Evolution of Large Language Models

AI models have evolved at breakneck speed since 2018:

• GPT Series: Starting with GPT-1, OpenAI’s iterative improvements culminated in GPT-5’s 2025 release with its 400,000-token context window
• Claude: Emerged in the early 2020s with a focus on safety, interpretability, and extended context capabilities
• Gemini: Evolved from Google’s Bard to become a fully multimodal platform deeply integrated with Google Workspace

This rapid development has created industrial-scale AI systems with vastly expanded capabilities in reasoning, context handling, and multimodal processing. These systems are increasingly being deployed in multi-agent configurations for complex business applications.

Vellum AI provides comprehensive benchmark data on these models.

GPT-5: OpenAI’s Latest Achievement

OpenAI’s GPT-5 development prioritized four key areas:

1. Expanded context window (400k tokens)
2. Enhanced safety protocols
3. Specialized knowledge domains (especially healthcare)
4. Cost efficiency ($1.25/$10 per million input/output tokens)

GPT-5’s performance on math benchmarks is remarkable, achieving perfect accuracy on complex tests like AIME 2025. Available through ChatGPT Pro and API access, GPT-5 offers significant improvements in reasoning, multimodal processing, and overall reliability compared to GPT-4.

Claude: Anthropic’s Safety-First Approach

Anthropic built Claude around interpretability, long-context handling, and methodical reasoning. Its architecture emphasizes safety and transparency at every level.

Claude’s standout features include “memory files” for persistent context between sessions and exceptional code generation capabilities. While expensive at premium tiers ($15/$75 per million tokens for Opus 4.1), Claude demonstrates superior coding abilities, capable of creating complex applications and games autonomously.

Gemini: Google’s Multimodal Contender

Google developed Gemini as a natively multimodal model, training it simultaneously across text, images, and audio inputs. Its deep integration with Google’s ecosystem (Gmail, Docs, Android) creates a seamless user experience.

Gemini offers competitive pricing similar to GPT-5 ($1.25/$10 per million tokens) with both standard and pro-tier options. Its strengths include real-time data access, excellent scalability within Workspace environments, and cost-effective implementation.

Technical Capabilities Head-to-Head

Each model employs different training methodologies and architectural approaches, resulting in varying parameter counts and efficiency metrics. On standard industry benchmarks, GPT-5 currently leads in most categories. Understanding how these models function as intelligent agents can provide deeper insight into their capabilities and limitations.

Practical Performance Comparison

In natural language tasks, all three models excel, though GPT-5 offers the most reliable overall experience. For reasoning and problem-solving, Gemini excels with real-time factual analysis, while GPT-5 and Claude provide more nuanced step-by-step reasoning (with Claude showing particular strength in philosophical contexts).

For creative content generation, Claude and GPT-5 lead the pack, with Claude having a slight edge in complex interactive coding tasks. In multimodal implementation, Gemini provides the most seamless experience, though GPT-5’s capabilities remain highly competitive.

ChatGPT/GPT-5 receives consistent praise for interface polish and operational stability.

User Experience and Interface Comparison

GPT-5 offers extensive customization options, professional workflow integrations, and multi-platform accessibility (web, iOS, Android). Claude excels at long-form content generation through its website interface but has limitations in mobile experience and third-party integrations.

Gemini’s deep embedding in Google’s cloud and productivity ecosystem makes it ideal for existing Workspace users, with response formatting and consistency tailored to Google’s design language. Integrating these AI models effectively into your existing workflows requires careful optimization to maximize productivity.

Specialized Use Cases: Which Model Excels Where?

• Coding and Development: Claude 4 delivers the most impressive code and technical project results, while Gemini offers the most budget-friendly option for scalable coding tasks
• Academic Research: GPT-5’s extended context window makes it optimal for document-heavy, nuanced scholarly work
• Enterprise Use: Gemini’s integration advantages benefit large organizations, while GPT-5 provides versatility for API-centric implementations
• Creative Content: Both Claude and GPT-5 excel, with specific strengths depending on the creative medium

For small and medium enterprises looking to implement AI solutions, the right choice depends on specific business needs and budget constraints.

