Key Points: In August 2025, the AI field achieved a new milestone. OpenAI's GPT-5, Anthropic's Claude4Opus, and Google's Gemini2.5Pro represent the current top level of large language models. This article will provide an in-depth evaluation and comparison of these three top AI models based on the latest benchmark test data.
Key Findings: GPT-5 excels in mathematical reasoning (AIME2025 at 94.6%), Claude4Opus becomes the new king in programming (SWE-bench at 72.5%), while Gemini2.5Pro leads in long context and multimodal processing (1 million token context window).
I. Overview of the AI Model Landscape in 2025
On August 7, 2025, OpenAI officially released GPT-5, marking a new stage in the development of large language models. At the same time, Anthropic's Claude4Opus (launched in May) and Google's Gemini2.5Pro formed a tripartite competitive landscape. This GPT-5 evaluation will deeply analyze the performance differences of these three models across various dimensions.
From an overall architecture perspective, these three models all use a hybrid reasoning mode, capable of intelligently switching between fast response and deep thinking. GPT-5 uses a unified system architecture, integrating a fast model, a deep reasoning model, and a real-time router; Claude4Opus offers immediate response and extended thinking modes; while Gemini2.5Pro stands out as the preferred tool for processing long documents due to its massive context window.
II. Core Performance Benchmark Test Comparison
To objectively evaluate the actual capabilities of the three models, we collected the latest official benchmark test data. The following table shows the comparison results of key indicators:
| Benchmark Test | GPT-5 | Claude4Opus | Gemini2.5Pro | Test Description |
|---|---|---|---|---|
| SWE-bench Verified | 74.9% | 72.5% | 63.8% | Software engineering practical tasks |
| AIME2025 | 94.6% | 33.9% | 86.7% | Math competition questions |
| AIME2024 | 88.0% | 33.9% | 92.0% | Math competition questions |
| MMMU | 84.2% | 73.7% | 81.7% | Multimodal understanding |
| GPQA Diamond | 88.4% | 74.9% | 84.0% | Scientific question-answering reasoning |
| MRCR (128K) | 48.8% | - | 91.5% | Long context reading comprehension |
| Terminal-bench | - | 43.2% | - | Terminal operation tasks |
| LiveCodeBench v5 | - | - | 70.4% | Real-time programming challenges |
2.1 Programming Ability Comparison Analysis
In terms of programming ability, GPT-5 demonstrates comprehensive advantages. In the SWE-bench Verified benchmark test, GPT-5 scored 74.9%, indicating its outstanding performance in practical software engineering tasks. Claude4Opus follows closely with 72.5%, earning it the title of "Best Programming Model in the World." In contrast, Gemini2.5Pro's performance in programming is relatively conservative at 63.8%.
Notably, Claude4Opus performed exceptionally well in the Terminal-bench test, achieving 43.2%, which demonstrates its professional capability in terminal operations and system management tasks. For developers who need to perform complex codebase operations and debugging, both GPT-5 and Claude4Opus are excellent choices.
2.2 Evaluation of Mathematical Reasoning Ability
Mathematical reasoning ability is an important indicator for measuring AI model logic thinking. In the AIME2025 test, GPT-5 achieved an impressive score of 94.6%, approaching the level of human math competition elites. Gemini2.5Pro performed best in AIME2024 (92.0%) but slightly declined in 2025 (86.7%).
Claude4Opus is relatively weaker in mathematical reasoning, scoring only 33.9% in the AIME test. This indicates that although Claude4Opus performs excellently in programming, it still has room for improvement in pure mathematical reasoning tasks.
2.3 Multimodal Processing Ability
In terms of multimodal understanding, GPT-5 reached 84.2% in the MMMU benchmark test, demonstrating its comprehensive ability in handling various input types such as text, images, and audio. Gemini2.5Pro followed closely with 81.7%, but considering its native support for video input, its actual multimodal application capability may be even more outstanding.
Claude4Opus has relatively limited performance in multimodal aspects (73.7%), mainly because its design focus is more on text processing and programming tasks.
III. Deep Comparison of Functional Features
3.1 Context Processing Ability Comparison
In terms of context processing ability, Gemini2.5Pro has an absolute advantage. Its 1 million token context window (planned to expand to 2 million) allows it to handle entire books, large codebases, or detailed technical documents. The 91.5% score in the MRCR benchmark test fully proves this capability.
