ChatGPT-5 vs GPT-5 Pro vs o3 vs 4o: 2025 Benchmarks, Costs, Best Uses

TL;DR - Best model by job:
• Coding & complex reasoning: GPT-5 / GPT-5 Pro
• General chat at lower cost: 4o
• Math/logic with tools: o3
• Docs/data analysis & long context: GPT-5
• Lowest cost at scale: GPT-5 mini / API mix
• Automation & workflows: ChatGPT Agent
(Benchmarks, pricing, and step-by-step picks below.)

On August 7, 2025, OpenAI has released ChatGPT 5. With legacy models like GPT-4o being officially retired and new specialized versions like GPT-5 Pro emerging, how do you navigate this new landscape?

This article provides the definitive guide to OpenAI's 2025 lineup. We'll benchmark the standard ChatGPT 5, the powerhouse GPT-5 Pro, the new ChatGPT Agent capabilities, and the specialized Deep Research mode against their predecessors, OpenAI o3 and GPT-4o, to help you choose the perfect tool.

Which OpenAI Model Delivers the Best Performance, and How Does ChatGPT 5 Redefine the Lineup?

ChatGPT 5 represents a fundamental shift in how OpenAI structures its AI offerings. Rather than requiring users to manually select between different models for different tasks, the new unified ChatGPT 5 system automatically switches between fast and deep thinking modes based on your needs.

The key innovation lies in what OpenAI calls the "real-time router" - an intelligent system that analyzes conversation type, complexity, tool needs, and user intent to determine whether to use the quick-response model or engage the deeper "GPT-5 thinking" mode. According to OpenAI's technical documentation, this router is continuously trained on real signals including user model switches, preference rates, and measured correctness.

GPT-5 vs GPT-4 Differences - Quick Table (2025)

GPT-5 changes everyday outcomes: higher reasoning accuracy, stronger coding/math, and fewer tokens for the same work. Here’s what improves and where you feel it.

The New Model Hierarchy

Table 1: OpenAI's 2025 Model Lineup

The unified approach means that when you type a query into ChatGPT, the system automatically determines whether to provide a quick response or engage deeper reasoning. This eliminates the cognitive load of model selection while ensuring optimal performance for each query type.

How Does the New ChatGPT 5 Perform on Academic Science Benchmarks?

ChatGPT 5 GPQA Science Performance

The Graduate-Level Science Questions (GPQA) benchmark tests PhD-level understanding across multiple scientific disciplines. This evaluation reveals the dramatic improvements in ChatGPT 5's scientific reasoning capabilities.

ChatGPT 5 demonstrates remarkable performance on the GPQA Diamond benchmark, achieving:

• GPT-5 Pro (with Python): 89.4% accuracy

• GPT-5 (with Python): 87.3% accuracy

• OpenAI o3: 83.3% accuracy

• GPT-4o: 70.1% accuracy

The introduction of thinking mode provides a substantial boost, with GPT-5's accuracy jumping from 77.8% to 85.7% when reasoning is engaged. This represents a fundamental improvement in the model's ability to tackle complex scientific problems that require multi-step reasoning and deep domain knowledge.

LiveCodeBench Competitive Programming with ChatGPT 5

GPT-5 leads SWE-bench Verified at 74.9%, ahead of o3 69.1%, 4o 30.8%.

The SWE-bench Verified benchmark measures the ability to solve real-world GitHub issues.

Table 2: Software Engineering Performance Comparison

ChatGPT 5's coding prowess extends beyond simple problem-solving. According to OpenAI's developer documentation, the model shows particular improvements in:

• Complex front-end generation with aesthetic sensibility

• Debugging larger repositories

• Creating responsive websites and applications in a single prompt

• Understanding design principles like spacing, typography, and white space

How Do the New OpenAI Models Compare on Mathematical Reasoning, and What is the Role of ChatGPT 5?

ChatGPT 5 USAMO & AIME Mathematical Olympiad Performance

Mathematical reasoning represents one of the most significant leaps forward in ChatGPT 5's capabilities. The model's performance on competition mathematics benchmarks demonstrates expert-level problem-solving abilities.