Ethical and Safety Considerations

Claude leads with its cautious approach that prioritizes error avoidance and transparency in reasoning. GPT-5 and Gemini both implement extensive content filtering systems, with GPT-5 featuring specialized safety optimizations for health-related topics.

All three platforms employ bias management techniques, though their approaches to detection and mitigation vary. Privacy policies, data retention practices, and user control options also differ between platforms.

Cost and Accessibility Comparison

GPT-5 and Gemini Pro offer the most affordable pricing at $1.25/$10 per million input/output tokens, while Claude is significantly more expensive at premium tiers ($15/$75 per million tokens for Opus 4.1).

API availability, rate limits, and integration options vary across platforms, with GPT-5 and Gemini offering the most flexible options for developers. Geographic availability is nearly universal for all major models, though Gemini faces some regional restrictions based on Google’s licensing agreements.

Expert and User Opinions

Benchmark data consistently shows GPT-5’s dominance in mathematics and general reasoning tests. Expert assessments highlight Claude’s superior performance in code generation and certain creative applications, while industry recognition of Gemini focuses on its integration advantages, processing speed, and favorable total cost of ownership.

User feedback generally praises GPT-5 for reliability, Claude for depth of reasoning, and Gemini for seamless Google integration.

Answering the Question: Is GPT-5 Better than Claude and Gemini?

The answer depends entirely on your specific requirements:

• GPT-5 leads on public benchmarks and reliability metrics, making it the default choice for precision and mission-critical applications
• Claude excels specifically in coding tasks and deeply reasoned outputs, particularly valuable for research or complex programming projects
• Gemini shines in real-time information processing, budget-conscious scaling, and Google Workspace integration

Each model leads in at least one important domain, making a universal “best” impossible to declare.

Future Developments and Roadmaps

OpenAI plans to expand GPT-5’s multimodal capabilities and add persistent memory features in upcoming updates. Claude’s development roadmap focuses on enhanced memory capabilities and limited multimodal functionality. Gemini’s future trajectory emphasizes expanded modalities and deeper integration across Google’s product ecosystem.

Industry-wide trends point toward increased personalization, specialized vertical models, and improved reasoning capabilities across all platforms. For a broader perspective on where AI is headed in 2025 and beyond, explore our analysis of emerging AI trends.

Conclusion and Recommendations

When choosing between these new AI models, consider:

• For general-purpose use and reliability: GPT-5
• For complex code and creative projects: Claude
• For Google-centric environments and cost-effective scaling: Gemini

The rapid pace of development in AI models means these comparisons will evolve quickly. Evaluate models based on your specific use cases rather than general rankings, and regularly reassess as capabilities change.

What AI assistant needs do you have? Share your experiences with these new AI models in the comments below.

FAQ

Q1: Which AI model has the largest context window in 2025?

A1: GPT-5 leads with a 400,000 token context window, allowing it to process and reference the equivalent of hundreds of pages of text in a single conversation.

Q2: Is Claude better than GPT-5 for programming tasks?

A2: Yes, Claude consistently outperforms both GPT-5 and Gemini in complex coding tasks, though it comes at a significantly higher cost per token.

Q3: Which AI model integrates best with Google products?

A3: Gemini provides the most seamless integration with Google’s ecosystem, including Gmail, Docs, and Android platforms.

Q4: What are the pricing differences between these AI models?

A4: GPT-5 and Gemini offer similar pricing at approximately $1.25/$10 per million input/output tokens, while Claude’s premium tiers (Opus 4.1) are significantly more expensive at $15/$75 per million tokens.

Q5: Can these AI models be used for healthcare applications?

A5: GPT-5 has specialized knowledge optimizations for healthcare topics with enhanced safety protocols, though all models require careful implementation and human oversight for healthcare applications.