The AI landscape has evolved dramatically with OpenAI’s latest releases. Understanding the differences between ChatGPT 4o vs o1 is crucial for businesses and developers looking to leverage cutting-edge artificial intelligence capabilities. While GPT-4o revolutionized multimodal AI interactions, the o1 series introduces a fundamental shift toward advanced reasoning and problem-solving .
If you’ve been wondering about chatgpt o1 vs 4o performance, or whether the chatgpt 4o vs o1 preview makes a difference in your workflow, this comprehensive guide breaks down the 10 major upgrades you’ll notice immediately.
The chat gpt o1 vs 4o comparison reveals that these aren’t just incremental improvements—they represent a paradigm shift in how AI models approach complex problems. From enhanced mathematical reasoning to superior coding capabilities, the o1 series was designed with one radical departure: it thinks before it responds .
Quick Comparison: ChatGPT 4o vs O1 at a Glance
Before diving deep into the upgrades, here’s a comprehensive comparison table to help you understand the key differences between chatgpt 4 vs 4o and the o1 series:
| Feature | GPT-4o | o1-preview | o1 | o1-mini |
| Release Date | May 2024 | September 2024 | September 2024 | September 2024 |
| Primary Focus | Speed & multimodal tasks | Advanced reasoning | Enhanced reasoning | Coding efficiency |
| Reasoning Approach | Direct response generation | Chain-of-thought reasoning | Large-scale RL reasoning | Fast reasoning for STEM |
| Context Window | 128,000 tokens | 128,000 tokens | 128,000 tokens | 128,000 tokens |
| Response Speed | 103 tokens/second | Slower (deliberate thinking) | Moderate | 73.9 tokens/second |
| Input Support | Text, image, audio, video | Text, image | Text, image | Text only |
| Output Support | Text, image, audio | Text | Text | Text |
| Math Performance (AIME) | 13% accuracy | 83% accuracy | 74.4% pass@1, 83.3% cons@64 | High (STEM-optimized) |
| Coding (Codeforces Elo) | 808 (11th percentile) | 1,258 (62nd percentile) | 1,673 (89th percentile) | Optimized for coding |
| Best Use Cases | Customer service, content creation, real-time chat | Complex problem-solving, research | Advanced reasoning tasks | Coding, programming |
| Pricing (Input) | $10 per 1M tokens | $15 per 1M tokens | Higher than 4o | 80% cheaper than o1-preview |
| Pricing (Output) | $10 per 1M tokens | $60 per 1M tokens | Higher than 4o | More cost-effective |
| Multimodal Capability | ✅ Full multimodal | ✅ Text + Image | ✅ Text + Image | ❌ Text only |
| Safety Score (Jailbreak) | 22/100 | 84/100 | Higher | Higher |
| Knowledge Base | Broad general knowledge | Limited compared to 4o | Enhanced | Focused on coding |
1. Revolutionary Chain-of-Thought Reasoning
The most fundamental upgrade in the chatgpt o1 vs 4o comparison is the introduction of native chain-of-thought reasoning .
How It Works
Unlike GPT-4o, which generates answers directly, o1 models spend more time thinking before providing responses. This approach mimics how human experts tackle difficult problems—analyzing different strategies, identifying mistakes, and correcting them before delivering a final answer .
GPT-4o operates on speed and fluency, generating responses at 103 tokens per second. In contrast, o1-preview uses deliberate reasoning steps, making it slower but significantly more accurate for complex tasks .
Real-World Impact
In tests conducted by OpenAI, the difference is dramatic:
- GPT-4o correctly solved only 13% of International Mathematical Olympiad (IMO) qualifying exam problems
- o1-preview successfully solved 83% of the same problems
This demonstrates superior reasoning capabilities in complex contexts, making chatgpt 4o vs o1 for coding and mathematical problem-solving a clear win for the o1 series.
The o1 models achieved this through large-scale reinforcement learning (RL), which teaches the model to reward correct reasoning and penalize mistakes .
2. Exceptional Mathematical and Scientific Problem-Solving
When evaluating chatgpt o1 pro vs 4o for STEM applications, the o1 series shows remarkable improvements .
Mathematical Excellence
On the 2024 AIME (American Invitational Mathematics Examination), the performance gap is striking:
- GPT-4o: 12% average (1.8/15 problems)
- o1 (single sample): 74% average (11.1/15 problems)
- o1 (consensus of 64 samples): 83% average (12.5/15 problems)
- o1 (1000 samples with scoring): 93% average (13.9/15 problems)
A score of 13.9 places o1 among the top 500 students nationally and above the cutoff for the USA Mathematical Olympiad .