By contrast, GPT-5 and Claude4Opus have smaller context windows, but they can already meet most scenario needs in practice. GPT-5 achieves more efficient context utilization through its unified architecture, while Claude4Opus enhances long-term task processing capabilities through improved memory mechanisms.
3.2 Safety and Reliability
GPT-5 adopts a new "safe completion" training paradigm for safety, which is more flexible and practical compared to traditional rejection-based safety training. Official data show that GPT-5's hallucination error rate has decreased by 45% compared to GPT-4o, showing significant improvements in factual accuracy.
Claude4Opus inherits Anthropic's consistent safety-first philosophy, ensuring the safety and harmfulness of output content through Constitutional AI training methods. In reducing shortcut behaviors, Claude4Opus improves by 65% compared to Claude3.7Sonnet.
Although Gemini2.5Pro does not have particularly outstanding innovations in safety, Google's long-term investment in responsible AI provides reliable safety guarantees for it.
IV. Usage Scenarios and Application Recommendations
4.1 Programming and Software Development
Recommended order: GPT-5 > Claude4Opus > Gemini2.5Pro
For software developers, GPT-5, with its 74.9% SWE-bench score, is the first choice. Its ability to create beautiful and responsive websites, applications, and games in complex front-end generation and debugging large codebases is particularly outstanding. As the "Best Programming Model in the World," Claude4Opus excels in code quality and accuracy, making it especially suitable for scenarios requiring long-term focused programming tasks.
Although Gemini2.5Pro performs generally in programming benchmark tests, its vast context window gives it unique advantages in tasks such as large-scale codebase analysis and document generation.
4.2 Mathematics and Scientific Research
Recommended order: GPT-5 > Gemini2.5Pro > Claude4Opus
In the fields of mathematical reasoning and scientific research, GPT-5 showcases PhD-level intelligence with a 94.6% score in AIME2025. Its ability to solve complex mathematical problems and analyze scientific papers is close to the level of professional researchers.
Gemini2.5Pro's 84.0% score in the GPQA Diamond test shows its strength in scientific question-answering. Combined with its multimodal capabilities, it is particularly suitable for handling research documents that include charts and formulas.
4.3 Long Document Processing and Analysis
Recommended order: Gemini2.5Pro > GPT-5 > Claude4Opus
For scenarios requiring processing long documents, research reports, and legal documents, Gemini2.5Pro's 1 million token context window gives it a decisive advantage. The 91.5% score in the MRCR test proves its excellent ability in long-context understanding.
This characteristic makes Gemini2.5Pro an ideal choice for professionals such as lawyers, researchers, and consultants, as it can process entire books or complete project documents in one go.
4.4 Multimedia Content Creation
Recommended order: Gemini2.5Pro > GPT-5 > Claude4Opus
In multimedia content processing, Gemini2.5Pro supports multiple input formats such as text, images, audio, and video, giving it a clear advantage in content creation and media analysis. Its ability to understand and analyze video content provides creators with powerful tools.
Although GPT-5 performed best in the MMMU test (84.2%), in practical multimedia applications, Gemini2.5Pro's native multimodal support may be more practically valuable.
💡 Professional Model Selection Advice
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The AIbase Model Square not only supports comparisons of top models like GPT-5, Claude4Opus, and Gemini2.5Pro, but also provides a wealth of testing tools and benchmark data. It is an indispensable reference platform for AI practitioners and enterprise decision-makers. Through its intuitive comparison interface, you can quickly understand the performance differences of different models in specific tasks, thus making informed technical choices.
V. Pricing and Availability Analysis
5.1 Cost-Effectiveness Analysis
From a pricing perspective, GPT-5 and Gemini2.5Pro offer the same price level ($1.25/$10.00), while Claude4Opus has a significantly higher price ($15/$75). Considering the performance differences, GPT-5 offers better balance in most tasks, therefore providing the highest overall cost-effectiveness.
Gemini2.5Pro, although slightly inferior to GPT-5 in some benchmark tests, offers irreplaceable value for specific use cases with its unique long-context capabilities and multimodal support. The high pricing of Claude4Opus mainly reflects its professional programming capabilities and enterprise-grade reliability.
5.2 Access Methods and Deployment Options
GPT-5 is currently available through the ChatGPT platform and the OpenAI API, supporting multiple subscription tiers including Plus, Pro, Team, and Enterprise. Enterprise users can obtain higher usage limits and priority support.
