Claude Opus 4 vs Gemini 2.5 Pro vs OpenAI o3: Comprehensive AI Model Comparison
- Leanware Editorial Team
- 5h
- 10 min read
Every major AI company is pushing to release the next generation of models, improving reasoning, coding capabilities, and AI agents. Recently, Anthropic and Google DeepMind released Claude Opus 4 and Gemini 2.5 Pro, joining OpenAI’s earlier release of o3 this year.
Let’s compare these models on their capabilities, performance, pricing, and practical use cases to understand which one fits different development and business needs.
TL;DR: Claude Opus 4 leads coding benchmarks at 72.5% SWE-bench, Gemini 2.5 Pro offers 1M token context for massive document processing, OpenAI o3 provides balanced performance with superior tool integration. Choose Claude for development work, Gemini for research applications, o3 for general enterprise needs.
Overview of the AI Models
These three models achieve nearly similar results on coding, reasoning, math, science, and visual benchmarks. Choosing between them depends on which provides better long-context support, API integration, and cost efficiency for your use case.
Claude Opus 4
Released on May 22, 2025, Claude Opus 4 is Anthropic’s most advanced model, built for long-form coding, multi-step reasoning, and agent workflows. It ranks highest on SWE-bench (72.5%) and Terminal-bench (43.2%), and maintains performance over extended sessions (Claude Opus 4 Launch Post). This makes it well-suited for editing, debugging, and working across large codebases.
It integrates with Claude Code for use in VS Code, JetBrains, and GitHub workflows. It supports extended thinking, tool use, improved memory from local file access, and delivers consistent performance across reasoning, multimodal input, and scientific tasks. Available via API at stable pricing, Opus 4 is a strong choice for engineering and research environments.
Gemini 2.5 Pro (Preview)
Gemini 2.5 Pro Preview is Google DeepMind’s most capable model, designed for reasoning, coding, and complex multimodal tasks. It supports text, images, audio, and video as input, with a 1 million token context window and 64k token output. The model builds on a refined sparse Mixture-of-Experts (MoE) Transformer architecture and is available via Google AI Studio and the Gemini API.
It includes a new “Deep Think” mode that improves reasoning using parallel thinking techniques. Benchmarks show strong performance: 83% on AIME 2025, 79.6% on MMMU, 75.6% on LiveCodeBench v5, and 63.2% on SWE-bench Verified. It also scores 76.5% / 72.7% (whole/diff) on Aider Polyglot for code editing (Google DeepMind Reports).
Versions:
gemini-2.5-pro-preview-05-06: Public preview, released May 6, 2025
gemini-2.5-pro-exp-03-25: Experimental, released March 28, 2025
OpenAI o3
Released on April 16, 2025, OpenAI o3 is a reasoning-focused model in the o-series, built for complex tasks and full tool use within ChatGPT - web browsing, Python, file analysis, image understanding, and image generation. It's designed to reason about when and how to use tools to provide structured, useful responses.
The model shows strong performance across benchmarks as reported by OpenAI:
69.1% on SWE-Bench (vs. o1’s 48.9%)
2706 ELO in competitive programming (vs. 1891)
91.6% on AIME 2024, 88.9% on AIME 2025 (vs. 74.3%)
83.3% on GPQA Diamond (vs. 78%)
Access:
Available for Plus, Pro, and Team users in ChatGPT, with API access and wider rollout in progress. A pro variant with extended tool capabilities is expected soon.
Key Features and Capabilities
Claude Opus 4: Advanced Coding and Reasoning
Claude 4 Opus is best known for its performance on complex, long-running coding tasks and multi-step agent workflows. It supports extended tool use and local file memory, helping maintain context over time.
These capabilities, along with deep IDE integrations, make it well-suited for developers working on large codebases, complex problem-solving, and advanced AI agent applications.
Gemini 2.5 Pro: Multimodal Integration and Reasoning
Gemini 2.5 Pro handles complex coding workflows and reasoning tasks well, especially in web development and structured problem-solving. It can generate, edit, and debug code for interactive apps and large codebases.
The model supports multimodal inputs - text, audio, images, and video. Its extended context window helps with long documents, complex prompts, and large datasets. It is a strong fit for users building web-based tools, agents, and apps that rely on integrated media or structured reasoning.
OpenAI o3: Tool Use and Visual Reasoning
OpenAI o3 performs well on complex reasoning tasks, especially in math, science, and coding. It uses tools like Python, web browsing, and image editing to solve problems more effectively.
The model supports multimodal input - text and images - and handles visual reasoning tasks like interpreting charts and graphics.
It can also self-check responses for accuracy and reason about safety in context. o3 fits well for agentic workflows, data analysis, and content generation. However, the o4-mini variant offers a faster, cost-efficient option for high-volume tasks.
Performance Benchmarks
Claude 4 Opus: SWE-bench and Terminal-bench Scores
Claude 4 Opus shows top-tier performance on coding benchmarks, scoring 72.5% on SWE-bench and 43.2% on Terminal-bench, according to Anthropic’s launch announcement.
It performs well in agentic coding and terminal-based workflows, supporting extended and complex coding sessions with consistent accuracy.
Performance Benchmarks (Anthropic, May 2025):
Task | Performance |
Agentic coding (SWE-bench Verified) | 72.5% / 79.4% |
Agentic terminal coding (Terminal-bench) | 43.2% / 50.0% |
Graduate-level reasoning (GPQA Diamond) | 79.6% / 83.3% |
Agentic tool use (Retail) | 81.4% |
Agentic tool use (Airline) | 59.6% |
Multilingual Q&A (MMLU) | 88.8% |
Visual reasoning (MMMU, validation) | 76.5% |
High school math (AIME 2025) | 75.5% / 90.0% |
Gemini 2.5 Pro: GPQA Diamond and Visual Reasoning
Gemini 2.5 Pro shows strong results across key benchmarks, with particular capabilities in reasoning, code generation, editing, and multimodal understanding. It ranks well on GPQA (graduate-level physics QA) and visual reasoning tests, handling spatial diagrams, charts, and figures with high accuracy.
Benchmark Performance GEMINI 2.5 PRO Preview (05-06) (Google DeepMind)
Benchmark | Performance |
Input price $/1M tokens | $2.50 $1.25 <= 200k tokens |
Output price $/1M tokens | $15.00 $10.00 <= 200k tokens |
Reasoning & knowledge (Humanity's Last Exam (no tools)) | 17.8% |
Science (GPQA diamond) | 83.0% (single attempt (pass@1)) |
Mathematics (AIME 2025) | 83.0% (single attempt (pass@1)) |
Code generation (LiveCodeBench v5) | 75.6% (single attempt (pass@1)) |
Code editing (Aider Polyglot) | 76.5% / 72.7% (whole / diff) |
Agentic coding (SWE-bench Verified) | 63.2% |
Factuality (SimpleQA) | 50.8% |
Visual reasoning (MMMU) | 79.6% (single attempt (pass@1)) |
Image understanding (Vibe-Eval (Reka)) | 65.6% |
Video (Video-MME) | 84.8% |
Long context (MRCR) | 93.0% (128k (average)) / 82.9% (1M (pointwise)) |
Multilingual performance (Global MMLU (Lite)) | 88.6% |
OpenAI o3: Competitive Programming and Multilingual QA
OpenAI o3 shows strong performance across benchmarks in coding, math, science, and visual reasoning. It achieves 69.1% on SWE-bench Verified without custom scaffolding and 83.3% on GPQA (PhD-level science). The model performs especially well on visual tasks, scoring 82.9% on MMMU and 86.8% on MathVista.
Compared to earlier OpenAI models, o3 makes significantly fewer major errors on real-world tasks. It's particularly effective for analytical reasoning in programming, business, and STEM domains, where multi-step evaluation and hypothesis generation are required.
Context Window and Memory Capabilities
Claude 4 Opus: 200K Token Context
Claude 4 Opus supports a 200,000-token context window, which makes it reliable for long-form tasks like legal document review, large-scale code analysis, and multi-step research. It keeps track of relevant details across long inputs and avoids context drift, even over extended interactions.