Scientific Reasoning
On GPQA Diamond—a difficult benchmark testing expertise in chemistry, physics, and biology—o1 surpassed human PhD experts:
- GPT-4o: 50.6% accuracy
- o1-preview: 73.3% accuracy
- o1: 77.3% accuracy
This makes o1 the first model to exceed PhD-level performance on this benchmark, though this doesn’t imply it surpasses PhDs in all respects .
Subject-Specific Performance
| Subject | GPT-4o | o1 |
| Physics | 59.5% | 92.8% |
| Chemistry | 40.2% | 64.7% |
| Biology | 61.6% | 69.2% |
These results position the chat gpt o1 vs 4o comparison firmly in favor of o1 for scientific and academic applications .
3. Advanced Coding and Debugging Capabilities
For developers comparing chatgpt 4o vs o1 for coding, the o1 series represents a significant leap forward .
Competitive Programming Performance
The o1 models excel in generating and debugging complex code:
Codeforces Elo Ratings:
- GPT-4o: 808 Elo (11th percentile)
- o1-preview: 1,258 Elo (62nd percentile)
- o1: 1,673 Elo (89th percentile)
- o1-ioi (specialized model): 1,807 Elo (93rd percentile)
This means o1 performs better than 93% of human competitors in programming contests .
International Olympiad in Informatics (IOI)
OpenAI trained a specialized o1-ioi model that competed in the 2024 IOI under the same conditions as human contestants:
- Score: 213 points (49th percentile)
- With 10,000 submissions: 362.14 points (above gold medal threshold)
The model had 10 hours to solve six challenging algorithmic problems with 50 submissions allowed per problem. A test-time selection strategy based on performance added nearly 60 points compared to random submission .
Why o1-mini Excels for Developers
o1-mini is specifically designed for coding tasks:
- 80% cheaper than o1-preview
- Generates responses at 73.9 tokens per second
- Retains advanced reasoning capabilities
- Ideal for cost-effective programming problem-solving
This makes chatgpt o1 vs o4 mini comparisons less relevant, as o1-mini focuses purely on efficiency for technical tasks.
If you’re a development team looking to integrate AI-powered coding solutions, contact Ranking Mantra to explore how o1 models can accelerate your software development workflow.
4. Enhanced Safety and Responsible AI
One of the most important upgrades when comparing gpt 4 o1 models to GPT-4o is enhanced safety .
Safety Test Performance
Jailbreak Resistance:
- GPT-4o: 22 out of 100 on difficult jailbreak tests
- o1-preview: 84 out of 100
This dramatic improvement means o1 models handle attempts to bypass safety rules (jailbreaking) far more effectively .
Why Chain-of-Thought Improves Safety
The o1 series integrates OpenAI’s policies for model behavior directly into the chain of thought. This approach allows models to:
- Reason about safety principles in context
- Follow ethical guidelines more robustly
- Resist out-of-distribution safety challenges
By teaching the model to reason about safety rules rather than simply memorizing them, o1 demonstrates more consistent adherence to responsible AI principles .
Safety Evaluation Breakdown
| Metric | GPT-4o | o1-preview |
| Safe completions (standard prompts) | 99.0% | 99.5% |
| Safe completions (jailbreaks & edge cases) | 71.4% | 93.4% |
| Harassment (severe) | 84.5% | 90.0% |
| Exploitative sexual content | 48.3% | 94.9% |
| Sexual content involving minors | 70.7% | 93.1% |
| Advice about violent wrongdoing | 77.8% | 96.3% |
These improvements make o1 significantly safer for enterprise deployment .
5. Multimodal Capabilities: Where GPT-4o Still Leads
While o1 models excel at reasoning, GPT-4o maintains an advantage in multimodal processing .
GPT-4o’s Multimodal Strengths
Input Support:
- Text
- Images
- Audio
- Video
Output Support:
- Text
- Images
- Audio
GPT-4o is designed as OpenAI’s most advanced multimodal model, capable of processing and generating any combination of text, vision, and audio content .
o1 Series Multimodal Limitations
o1-preview and o1:
- Input: Text + Images
- Output: Text only
o1-mini:
- Input: Text only
- Output: Text only
When to Choose GPT-4o Over o1
For use cases requiring:
- Real-time audio processing
- Image generation
- Video understanding
- Voice interactions
- Quick multimodal responses
GPT-4o remains the superior choice .
MMMU Performance
Despite limitations, o1 with vision capabilities scored 78.2% on MMMU (Massive Multi-discipline Multimodal Understanding), becoming the first model competitive with human experts .
6. Speed vs. Depth: Response Time Trade-offs
A crucial consideration in the chatgpt o1 vs 4o reddit discussions is the speed-depth trade-off .