The Harvard-MIT Mathematics Tournament (HMMT) results show near-perfect performance:

• GPT-5 Pro (with Python): 100% accuracy

• GPT-5 (with Python): 96.7% accuracy

• GPT-5 (no tools): 93.3% accuracy

• OpenAI o3: 93.3% accuracy

ChatGPT 5 HMMT Competitive Mathematics Results

The breakthrough in mathematical capabilities extends to expert-level challenges. On FrontierMath, which tests the boundaries of mathematical reasoning, ChatGPT 5 achieves unprecedented results.

Table 3: Expert-Level Mathematics Performance (FrontierMath Tier 1-3)

These results represent a paradigm shift in AI mathematical capabilities. According to research published by OpenAI, GPT-5's mathematical improvements stem from enhanced training on mathematical reasoning patterns and better integration of computational tools.

What Are the Agentic Capabilities of the New OpenAI Suite, and How Does ChatGPT 5 Contribute?

ChatGPT Agent Performance Analysis

The agentic capabilities of ChatGPT 5 represent a fundamental evolution in how AI systems can autonomously complete complex tasks. The BrowseComp benchmark measures the ability to search, browse, and synthesize information from the web.

ChatGPT Agent, powered by GPT-5's underlying architecture, achieves:

• 68.9% accuracy on agentic search and browsing tasks

• Outperforms standalone GPT-5 (54.9%) when specialized for web tasks

• Significantly exceeds OpenAI o3 (49.7%) in information synthesis

Comparing ChatGPT 5's Built-in Tools

The seamless integration of tools within ChatGPT 5 creates a fundamentally different user experience. The Tau2-bench function calling benchmark reveals how effectively the model coordinates multiple tools.

Table 4: Function Calling Performance Across Industries

The tool integration extends beyond simple function calling. ChatGPT 5 now includes:

• Canvas: Collaborative editing environment (documentation)

• Web Search: Real-time information retrieval using Bing integration

• Image Generation: DALL-E 3 integration for visual content

• Code Interpreter: Python execution environment

• Memory: Contextual understanding across conversations

How Does ChatGPT 5 Handle Abstract Reasoning and Deep Research Challenges?

ARC-AGI Abstract Reasoning with ChatGPT 5

Abstract reasoning capabilities show significant improvements in ChatGPT 5's architecture. The model demonstrates enhanced ability to identify patterns, make logical inferences, and solve novel problems without explicit training.

The multimodal reasoning capabilities are particularly impressive, as shown in the MMMU (Massive Multi-discipline Multimodal Understanding) benchmark:

Table 5: Multimodal Understanding Performance

ChatGPT Deep Research Connector Performance

The Deep Research feature, available through ChatGPT Plus and Pro subscriptions, enables comprehensive information synthesis across multiple sources. According to the ChatGPT Release Notes, this feature now supports:

• Google Drive integration (setup guide)

• Microsoft SharePoint connectivity

• Dropbox file access

• GitHub repository analysis

• HubSpot CRM data integration

• Custom connectors via Model Context Protocol (MCP)

The Deep Research capability shows exceptional performance on the Humanity's Last Exam benchmark, which tests expert-level knowledge across diverse subjects:

Which Model Offers the Best Processing Power, and What Makes the Unified ChatGPT 5 Unique?

Context Processing Comparison for ChatGPT 5

The unified ChatGPT 5 system introduces a revolutionary approach to resource allocation. Rather than fixed processing power, the model dynamically adjusts its computational resources based on query complexity.

The efficiency gains are remarkable. ChatGPT 5 achieves better performance than OpenAI o3 while using 50-80% fewer output tokens across various tasks. This efficiency translates directly to:

• Faster response times for simple queries

• More thorough analysis for complex problems

• Better resource utilization across the platform

GPT-5 Pro vs. ChatGPT 5 "Thinking Mode"

Understanding when to use GPT-5 Pro versus relying on the automatic thinking mode requires examining their performance characteristics:

Table 6: Thinking Efficiency Comparison

GPT-5 Pro provides extended reasoning for the most challenging tasks, making 22% fewer major errors than standard GPT-5 thinking mode according to OpenAI's evaluation data.

What Are the Real-World Performance Differences Within the New ChatGPT 5 Ecosystem?