Claude4Opus is available through the Claude.ai web version, API, and cloud platforms such as Amazon Bedrock and Google Cloud Vertex AI. Its enterprise deployment options are more diverse, suitable for integration needs of large organizations.
Gemini2.5Pro is currently primarily accessible through Google AI Studio and the Gemini API, and is planned to be launched on the Vertex AI platform soon. Google also provides a Gemini Advanced subscription plan for individual users, offering a more convenient access method.
VI. Technical Architecture Deep Dive
6.1 Unified System Architecture of GPT-5
GPT-5 adopts an innovative unified system design, integrating three core components: the intelligent and efficient model handles most routine questions, the deep reasoning model (GPT-5thinking) specializes in complex issues, and the real-time router intelligently decides which model to use based on the conversation type, complexity, tool requirements, and user explicit intent.
The advantage of this architecture lies in maintaining response speed while providing high-quality output. The router continuously improves its decision-making capabilities by learning real signals such as user model switching behavior, response preference rates, and accuracy measurements.
6.2 Hybrid Reasoning Mode of Claude4Opus
Claude4Opus adopts a hybrid reasoning architecture, supporting two modes: near-instant response and extended thinking. Notably, it supports using tools during extended thinking, allowing for alternating between reasoning and tool usage, thereby significantly improving response quality.
In terms of memory capabilities, Claude4Opus can create and maintain "memory files" to store key information, providing strong support for long-term task perception, coherence, and agent task performance.
6.3 Large Context Architecture of Gemini2.5Pro
The core advantage of Gemini2.5Pro lies in its massive context processing capability. A 1 million token context window (approximately 750,000 English words) enables it to process complete technical manuals, research reports, or codebases in a single conversation.
This model also has strong multimodal integration capabilities, able to process text, images, audio, and video inputs simultaneously, providing an ideal technical foundation for complex multimedia analysis tasks.
VII. Practical Application Case Analysis
7.1 Enterprise-Level Application Scenarios
In enterprise applications, the three models demonstrate different professional characteristics. Cursor Company rated Claude4Opus as "the latest technology in the programming field," believing that it achieved breakthrough progress in understanding complex codebases. Replit reported that Claude4Opus showed significant precision and advancement in multi-file complex changes.
GPT-5 performed well in internal benchmark tests for economic value knowledge work, and in tasks covering over 40 professions such as law, logistics, sales, and engineering, GPT-5 was comparable to or better than experts in about half of the cases when using reasoning functions.
Google's enterprise customers mainly use Gemini2.5Pro's long-context capability to handle large document analysis, compliance checks, and knowledge management tasks. Its 1 million token processing capability has unique value in these scenarios.
7.2 Developer Ecosystem
GitHub announced that Claude Sonnet4 would be the driving model for its new programming agent GitHub Copilot, reflecting Claude's outstanding performance in agent scenarios. Sourcegraph reported that Claude Sonnet4 showed substantial progress in software development, being able to stay on the right track for longer periods, understand problems more deeply, and provide more elegant code quality.
OpenAI provides developers with rich GPT-5 integration tools, including the Codex CLI command-line interface, enabling developers to directly use GPT-5 for programming tasks in the terminal.
VIII. Future Development Trend Predictions
8.1 Technology Evolution Directions
Based on the characteristics of the three models, we can foresee that future AI model development will revolve around the following directions:
- Standardization of Hybrid Reasoning Architecture: All major models adopt a combined architecture of fast response and deep reasoning, which will become an industry standard.
- Continuous Expansion of Context Window: Gemini2.5Pro plans to expand to 2 million tokens, and other models are expected to follow this trend.
- Enhancement of Multimodal Capabilities: Video understanding and audio processing capabilities will become basic configurations.
- Parallel Development of Specialization and Generalization: Models will maintain general capabilities while achieving deeper specialization in specific fields (such as programming, scientific research).
8.2 Expansion of Application Scenarios
With the improvement of model capabilities, we expect the following application scenarios to develop rapidly:
- Autonomous Software Development: Based on the programming capabilities of GPT-5 and Claude4Opus, completely autonomous software development workflows will become possible.
- Research Assistant: GPT-5's mathematical reasoning capability enables it to take on more research assistance work.
- Large-Scale Document Intelligence: Gemini2.5Pro's long-context capability will drive revolutionary changes in corporate knowledge management.
- Automated Multimedia Content: The combination of video understanding and generation capabilities will open up new content creation models.
Conclusion and Selection Recommendations
Comprehensive Evaluation Results: