Grok 4 vs. Claude Opus 4 vs. Gemini 2.5 Pro vs. OpenAI o3: The Ultimate 2025 AI Showdown

Grok 4 just dropped, and there’s already talk about whether it’s the smartest model out there. But the real question is how it performs where it matters, especially compared to Claude Opus 4, Gemini 2.5 Pro, and OpenAI o3.

These models differ in meaningful ways - reasoning, speed, context handling, and cost structure. One might be better for API-heavy workloads, another for long-form generation, another for tool use.

This article breaks down how each model performs across reasoning, coding, real-time knowledge, multimodal capabilities, integration, and pricing, so you can evaluate which one fits your product or organization.

TL;DR: Claude Opus 4 is best for complex reasoning. Grok 4 is strong on code and has the lowest API cost ($3 input / $15 out per million tokens). Gemini 2.5 Pro is fast and fits well with Google tools. o3 is stable and easy to access, but lighter overall. No perfect model- just depends on what you need and how you work.

Model Comparison Overview

Property	Claude Opus 4	Grok 4	Gemini 2.5 Pro	o3 (OpenAI)
Context	200K tokens	256K tokens	1M in / 65K out	200K tokens
Max Output	32K tokens	256K tokens	65K tokens	100K tokens
Input Price	$15/M	$3–6/M	$1.25–2.50/M	$2/M
Output Price	$75/M	$15–30/M	$10–15/M	$8/M
Latency	~3.15 sec	~9.5 sec	~2.52 sec	~9.55 sec
Throughput	~39.27 tokens/sec	~61.5 tokens/sec	~83.73 tokens/sec	~37.55 tokens/sec

1. Grok 4 (xAI)

Property	Grok 4 (xAI)
Context Length	256K tokens
Max Output	256K tokens
Input Pricing	$3-$6 per million tokens
Output Pricing	$15$30 per million tokens
Latency	~9.5 seconds
Throughput	~61.5 tokens/sec
Uptime	100% (as of July 24, 2025)
Data Policy	No prompt training Logs kept for 30 days
Moderation	Handled by developer
Generation Params	Supports temperature, top_p, tools, logprobs, and more

Grok 4 is xAI’s latest large language model, trained using reinforcement learning at a scale that’s unusual even among top-tier models. Instead of just predicting the next token, Grok 4 learns behaviors through RLHF-like methods during pretraining - using a 200,000-GPU setup known as “Colossus.” 

This lets the model develop better planning and decision-making skills, especially when paired with tool use.

Integrated Tools and Web Access

Unlike models that route requests to external tools, Grok 4 includes native support for tools like a code interpreter, web browser, and real-time X (Twitter) search. 

The model can decide on its own when to invoke these tools during inference. This improves its ability to handle real-time questions, debug live code, or reason about current events without relying solely on training data.

Grok 4 Heavy Variant

The “Heavy” version of Grok 4 runs parallel reasoning paths and selects the most confident output at the end. This variant currently ranks at or near the top of academic benchmarks like ARC-AGI V2 and MMLU (Humanity’s Last Exam), with >50% accuracy on several hard tests. 

It’s particularly strong at multistep reasoning and advanced math, and it beats Claude Opus, Gemini 2.5 Pro, and GPT-4 Turbo in several competitive coding benchmarks.

Context, Input, and Interfaces

Grok supports a 256K token context window and can take in multimodal input, including images and video through the camera when used in voice mode. 

It’s available via the xAI API and integrated into X’s Premium+ subscription through the “Grok” assistant. Enterprise support (SOC 2, GDPR, etc.) is rolling out.

2. Claude Opus 4 (Anthropic)

Property	Claude Opus 4
Context Length	200K tokens
Max Output	32K tokens
Input Pricing	$15 per million tokens
Output Pricing	$75 per million tokens
Latency	3.15 s
Throughput	39.27 tokens/sec
Uptime	98.91% (as of Jul 25, 2025 – 5 AM)
Supported Params	Max Tokens, Temperature, Stop, Tools, Tool Choice
Data Policy	No prompt training Logs kept for 30 days
Moderation	Managed by OpenRouter
Anonymity Notes	Requires user IDs

Claude Opus 4 is Anthropic’s top-tier language model, designed for demanding use cases like advanced coding, long-horizon agent workflows, and research-intensive tasks. It builds on a hybrid reasoning architecture that balances speed and depth, capable of both fast completions and extended step-by-step thinking.

The model is particularly effective in multi-agent systems and background task handling. Developers can run Claude Code asynchronously to manage long-running operations, enabling more complex automation and orchestration. It excels on benchmarks like SWE-bench, MMLU, and TAU-bench, and it's one of the few models built with structured agentic reasoning in mind.

Background Task Support

One key feature is the ability to delegate long-running coding jobs in the background. This helps teams offload large-scale code refactoring or research tasks without blocking the session or needing constant supervision.

Hybrid Reasoning and Cost Controls

Claude Opus 4 offers real-time reasoning or extended “thinking” modes. Developers can adjust Claude’s thinking budget depending on the task’s complexity or desired cost-performance balance  -  a rare feature among frontier models.

Availability

It’s available via the Anthropic API, Amazon Bedrock, and Google Vertex AI, and is integrated into Claude’s web and desktop apps. Enterprise features include SOC 2 support, SSO, SCIM, and advanced permission controls.

3. Gemini 2.5 Pro (Google)

Feature	Details (Google Vertex)
Context Window	1,048,576 tokens in / 65,535 tokens out
Input Pricing	$1.25-$2.50 per million tokens
Output Pricing	$10-$15 per million tokens
Latency	2.52 seconds
Throughput	83.73 tokens per second
Uptime	99.14% (as of July 23, 2025 – 1 PM)
Supported Params	Max Tokens, Temperature, Top P, Stop, Tool Use, Format
Structured Output	Supported
Data Policy	No prompt training, logs retained for 1 day
Moderation	Handled by the developer

Gemini 2.5 Pro is Google’s top-tier model as of mid-2025. It accepts multimodal inputs including text, code, images, audio, PDFs, and video frames. The model supports a 1 million token input window and can return up to 65K tokens in a single response.

It performs well on complex reasoning tasks, math, and code generation. Benchmarks show 75.6% on LiveCodeBench v5, 83.0% on AIME 2025 (math), and 63.2% on SWE-bench (agentic coding). It also supports settings like temperature (0-2), Top-P (0-1), Top-K (up to 64), and candidate count (1-8).

The model accepts prompts up to 7MB in size and supports up to 3,000 images per request. It offers tool use and structured output, but external orchestration is required.

Latency averages ~3.1 seconds, with throughput near 39 TPS. Availability is over 98% as of July 2025. Gemini is accessible via Vertex AI or Gemini Advanced. It doesn’t support fine-tuning. Prompt logs are retained for 30 days, and moderation is handled by OpenRouter. User IDs are required for access.

4. OpenAI o3

Property	Details
Context Length	200,000 tokens
Max Output Tokens	100,000 tokens
Structured Output	Supported (100%)
Pricing	$2 /M input - $8 /M output
Latency	~9.55s
Throughput	~37.55 tokens/sec
Access	ChatGPT (Plus, Pro, Team), API
Moderation	Managed by OpenRouter
Prompt Logging	Retained (duration unknown)
User Identity	Required
Knowledge Cutoff	June 1, 2024

OpenAI o3 is a reasoning-first model released in April 2025. It supports text and image input and can use tools in ChatGPT like Python, web browsing, file uploads, and image generation.

It performs well on complex reasoning tasks across math, code, and science. It scores 69.1% on SWE-bench (no scaffolding), 2706 Elo in competitive programming, 88.9% on AIME 2025, 83.3% on GPQA Diamond, 82.9% on MMMU, and 86.8% on MathVista.

It’s well-suited for analytical tasks that involve step-by-step logic, hypothesis testing, or working across text and images.

The model supports a 200,000-token context window and can generate up to 100,000 tokens in a single output. It’s commonly used for programming help, data analysis, technical writing, and instruction-following tasks. It also supports reasoning over visual inputs like diagrams or charts.

OpenAI o3 is available in ChatGPT (Plus, Pro, Team) and via API. A pro variant with more tool capabilities is expected.

Core Capabilities and Differentiators

1. Reasoning and Planning

Claude Opus 4 is the most consistent at structured reasoning. It handles long, multi-step problems reliably, even when they involve abstract logic or conflicting information. o3 is close - it’s strong across logic, math, and science, and holds up well under complex reasoning tasks.

Grok 4 is strong on open-ended reasoning and math-heavy tasks, but less stable when instructions are vague. Gemini 2.5 is quick and often correct in common scenarios, but tends to miss edge cases and doesn’t reason as deeply.

2. Tool Use and Autonomy

Grok 4 leads in autonomous tool use. It knows when to call tools and handles multi-step chains well. o3 supports tool use but depends on external setup and access; it's less autonomous out of the box. 

Claude uses tools conservatively but predictably. Gemini also supports tools but needs scaffolding to behave reliably - it won’t take action unless guided.

3. Coding and Agent Behavior

Claude produces clean, maintainable code and handles instruction-heavy automation well. OpenAI o3 is strong at code reasoning, particularly when tasks span across text, code, and visuals. It's good for writing utilities, analyzing scripts, and debugging. 

Grok is quick at solving algorithmic problems but can be brittle. Gemini generates readable code when guided, but results are mixed without close supervision.

4. Context and Recall

o3 supports a 200K token window and is consistent at tracking information across long prompts. Claude still performs best in maintaining memory over multi-turn interactions. 

Grok holds short-term context well but sometimes overweighs recent input. Gemini has the largest theoretical context size but often struggles with relevance unless prompted carefully.

4. Output Stability

Claude is the most predictable in structured outputs and instruction-following. o3 is stable across formats and good at function calling and structured completions. 

Grok can go off-track occasionally but tends to answer directly. Gemini outputs are fast but less controlled - sometimes helpful, sometimes vague.

Performance Benchmarks

The following benchmark results are reported by each model provider based on their own test setups.

Claude Opus 4

Task	Performance
Agentic coding (SWE-bench Verified)	72.5% / 79.4% (with test-time parallelism)
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% (with tool use)

Anthropic's benchmarks show that Claude Opus 4 performs well on complex reasoning, agentic coding, and structured tool use. It benefits from techniques like parallel decoding and chain-of-thought prompting, with strong results on SWE-bench and AIME.

Grok 4 

Task	Performance
Real-world tasks (MMLU+Python+Internet)	38.6% (Grok 4) / 44.4% (Heavy)
Pass@1 Accuracy (text-only subset)	26.9% (no tool) / 50.7% (with tools)
Graduate-level reasoning (GPQA)	87.5% (Grok 4) / 88.4% (Heavy)
Competitive coding (LiveCodeBench)	79.0% (Grok 4) / 79.4% (Heavy)
Math proofs (USAMO 2025)	37.5% (Grok 4) / 61.9% (Heavy)
Competitive math (HMMT 2025)	90.0% (Grok 4) / 96.7% (Heavy)
Competition math (AIME 2025)	91.7% (Grok 4) / 100% (Heavy)
Abstraction & reasoning (ARC-AGI-2)	15.9%

xAI’s benchmark results show that Grok 4 performs well on math and reasoning tasks. Tool use - especially Python and internet access - adds noticeable gains in areas like competitive coding, scientific QA, and open-ended problem solving.

Gemini 2.5 Pro 

Task	Performance
LiveCodeBench v5 (Code Generation)	75.6%
LiveCodeBench v6 (Deep Think)	80.4%
Aider Polyglot - Code Editing (Whole/Diff)	76.5% / 72.7%
SWE-bench Verified (Agentic Coding)	63.2%
AIME 2025 (Math)	83.0%
USAMO 2025 (Math-Deep Think)	49.4%
GPQA (Science)	83.0%
Humanity’s Last Exam (Reasoning)	17.8%
MRCR (128k context recall)	93.0%
Multimodality (Deep Think variant)	84.0%

Benchmarks reported by Google DeepMind show that Gemini 2.5 Pro performs well in math, science, and code-related tasks. It shows improvements in reasoning and tool use on newer evaluations like LiveCodeBench v6 and SWE-bench. 

Long-context recall is strong. Performance on open-ended reasoning tasks like Humanity’s Last Exam remains lower.