It also supports up to 32K output tokens and shows improved code taste - producing clean, structured output that matches the surrounding style. For engineering workflows, it can run background coding tasks and support agent-based systems that require persistent state and long-horizon reasoning.
Gemini 2.5 Pro: Up to 1 Million Tokens
Gemini 2.5 Pro supports a context window of up to 1 million tokens. This makes it a reliable option for working with large documents, such as full books, legal records, or mixed media inputs that include text, images, audio, and video.
It maintains high recall rates, achieving 100% for inputs up to around 530,000 tokens and 99.7% at the full 1 million tokens.
OpenAI o3: Contextual Understanding and Retention
OpenAI o3 supports a 200,000-token context window with a maximum output of 100,000 tokens. This allows it to handle complex queries that require multi-step reasoning and deep analysis across coding, math, science, and visual tasks.
Compared to lighter variants like o4-mini, o3 provides stronger reasoning capabilities and better multimodal performance. While o4-mini is faster and more cost-efficient for simpler tasks, o3 handles complex, multi-faceted problems more effectively without losing coherence.
Use Case and Integration
Claude 4 Opus: Coding, Agents, and Research
Claude 4 Opus handles advanced coding tasks like multi-step generation, refactoring, and debugging with up to 32K output tokens.
For AI agents, it manages long-term workflows such as automating marketing campaigns or coordinating enterprise processes.
When you need to research complex data sets, like academic papers, reports, or internal databases, Claude 4 Opus can search and summarize information accurately.
It also generates long-form content with a steady tone and clear structure, useful for documentation or knowledge articles.
You can access Claude 4 Opus through the Anthropic API, Amazon Bedrock, and Google Cloud Vertex AI.
Gemini 2.5 Pro: Reasoning and Multimodal Integration
Gemini 2.5 Pro handles tasks that need advanced reasoning, coding, multimodal understanding, and long context management. It supports Google Search grounding, code execution, function calling, controlled generation, token counting, and context caching.
You can access Gemini 2.5 Pro via Google AI Studio, the Gemini app for Advanced users, and Google Cloud’s Vertex AI. Using the “Deploy example app” feature requires a Google Cloud project with billing and the Vertex AI API enabled.
The model shares common limitations like hallucinations and struggles with complex logic and causal reasoning. Its knowledge cutoff is January 2025.
OpenAI o3: Reasoning and Enterprise Integration
OpenAI o3 is for advanced reasoning in coding, math, science, and visual tasks. It performs strongly on benchmarks like Codeforces, SWE-bench, and MMMU. So, it’s especially good at analyzing charts, diagrams, and solving multi-step problems.
Available via ChatGPT and the OpenAI API, o3 can be integrated into SaaS tools or internal systems through ChatGPT Enterprise or custom API workflows.
Pricing and Accessibility
Claude 4 Opus
Claude 4 Opus is available on Anthropic’s platform via web, iOS, and Android, with multiple tiers depending on usage needs:
Plan | Price |
Free | $0 |
Pro | $20/month ($17/month billed annually) |
Max | From $100/month |
Team | $25/person/month ($30/month billed monthly) |
Enterprise | Custom pricing |
API Pricing:
Category | Price per 1M Tokens |
Input | $15 |
Output | $75 |
Prompt Caching (Write) | $18.75 |
Prompt Caching (Read) | $1.50 |
Batch processing: Up to 50% discount
Prompt caching: Up to 90% cost reduction
Context window: 200K tokens
API access is metered and scalable, with enterprise options for higher throughput and priority support.
Gemini 2.5 Pro
Gemini 2.5 Pro is free with limited access on the Gemini App. Full access costs $19.99/month via Gemini Advanced (Pro) on Google One AI Premium. Vertex AI on Google Cloud offers full API access but requires a billed Google Cloud project with Vertex AI API enabled.
Note: Vertex AI pricing largely follows the legacy AI Platform and AutoML pricing, with exceptions for Gemini features like context caching and TTS.