Response Generation Speed
| Model | Tokens per Second | Approach |
| GPT-4o | 103 | Direct generation |
| o1-mini | 73.9 | Fast reasoning |
| o1-preview | Slower | Deliberate thinking |
| o1 | Moderate | Balanced reasoning |
When Speed Matters: Choose GPT-4o
GPT-4o excels in scenarios requiring:
- Customer service chatbots
- Real-time data analysis
- Quick content generation
- Conversational interfaces
- Immediate multimodal responses
When Depth Matters: Choose o1
o1 models are designed for:
- Complex mathematical problems
- Advanced coding challenges
- Scientific research
- Multi-step reasoning tasks
- Problems requiring careful analysis
The Thinking Process Advantage
While o1 takes longer to respond, this deliberate approach dramatically improves accuracy on complex problems. The model:
- Tries different strategies
- Identifies and corrects mistakes
- Breaks down complex steps
- Refines its approach when needed
This makes the chatgpt 4o vs o1 preview choice dependent on whether your priority is speed or accuracy.
7. Context Window and Token Performance
Both 4o vs 4 chatgpt models and the o1 series share the same context window capacity .
Context Window Specifications
All Models:
- 128,000 tokens context window
- Support for very large inputs and outputs
- Ability to handle extensive conversations
- Processing of lengthy documents
Effective Context Utilization
While the context window size is identical, how models use this capacity differs:
GPT-4o:
- Optimized for maintaining conversational context
- Efficient at processing multimodal inputs within the window
- Balances speed with context retention
o1 Models:
- Use context for deeper reasoning chains
- May require more tokens for internal thought processes
- Optimize for accuracy over speed in context processing
Practical Implications
For applications involving:
- Long document analysis
- Extended conversations
- Multi-turn reasoning
- Comprehensive code reviews
Both model families handle these effectively, but o1 will provide more thorough analysis while GPT-4o delivers faster processing .
8. Pricing and Cost-Effectiveness
Cost is a critical factor when choosing between chatgpt o1 pro vs 4o for business applications .
Detailed Pricing Comparison
| Model | Input Tokens (per 1M) | Output Tokens (per 1M) | Cost Efficiency |
| GPT-4o | $10 | $10 | Excellent for general use |
| o1-preview | $15 | $60 | 6x more expensive output |
| o1 | Higher than GPT-4o | Higher than GPT-4o | Premium pricing |
| o1-mini | Lower | Lower | 80% cheaper than o1-preview |
Cost Analysis
GPT-4o costs $10 per million output tokens, while o1-preview costs $60 per million output tokens—making o1-preview 6 times more expensive .
However, o1-mini is 80% cheaper than o1-preview, making it an ideal choice for developers who need advanced reasoning for coding without the broader knowledge base .
ChatGPT Subscription Tiers
| Plan | Price | Access |
| ChatGPT Plus | $20/month | o1-preview, o1-mini, GPT-4o (limits: 30 msgs/week o1-preview, 50 msgs/week o1-mini) |
| ChatGPT Team | $25-30/month/user | Higher limits, business features |
| ChatGPT Enterprise | Custom quote | Maximum capacity, security features |
ROI Considerations
While o1 models cost more per token:
- Fewer attempts needed for complex problems
- Higher first-attempt accuracy reduces iteration costs
- Significant time savings on reasoning-heavy tasks
- Reduced need for human expert review
For businesses evaluating AI implementation costs, explore our consulting services at Ranking Mantra to optimize your AI budget.
9. Training Approach: Reinforcement Learning vs. Pre-training
The chat gpt o1 vs 4o comparison reveals fundamentally different training philosophies .
GPT-4o Training
GPT-4o follows traditional large language model training:
- Pre-training on massive datasets for fluency and general knowledge
- Focus on speed and breadth of information
- Optimized for multimodal task performance
- Trained to respond quickly across diverse domains
o1 Series Training Innovation
o1 models employ a revolutionary approach:
Large-Scale Reinforcement Learning (RL):
- Models learn to hone their chain of thought
- Refine problem-solving strategies
- Recognize and correct mistakes
- Break down complex steps into simpler ones
- Try different approaches when initial methods fail
Reinforcement Learning Benefits
This RL approach teaches o1 to:
- Reward: Correct reasoning and accurate solutions
- Penalize: Errors and incorrect approaches
- Optimize: Test-time computation for better accuracy
Performance Scaling
o1 demonstrates unique scaling characteristics:
- Performance improves consistently with more reinforcement learning (train-time compute)
- Accuracy increases with more thinking time (test-time compute)
- Different scaling constraints than traditional LLM pre-training
This means o1’s performance can be enhanced by allowing more processing time, a fundamentally different paradigm from GPT-4o .
10. Specialized Models and Use Case Optimization
The final major upgrade is the introduction of specialized variants tailored for specific tasks .