OpenAI o3

Task / Benchmark	o3 (Full)	o3-mini
SWE-Bench Verified (software engineering)	69.1%	48.9%
Codeforces ELO (competitive coding)	2706	2073
AIME 2024 (math)	91.6%	87.3%
AIME 2025 (math)	88.9%	86.5%
GPQA Diamond (PhD-level science)	83.3%	77.0%
Humanity’s Last Exam (reasoning)	42.9% (with tools)	13.4%
	20.3% (no tools)	-
SWE-Lancer (freelance coding)	$65,250 earned	$17,375 earned
Scale MultiChallenge (multi-turn tasks)	56.5%	39.9%
BrowseComp (agentic browsing)	49.7% (with tools)	-
Aider Polyglot (code editing)	81.3% whole / 79.6% diff	66.7% whole / 60.4% diff
MathVista (visual math)	86.8%	-
MMMU (college-level visual tasks)	82.9%	-
CharXiv-Reasoning (science figures)	78.6%	-

o3 delivers strong performance across engineering, math, and reasoning tasks - especially when tools like Python and browsing are enabled, as by OpenAI. 

It improves significantly over o3-mini on benchmarks like SWE-Bench, freelance coding tasks, and code editing. In agentic and multi-step reasoning, tool use increases effectiveness substantially.

Context Window and Long-Context Recall

Model	Context Window	Max Output	Recall Performance (notes)
Gemini 2.5 Pro	1M tokens in	65K tokens out	93% on MRCR-128K; excellent at long-context QA
Grok 4	256K tokens	256K tokens	Good short-term recall; prioritizes recent input
Claude Opus 4	200K tokens	32K tokens	Best at tracking logic over long, multi-turn flows
OpenAI o3	200K tokens	100K tokens	Reliable recall + consistent long-chain reasoning

Even though Gemini supports the largest window (1M tokens), Claude handles long, structured reasoning more reliably, especially over multiple turns. o3 offers a good balance: strong recall, high output length, and consistent multi-step reasoning. 

Grok uses a recency-focused memory strategy, which works well in short interactions but limits deeper recall. Each model’s long-context capability shows a tradeoff between size, attention strategy, and latency.

Ecosystem, Tool Use, and Integration

All these models offer API access and tool support, but differ in how they handle integration, extensibility, and developer workflow.

Grok 4 is available through a public API that supports native tool use, real-time data retrieval, and context windows up to 256K tokens - useful for working with large documents or live content. It connects directly to the X platform and is designed around streaming input and lightweight computation. The API is accessible via xAI’s developer site.

Claude Opus 4 is available through Anthropic’s own API as well as Amazon Bedrock and Google Cloud. It supports tool use for web search, file processing, and planning tasks across documents and code. It’s often used in environments where safety, compliance, and traceability are important. You can toggle between faster or more detailed response modes depending on the task.

Gemini 2.5 Pro is built into Google’s product stack, with direct access to Docs, Sheets, Gmail, Vertex AI, BigQuery, and Firebase. It supports text, images, audio, and video, making it suitable for teams working inside Google Cloud or Workspace. The API enables full-stack workflows - data in, model processing, output into applications - with minimal setup if you're already using Google’s tools.

OpenAI o3 offers broad integration support across development and business platforms. Its API connects to tools like the Code Interpreter, Assistants API, and persistent memory. You can extend it using third-party plugins from the GPT Store or bring it into existing systems through platform SDKs. 

It supports a range of use cases from quick prototyping to production-grade assistants - without requiring deep configuration.

Pricing, Tiers, and Accessibility

Claude Opus 4

Claude Opus is available on the Anthropic web and mobile apps under paid plans (Pro, Max, Team, Enterprise), and through API platforms including Anthropic API, Amazon Bedrock, and Google Cloud Vertex AI.

App Plans

Plan	Price
Free	$0
Pro	$20/month ($200/year)
Max	From $100/month
Team	$30/user/month ($25 with annual billing)
Enterprise	Custom

API Pricing (per 1M tokens)

Category	Price
Input	$15.00
Output	$75.00
Prompt Caching (Write)	$18.75
Prompt Caching (Read)	$1.50

• Prompt caching: Up to 90% savings

• Batch processing: Up to 50% savings

• Context window: 200K tokens

Gemini 2.5 Pro

Gemini Pro is free with limited access on the Gemini app. Full access is included in the $19.99/month Gemini Advanced plan via Google One AI Premium. API access is available through Google Cloud’s Vertex AI with a billing account.

