1.05M context window
- Needs at least 3000 completion tokens
- Speed: Medium • Cost: High
- Vision: images supported
- Model id:
gpt-5.5
GPT-5.4
10 credits • Previous-generation flagship GPT model with strong reasoning, creativity, and contextual understanding.
- 1M context window
- Needs at least 3000 completion tokens
- Speed: Medium • Cost: High
- Vision: images supported
- Model id:
gpt-5.4
GPT-5.2
8 credits • The model for coding and agentic tasks across industries.
- 400K context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: High
- Vision: images supported
- Model id:
gpt-5.2
GPT-5
6 credits • The flagship GPT-5 model offering state-of-the-art performance in reasoning, creativity, and contextual understanding for the most demanding applications.
- 200K context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: High
- Vision: images supported
- Model id:
gpt-5
GPT-5.4 Mini
3 credits • The mid-size GPT-5.4 tier: strong reasoning with a 400K context at a fraction of the flagship cost.
- 400K context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Medium
- Vision: images supported
- Model id:
gpt-5.4-mini
GPT-5 Mini
2 credits • A faster and more affordable GPT-5 variant optimized for everyday use while maintaining strong reasoning and contextual understanding.
- 200K context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Medium
- Vision: images supported
- Model id:
gpt-5-mini
GPT-5 Nano
1 credit • Ultra-lightweight GPT-5 optimized for speed and scale. Perfect for simple tasks, prototyping, and high-volume applications.
- 128K context window
- Needs at least 2000 completion tokens
- Speed: Very_fast • Cost: Low
- Vision: images supported
- Model id:
gpt-5-nano
Gemini 3.7 Flash
3 credits • The newest Gemini Flash model, with a 1M-token context window and native multimodal input.
- 1.05M context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Medium
- Vision: images supported
- Model id:
gemini-3.7-flash
Gemini 3.6 Flash
3 credits • Balances speed with intelligence for strong performance on agentic and multimodal tasks.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Medium
- Vision: images supported
- Model id:
gemini-3.6-flash
Gemini 3.5 Flash
6 credits • Most intelligent Gemini model for sustained frontier performance on agentic and coding tasks.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Medium
- Vision: images supported
- Model id:
gemini-3.5-flash
Gemini 3.5 Flash Lite
2 credits • The fastest, most cost-effective Gemini 3.5 model for high-throughput execution.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Very_fast • Cost: Very_low
- Vision: images supported
- Model id:
gemini-3.5-flash-lite
Gemini 3.1 Pro
8 credits • Reasoning-first Gemini model for complex agentic workflows and coding, with adaptive thinking.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: High
- Vision: images supported
- Model id:
gemini-3.1-pro-preview
Gemini 2.5 Flash
2 credits • A fast and capable model in the Gemini 2.5 series, balancing speed and reasoning performance for production use.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Medium
- Vision: images supported
- Model id:
gemini-2.5-flash
Gemini 2.5 Flash Lite
1 credit • A lightweight, cost-efficient variant of Gemini 2.5 Flash, optimized for low latency and basic tasks.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Very_fast • Cost: Very_low
- Vision: images supported
- Model id:
gemini-2.5-flash-lite
Anthropic
Claude Fable 5.1
35 credits • Anthropic’s most capable model, with cheaper cache reads than Fable 5 for long agentic work.
- 1M context window
- Needs at least 3000 completion tokens
- Speed: Slow • Cost: High
- Vision: images supported
- Model id:
claude-fable-5-1
Claude Opus 5.5
15 credits • Anthropic’s recommended model for most work: long-running agentic coding and knowledge work, near Fable 5.1 at a lower cost.
- 1M context window
- Needs at least 3000 completion tokens
- Speed: Medium • Cost: High
- Vision: images supported
- Model id:
claude-opus-5-5
Claude Fable 5
39 credits • Anthropic’s most capable model, for the most demanding reasoning and long-running agentic work.
- 1M context window
- Needs at least 3000 completion tokens
- Speed: Slow • Cost: High
- Vision: images supported
- Model id:
claude-fable-5
Claude Opus 5
20 credits • Previous-generation Opus model for complex agentic coding and enterprise work, with a 1M-token context window.
- 1M context window
- Needs at least 3000 completion tokens
- Speed: Medium • Cost: High
- Vision: images supported
- Model id:
claude-opus-5
Claude Opus 4.8
20 credits • The most capable Claude model, built for complex agentic coding and enterprise work.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: High
- Vision: images supported
- Model id:
claude-opus-4-8
Claude Sonnet 5.5
8 credits • The best combination of speed and intelligence in the current Claude lineup.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Medium
- Vision: images supported
- Model id:
claude-sonnet-5-5
Claude Sonnet 5
8 credits • The best combination of speed and intelligence, with near-Opus quality on coding and agentic work.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Medium
- Vision: images supported
- Model id:
claude-sonnet-5
Claude Opus 4.7
20 credits • Highly autonomous Claude Opus model, strong on long-horizon agentic work, vision, and memory.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: High
- Vision: images supported
- Model id:
claude-opus-4-7
Claude Opus 4.6
20 credits • Claude Opus model with superior reasoning, creativity, tool use, and contextual understanding.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: High
- Vision: images supported
- Model id:
claude-opus-4-6
Claude Sonnet 4.6
12 credits • Fast Claude Sonnet model with strong reasoning, creativity, tool use, and contextual understanding.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Medium
- Vision: images supported
- Model id:
claude-sonnet-4-6
xAI
Grok 4.7
9 credits • xAI’s most capable model for coding and knowledge work, with a 500K context window.