The o1 Model Family
o1-preview:
- Full-scale reasoning model
- Best for most difficult tasks
- Resource-intensive but highly capable
o1:
- Balanced reasoning and performance
- General-purpose advanced reasoning
- Suitable for wide range of applications
o1-mini:
- Optimized for coding and STEM
- 80% cheaper than o1-preview
- Faster inference
- Smaller footprint
o1-ioi:
- Specialized for competitive programming
- Achieved 1,807 Elo rating (93rd percentile)
- Scored 213 points in 2024 IOI (49th percentile)
GPT-4o Variants
GPT-4o:
- Full multimodal flagship model
- Best for general-purpose AI tasks
- Optimal speed-to-capability ratio
GPT-4o mini:
- Smaller, more affordable
- Faster inference
- Suitable for simpler tasks
- Cost-effective deployment
Choosing the Right Model for Your Needs
Choose o1-preview or o1 when:
- Solving complex mathematical problems
- Conducting scientific research
- Tackling advanced reasoning challenges
- Accuracy is paramount over speed
Choose o1-mini when:
- Developing software and debugging code
- Need cost-effective reasoning
- Working on STEM-specific problems
- Speed matters alongside reasoning
Choose GPT-4o when:
- Requiring multimodal capabilities
- Speed is critical
- Handling customer-facing applications
- Processing audio, images, or video
- Broad general knowledge is needed
Choose GPT-4o mini when:
- Budget constraints are tight
- Simple tasks don’t require flagship performance
- High-volume, low-complexity processing
Ready to implement the right AI model for your business? Contact Ranking Mantra today to discuss your specific requirements and get expert guidance.
Conclusion: Choosing Between ChatGPT 4o and o1
The chatgpt 4o vs o1 decision isn’t about which model is universally better—it’s about matching AI capabilities to your specific needs .
Quick Decision Framework
Choose GPT-4o if you need:
- ✅ Fast response times for customer interactions
- ✅ Multimodal processing (audio, video, images)
- ✅ Cost-effective solutions for general tasks
- ✅ Broad general knowledge
- ✅ Real-time conversational interfaces
- ✅ Content creation and creative writing
Choose o1 if you need:
- ✅ Advanced mathematical problem-solving
- ✅ Complex coding and debugging
- ✅ Scientific research and analysis
- ✅ Multi-step reasoning tasks
- ✅ PhD-level accuracy
- ✅ Enhanced AI safety and security
- ✅ Situations where accuracy trumps speed
Choose o1-mini if you need:
- ✅ Cost-effective advanced reasoning
- ✅ STEM-focused problem-solving
- ✅ Fast coding assistance
- ✅ Budget-conscious AI deployment
The Hybrid Approach
Many organizations benefit from using both:
- GPT-4o for customer-facing applications, content generation, and rapid responses
- o1 for backend analysis, complex calculations, and critical decision support
- o1-mini for development teams and technical problem-solving
Performance at a Glance
| Capability | Winner | Margin |
| Reasoning | o1 | Significant (83% vs 13% on AIME) |
| Coding | o1 | Substantial (89th vs 11th percentile) |
| Speed | GPT-4o | 103 tokens/sec vs slower o1 |
| Multimodal | GPT-4o | Audio/video support |
| Cost | GPT-4o | 6x cheaper output tokens |
| Safety | o1 | Much better (84 vs 22 on jailbreak) |
| Math/Science | o1 | Exceeds PhD-level performance |
Real-World Implementation
The chat gpt o1 vs o3 and future comparisons will continue to evolve as OpenAI releases new models. However, the fundamental trade-off between speed and reasoning depth will likely persist .
For businesses ready to harness AI’s full potential:
Whether you need GPT-4o’s versatility or o1’s advanced reasoning, successful AI implementation requires:
- Strategic planning
- Proper model selection
- Expert guidance
- Continuous optimization
At Ranking Mantra, we specialize in helping organizations:
- Assess AI readiness and determine which models fit your use cases
- Implement AI solutions that drive measurable business outcomes
- Optimize AI workflows for maximum efficiency and ROI
- Train teams to leverage AI capabilities effectively
- Navigate the rapidly evolving AI landscape
Take the Next Step
Don’t let the chatgpt 4o vs o1 decision paralyze your AI adoption. The right model—or combination of models—can transform your business operations, enhance productivity, and unlock new capabilities.
Contact Ranking Mantra today to:
- Schedule a free AI consultation
- Discuss your specific business needs
- Get expert recommendations on model selection
- Explore implementation strategies
- Learn how to maximize your AI investment
The AI revolution is here, and the organizations that act now will lead their industries tomorrow. Whether you choose GPT-4o for speed, o1 for reasoning, or a hybrid approach, make sure you have the right partner to guide your AI journey.
Start your AI transformation with Ranking Mantra—where cutting-edge AI meets strategic business expertise.
Note – The future of AI is both fast and thoughtful. With ChatGPT-4o and o1, you don’t have to choose between speed and intelligence—you can leverage both to create AI-powered solutions that truly transform your business.