Gemini 2.5 Pro (per 1M tokens)
Token Type | ≤200K Prompt | >200K Prompt |
Input | $1.25 | $2.50 |
Output (incl. thinking tokens) | $10.00 | $15.00 |
Context Caching | $0.31 | $0.625 |
Context Window Usage | $4.50/hour | — |
Additional Services
Feature | Free Tier | Paid Tier |
Google Search Grounding | 1,500 RPD | $35 / 1,000 requests |
Text-to-Speech (TTS) | Free | $1 input / $20 output per 1M tokens |
OpenAI o3
OpenAI o3 is included in these major ChatGPT subscription plans:
ChatGPT Plus at $20/month.
Pro at $200/month.
Team at $25 per user/month (billed annually) or $30 per user/month (billed monthly).
Enterprise with custom pricing.
API access is usage-based:
Input tokens: $10 per million.
Cached input tokens: $2.50 per million.
Output tokens: $40 per million.
Use Case Scenarios
Each model is suited to different real-world tasks. Here's a quick comparison of where these are most effectively applied:
Model | Use Case Scenarios |
Claude 4 Opus | Legal, compliance, data analysis, long-form writing, advanced coding |
Gemini 2.5 Pro | Research, education, multimodal tasks, tutoring, data synthesis |
OpenAI o3 | Productivity, support, creative writing, UI prototyping, math, coding |
Safety, Ethics, and Compliance
Claude Opus 4
Claude Opus 4 is the first Anthropic model launched with AI Safety Level 3 (ASL-3) protections, targeting misuse related to chemical, biological, radiological, and nuclear (CBRN) weapons. While it’s not confirmed that Opus 4 meets the ASL-3 capability threshold, Anthropic couldn’t fully rule it out, prompting a precautionary deployment. The measures focus on blocking extended CBRN workflows without broadly limiting access to general information.
ASL-3 also adds stronger security controls to prevent model weight theft, including two-party access protocols and bandwidth limits to detect exfiltration. These are designed to counter sophisticated threats.
Gemini 2.5 Pro
Gemini 2.5 Pro was developed with extensive oversight from Google’s safety and responsibility teams, following the company’s AI Principles. Safety evaluations included red teaming, automated testing, and independent assurance reviews.
The model is trained to avoid harmful outputs such as hate speech, medical misinformation, and explicit content. Google uses dataset filtering, fine-tuning, safety policies, and product-level mitigations to manage risks.
While Gemini 2.5 Pro showed improvements in areas like cybersecurity and machine learning R&D, it does not meet the thresholds for critical risk capabilities under Google's Frontier Safety Framework. Over-refusals and a sometimes preachy tone remain as noted limitations.
OpenAI o3
OpenAI o3 supports GDPR and CCPA compliance and is covered under a SOC 2 Type 2 report. Its products - ChatGPT Team, Enterprise, Edu, and the API - offer enterprise features like MFA, SAML SSO, SCIM, admin APIs, and audit logs.
These tools give organizations control over access, usage, and security, with role-based permissions, usage dashboards, and granular GPT controls.
OpenAI says it trains models to filter harmful content and reduce bias, using expert testing and user feedback. It also addresses child safety, privacy, deepfake transparency, and election disinformation to manage ethical and safety risks.
Which AI Model Suits Your Needs?
If you need advanced coding and debugging with support for long-context workflows, especially when working on large codebases or research projects, Claude Opus 4 is a good choice.
Gemini 2.5 Pro works well if you need to handle multimodal inputs like text, images, audio, and video with very long context windows, ideal for research or multimedia projects.
OpenAI o3 fits tool-based workflows, strong reasoning, and enterprise needs like data analysis and content creation. When deciding, consider how much context you need, whether you require multimodal input or tool support, and how cost affects your choice.
If you’re working with these AI models and need guidance on integration or custom AI development, you can contact our experts to help with technical details and practical solutions.
Good Luck!
Frequently Asked Questions
Which model performs best in coding tasks?
Claude Opus 4 leads in advanced coding and debugging, especially with large codebases.