- 500K context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Medium
- Vision: images supported
- Model id:
grok-4.7
Grok 4.6
9 credits • Previous-generation Grok model, with a 500K context window and strong multimodal reasoning.
- 500K context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Medium
- Vision: images supported
- Model id:
grok-4.6
Grok 4.5
8 credits • The flagship Grok model, with native video input and strong multimodal reasoning.
- 500K context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Medium
- Vision: images supported
- Model id:
grok-4.5
Grok 4.3
5 credits • A versatile 1M-context model offering strong language and reasoning capabilities at low cost.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Low
- Vision: images supported
- Model id:
grok-4.3
Grok 4.20 Reasoning
5 credits • Grok 4.20 in reasoning mode, with enhanced analytical and problem-solving capabilities.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Low
- Vision: images supported
- Model id:
grok-4.20-0309-reasoning
Zhipu AI
GLM-5.3
6 credits • Zhipu’s flagship for complex software engineering and long-horizon agent work, with a 1M-token context window.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Low
- Model id:
glm-5.3
GLM-5.3 Flash
1 credit • The fast, low-cost GLM-5.3 tier, keeping the 1M-token context window.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Low
- Model id:
glm-5.3-flash
GLM-5.2
6 credits • The previous GLM flagship, with a 1M-token context window and strong long-horizon performance.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Low
- Model id:
glm-5.2
GLM-4.7
3 credits • Newer GLM-4 generation model with adaptive reasoning for complex agentic and coding tasks.
- 200K context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Low
- Model id:
glm-4.7
GLM-5.1
6 credits • Zhipu’s frontier GLM-5 model, a large MoE for the most demanding reasoning and agentic work.
- 200K context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Low
- Model id:
glm-5.1
MiniMax
MiniMax M2.7 Highspeed
3 credits • The accelerated M2.7 tier — roughly 100 tokens/sec against the standard 60.
- 205K context window
- Needs at least 2000 completion tokens
- Speed: Very fast • Cost: Low
- Model id:
MiniMax-M2.7-highspeed
MiniMax M2.5 Highspeed
3 credits • The accelerated M2.5 tier — roughly 100 tokens/sec against the standard 60.
- 205K context window
- Needs at least 2000 completion tokens
- Speed: Very fast • Cost: Low
- Model id:
MiniMax-M2.5-highspeed
MiniMax M3
2 credits • MiniMax’s flagship model with a 1M-token context window and native multimodal (image) input.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Low
- Vision: images supported
- Model id:
MiniMax-M3
MiniMax M2.7
2 credits • Agentic MiniMax M2 model tuned for coding and reasoning, with a 205K context window.
- 205K context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Low
- Model id:
MiniMax-M2.7
MiniMax M2.5
2 credits • Cost-efficient MiniMax M2 tier for general-purpose tasks, with a 205K context window.
- 205K context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Very_low
- Model id:
MiniMax-M2.5
DeepSeek
DeepSeek V4 Flash
2 credits • Fast, low-cost general-purpose model with a 1M context window. Good for everyday conversations and high-volume tasks.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Low
- Model id:
deepseek-v4-flash
DeepSeek V4 Flash Vision
2 credits • Experimental vision variant of V4 Flash. Same 1M context and pricing; images are billed as input tokens.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: Low
- Vision: images supported
- Model id:
deepseek-v4-flash-vision-exp
DeepSeek V4 Pro
5 credits • Higher-performance tier for complex reasoning, with enhanced logical and analytical capabilities.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Low
- Model id:
deepseek-v4-pro
Moonshot AI
Kimi K3
12 credits • Moonshot AI’s flagship multimodal reasoning model with a one-million-token context window.
- 1M context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: High
- Vision: images supported
- Model id:
kimi-k3
Kimi K2.7 Code
5 credits • A reasoning-first Kimi model optimized for agentic software engineering and complex coding work.
- 256K context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Medium
- Model id:
kimi-k2.7-code
Kimi K2.7 Code Highspeed
9 credits • The high-throughput Kimi K2.7 Code variant for latency-sensitive coding and agent workflows.
- 256K context window
- Needs at least 2000 completion tokens
- Speed: Fast • Cost: High
- Model id:
kimi-k2.7-code-highspeed
Kimi K2.6
4 credits • A multimodal Kimi model for general reasoning, tool use, and long-context tasks.
- 256K context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Medium
- Vision: images supported
- Model id:
kimi-k2.6
Fireworks AI
DeepSeek R1
25 credits • Specialized reasoning model. Enhanced analytical capabilities.
- 64K context window
- Needs at least 2000 completion tokens
- Speed: Medium • Cost: Low
- Model id:
deepseek-r1
Reasoning Model Comparison
When to Use Reasoning Models
Perfect For
Mathematical Problems
Mathematical Problems
Solving complex math, physics, or engineering problems that require step-by-step work.
Code Debugging
Code Debugging
Analyzing code to find bugs, understand logic, and suggest improvements.
Strategic Planning
Strategic Planning
Business analysis, market research, competitive analysis.Best models: Claude Opus 5.5, GPT-6.1 Sol
Scientific Analysis
Scientific Analysis
Research paper analysis, experimental design, data interpretation.Best models: GPT-6 Astra, Gemini 3.8 Flash
Logic Puzzles
Logic Puzzles
Solving riddles, logic games, complex reasoning challenges.Best models: GPT-6 Luna, DeepSeek V4 Pro (budget option)
Not Ideal For
- 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
GPT-5.4 - Deep Analysis
DeepSeek V4 Pro - Budget Reasoning
Gemini 3.5 Flash Lite - 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
Troubleshooting
Responses too slow
Responses too slow
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
High costs
High costs
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
Not showing thinking process
Not showing thinking process
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
Token limit errors
Token limit errors
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