Coding Challenge Assessment - ChatGPT 5 vs o3 vs 4o

The practical coding capabilities of ChatGPT 5 extend far beyond benchmark performance. The Aider Polyglot benchmark tests multi-language code editing abilities:

Table 7: Multi-Language Coding Performance

Real-world developers report that ChatGPT 5 excels at:

• Creating complete, functional applications from single prompts

• Understanding and implementing complex architectural patterns

• Generating aesthetically pleasing UI with proper spacing and typography

• Debugging across large codebases with multiple dependencies

ChatGPT 5 Business Application Matrix

For business applications, ChatGPT 5's performance on economically important tasks provides crucial insights:

Table 8: Business Performance Comparison

The model shows particular strength in tasks requiring:

• Subject matter expertise (comparable to or better than experts in ~50% of cases)

• Complex reasoning across multiple domains

• Integration with company-specific data and context

• Maintaining consistency across long-form content

Which Pricing Model Offers the Best Value for Accessing the Power of ChatGPT 5?

Comprehensive ChatGPT 5 Pricing Comparison

Understanding the value proposition of each tier requires examining both features and usage limits:

Table 9: ChatGPT 5 Pricing Tiers (August 2025)

According to OpenAI's pricing documentation, API access provides additional flexibility:

• GPT-5: $1.25 input / $10.00 output per 1M tokens

• GPT-5 mini: $0.25 input / $2.00 output per 1M tokens

• GPT-5 nano: $0.05 input / $0.40 output per 1M tokens

Return on Investment for ChatGPT 5 Pro - Should You Buy It?

The ROI analysis for GPT-5 Pro depends heavily on use case complexity and volume:

Table 10: ROI Analysis by User Type

The economic impact study by OpenAI suggests that Pro users see positive ROI within the first week of subscription for knowledge-intensive work.

What Are the Strengths and Weaknesses of Each OpenAI Offering Featuring ChatGPT 5?

ChatGPT 5 (Standard)

Strengths:

• Unified Intelligence: Automatic switching between fast and deep thinking modes eliminates model selection complexity

• Broad Accessibility: Available to all users with generous free tier access

• Versatile Performance: Excels across coding, writing, analysis, and creative tasks

• Tool Integration: Seamless access to web search, image generation, and code execution

Limitations:

• Usage caps on free tier (transitions to GPT-5 mini after limits)

• No access to extended reasoning of Pro variant

• Limited customization compared to API access

GPT-5 Pro

Strengths:

• Peak Performance: State-of-the-art results on challenging benchmarks (88.4% on GPQA without tools)

• Extended Reasoning: Thinks longer for comprehensive, accurate answers

• Minimal Errors: 22% fewer major errors than standard GPT-5 thinking

• Professional Features: Full access to all ChatGPT capabilities

Limitations:

• High cost ($200/month for Pro subscription)

• Overkill for simple tasks

• Longer response times due to extended reasoning

ChatGPT Agent

Strengths:

• Workflow Automation: Executes complex multi-step tasks autonomously

• Tool Coordination: Superior performance on function calling (80.1% average accuracy)

• Real-World Application: Designed for practical business processes

Limitations:

• Requires specific prompting and setup

• Limited to Plus subscribers and above

• May need supervision for critical tasks

GPT-4o & OpenAI o3 (Legacy)

Strengths:

• Familiar Baseline: Well-understood capabilities and limitations

• Stable Performance: Consistent behavior for existing workflows

• API Availability: GPT-4 remains available via API

Limitations:

• Deprecated in ChatGPT: No longer available in web interface after April 30, 2025

• Inferior Performance: Significantly outperformed by GPT-5 across all benchmarks

• Limited Multimodal: Weaker visual and video understanding

Which OpenAI Model Should You Choose? A Decision Framework Centered on ChatGPT 5

Decision Framework by Use Case with ChatGPT 5

Making the right choice depends on understanding your specific needs and matching them to the appropriate tier:

Daily Use & General Questions: Standard ChatGPT 5 on Free/Plus

For everyday queries, research, and general assistance, the standard ChatGPT 5 provides exceptional value. The free tier offers sufficient access for:

• Quick questions and explanations

• Basic coding assistance

• Simple content creation

• General research tasks

Recommended for: Students, casual users, individuals exploring AI capabilities

Software Development & Complex Problem Solving: GPT-5 Pro on Pro/Team Plans

Professional developers and technical teams benefit from GPT-5 Pro's enhanced capabilities:

The instruction-following improvements (99% accuracy with thinking mode) make GPT-5 Pro ideal for:

• Large-scale software architecture

• Complex debugging scenarios

• Performance optimization

• Code review and refactoring

Recommended for: Professional developers, engineering teams, technical consultants

Automating Business Processes: ChatGPT Agent Capabilities

Organizations seeking to automate workflows should leverage ChatGPT Agent features:

With 69.6% accuracy on multi-turn instruction following, ChatGPT Agent excels at:

• Customer service automation

• Data processing pipelines

• Report generation

• Multi-tool coordination

Recommended for: Operations teams, business analysts, process automation specialists

In-Depth Academic/Market Research: ChatGPT 5 with Deep Research Connectors

Researchers and analysts benefit from Deep Research capabilities:

Table 11: Research Capability Comparison

The Deep Research feature's ability to connect to Google Scholar, PubMed, and proprietary databases makes it invaluable for serious research work.

Safety, Accuracy, and Reliability of ChatGPT 5

ChatGPT 5 Has Reduced Hallucinations and Improved Factuality

One of ChatGPT 5's most significant improvements lies in its dramatically reduced hallucination rates:

Table 12: Factual Accuracy Improvements

According to OpenAI's safety documentation, these improvements result from:

• Enhanced training on factual consistency

• Better source attribution mechanisms

• Improved reasoning about uncertainty

• Advanced verification systems

ChatGPT 5 Deception and Honesty Metrics

ChatGPT 5 shows remarkable improvements in honest communication:

The model's ability to recognize and communicate its limitations represents a crucial advancement:

• Coding deception: Reduced from 47.4% (o3) to 16.5% (GPT-5)

• Missing information handling: 9% false confidence vs 86.7% for o3

• Production traffic deception: Only 2.1% vs 4.8% for o3

ChatGPT 5 Healthcare and Safety-Critical Applications

The healthcare performance improvements make ChatGPT 5 particularly valuable for health-related queries:

Table 13: Healthcare Performance Metrics

The model now provides more precise and reliable responses, adapting to user context, knowledge level, and geography. However, OpenAI emphasizes that ChatGPT does not replace medical professionals.

GPT-5 Improvements Over GPT-4 (ChatGPT-5 vs ChatGPT-4 Differences)

The jump from GPT-4 (and its multimodal successor GPT-4o) to GPT-5 marks one of the biggest capability upgrades in ChatGPT’s history. GPT-5 isn’t just faster—it’s smarter, more accurate, and better equipped for the kinds of complex, real-world tasks people use ChatGPT for daily. From massive coding and math gains to a sharp drop in hallucinations and new personalization options, the difference is clear. The table below gives you a side-by-side look at exactly how ChatGPT-5 outperforms ChatGPT-4.

Recap of Key GPT-5 Improvements Over GPT-4

• Reasoning: GPT-5’s deep thinking mode closes the gap with expert-level problem solving, far beyond GPT-4’s limits.

• Accuracy: Up to 80% fewer factual errors when reasoning, and major leaps in health, math, and coding benchmarks.

• Efficiency: Completes complex reasoning tasks with half the output tokens needed by earlier models.

• Safety & Trust: Reduces over-agreeable (“sycophantic”) answers by over 50% while improving honesty about limitations.

• Personalization: New personalities and better instruction-following make it easier to tailor ChatGPT to your style.

If you’re wondering whether GPT-5 is worth the switch from GPT-4, the data speaks for itself. The improvements span speed, accuracy, safety, and versatility, with measurable leaps in every major benchmark. Whether you’re coding, doing research, writing creatively, or asking complex reasoning questions, GPT-5 delivers a more reliable and human-like experience, making it the clear new standard for ChatGPT users.

Final Recommendation - Should You Get ChatGPT 5?

ChatGPT 5 represents more than an incremental improvement. It's a fundamental reimagining of how AI systems adapt to user needs. The unified architecture eliminates the friction of model selection while delivering superior performance across every benchmark.

Key Takeaways for Decision Makers

For Individuals:

• Start with the free tier to experience ChatGPT 5's capabilities

• Upgrade to Plus ($20/month) when you need more capacity and tools

• Consider Pro ($200/month) only if you're doing professional knowledge work

For Businesses:

• Team plans ($25/user) provide the best balance of features and cost

• Invest in training employees on prompt engineering and tool usage

• Leverage Deep Research connectors for competitive intelligence

For Developers:

• API access provides maximum flexibility and control

• GPT-5's improved instruction following reduces development time

• Consider GPT-5 mini for high-volume, cost-sensitive applications

Additional Resources

Read our previous research comparing Claude 4 with other AI Models like Grok 4, Gemini 2.5 Pro and o3.

Official OpenAI Resources:

• ChatGPT Homepage

• OpenAI API Documentation

• GPT-5 Research Paper

• Pricing and Plans

• Safety and Alignment Research

Developer Resources:

• OpenAI Cookbook

• GPT Best Practices Guide

• API Rate Limits Documentation

• Model Context Protocol (MCP)

Google and Technical Resources:

• Google AI Blog

• Understanding Transformer Models

• AI Safety Best Practices

Benchmark Resources:

• SWE-bench Official Site

• MMMU Benchmark Paper

• HealthBench Evaluation Framework

• FrontierMath Challenge

This comprehensive analysis represents the current state of OpenAI's model ecosystem as of August 2025. As the field of artificial intelligence continues to evolve rapidly, we recommend checking OpenAI's official blog and release notes for the latest updates and improvements to the ChatGPT platform.

FAQs - GPT-5 vs o3 vs 4o (2025)

Is GPT-5 better than o3?

On OpenAI’s own real-world coding benchmark (SWE-bench Verified), GPT-5 scores 74.9% vs 69.1% for o3, while also improving math and multimodal benchmarks. Use GPT-5 when you need the best end-to-end coding and agentic outcomes; use o3 when you want deliberate, reasoning-heavy steps with strong visual analysis.

GPT-5 vs GPT-4o: which one should I pick?

GPT-5 leads on reasoning and coding SOTA; third-party roundups and OpenAI data show large gains (e.g., SWE-bench Verified 74.9% for GPT-5, with 4o far lower in external tests). Pick GPT-5 for complex work; pick 4o for general chat and creative, low-latency experiences.

What’s the GPT-5 context window and output limit?

400K token context with up to 128K output tokens, with text+vision support. That makes GPT-5 suitable for long PDFs, spreadsheets, and multimodal analysis without chunking in many cases.

How much does GPT-5 cost in the API?

List prices: $1.25 / 1M input tokens, $10.00 / 1M output tokens. “Cached input” is $0.125 / 1M when you reuse identical prompts for efficiency. GPT-5 mini is cheaper for well-defined tasks.

Where can I use GPT-5 today?

In ChatGPT and the OpenAI API (Responses/Assistants). Check your plan and region; enterprise tenants can also access through Azure OpenAI. Developers can select the gpt-5 family in model lists.

When should I choose o3 over GPT-5?

Choose o3 (or o3-pro) for problems that need long, step-by-step deliberation and visual reasoning in the chain of thought, or when you want stricter reasoning controls. Choose GPT-5 for the best overall task completion rate and agentic workflows.

Is GPT-4o deprecated?

No. gpt-4o remains documented and is still available in some plans/workflows, though OpenAI positions GPT-5 as the primary flagship going forward. Availability can change by plan/region.

Which OpenAI model is best for coding right now?

GPT-5 sits at the top of public coding leaderboards and OpenAI’s own release notes (e.g., 74.9% on SWE-bench Verified). If you need lower cost with strong reasoning, o3 is close; for quick chatty fixes, 4o is fine.

Does GPT-5 support images and tools?

Yes. GPT-5 is text+vision, supports large contexts, and can call tools/functions. Use it for document+image understanding and multi-tool agentic flows.

Any cost tips when migrating to GPT-5?

Use cached input pricing for repeated prompts/templates, route easy tasks to GPT-5 mini, and save output by returning structured, compact JSON. These three changes usually drop effective cost while preserving GPT-5 quality.

How much better is GPT-5 on GPQA Diamond than o3?

GPT-5 scores 87.3% vs 83.3% for o3; GPT-5 Pro reaches 89.4%.

Who wins on SWE-bench Verified?

GPT-5 (thinking) 74.9% vs o3 69.1%; 4o trails at 30.8%.

Is GPT-5 actually more efficient per task?

Yes. Medium difficulty drops from ~7,000 output tokens to ~4,000 for the same result.

Is HMMT really perfect on Pro?

GPT-5 Pro (with Python) hits 100%, GPT-5 hits 96.7%; o3 is 93.3%.