App Access

Plan	Price
Gemini Advanced	$19.99/month

API Pricing (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	$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

o3 is included in ChatGPT subscriptions and available via API.

ChatGPT Plans

Plan	Price
Plus	$20/month
Pro	$200/month
Team	$25/user/month (billed annually)
	$30/user/month (monthly billing)
Enterprise	Custom

API Pricing (per 1M tokens)

Token Type	Price
Input	$10.00
Cached Input	$2.50
Output	$40.00

Grok 4

Grok 4 is available through xAI’s platform under SuperGrok plans. Grok 3 access is free for X users.

Plan	Price/M	Includes
SuperGrok	$30	Grok 4
SuperGrok Heavy	$300	Grok 4 + Grok 4 Heavy

API Pricing (per 1M tokens)

Type	Price
Input Tokens	$3.00 / 1M tokens
Cached Input Tokens	$0.75 / 1M tokens
Output Tokens	$15.00 / 1M tokens
Live Search	$25.00 / 1K sources

Context Window: 256K tokens 

Safety, Alignment, and Ethical Stance

Claude Opus 4 is deployed with AI Safety Level 3 protections targeting high-risk misuse, especially around CBRN threats. While Anthropic hasn't confirmed Opus 4 reaches ASL-3 capabilities, it introduced controls like two-party access and bandwidth monitoring as precautions.

Gemini 2.5 Pro was developed under Google’s AI Principles and evaluated through red teaming, automated tests, and independent reviews. It avoids harmful content using dataset filtering, policy alignment, and product-level mitigations. While it improved in sensitive domains like cybersecurity, it does not meet Google's Frontier Safety Framework thresholds for critical risk capability.

OpenAI o3 supports enterprise-grade security controls and regulatory compliance, including SOC 2 Type 2, GDPR, and CCPA. Features like audit logs, SAML SSO, and admin APIs provide control over access and usage. 

OpenAI also uses expert testing and feedback to reduce bias, filter harmful content, and address risks around misinformation and safety.

Grok 4 includes SOC 2 Type 2, GDPR, and CCPA compliance for enterprise deployments. It uses real-time search tools and native integrations to support accurate outputs while meeting baseline security standards.

Getting Started

If you're choosing between Grok 4, Claude Opus 4, Gemini 2.5 Pro, and o3, the right option depends on what matters most to you - accuracy, speed, cost, or availability. 

Claude Opus 4 is strong on reasoning and consistent across tasks. Gemini 2.5 Pro is fast and fits well inside Google’s ecosystem. Grok 4 performs well in code but isn’t as cheap. o3 is stable and accessible, though lighter overall.

Try each on your actual workflows. That’s the only way to see what fits. You can also connect with our experts to explore what’s best for your use case.

Frequently Asked Questions

Which model is best for coding and development?

Claude Opus and Grok 4 both perform well on code-heavy tasks, especially when working with longer contexts. Grok 4 has an edge in certain benchmarks, but Claude is more consistent across different types of development work. o3 is good for smaller tasks. Gemini performs fine but isn’t as strong in code generation.

What's the main difference in their safety philosophies?

Claude Opus 4 takes a more cautious and structured approach, often avoiding risky or speculative output. o3 and Gemini balance safety with usability. Grok is less filtered in tone and responses, closer to open-domain output.

If I need the most up-to-date information, which model should I use?

All four support web access, but implementation varies. Gemini integrates search grounding through Google. Grok has built-in live search via X. Claude and ChatGPT also offer browsing. For real-time or source-grounded results, Claude or Gemini generally performs more reliably.

How do the costs compare for a small business or individual developer?

o3 and Gemini offer lower entry points with $20/month plans. Claude’s Pro plan is $20/month ($17 with annual billing), but its API pricing is much higher-$15 per million input tokens and $75 per million output tokens. Grok has cheaper API rates ($3 input, $15 output), though its premium app plan goes up to $300/month. Gemini’s API is the lowest-cost option overall, but it’s only available through Google Cloud billing. For budget-conscious users, o3 or Grok API may offer better value depending on usage.

Which model is best for analyzing large documents or datasets?

Claude Opus and Grok 4 support longer context windows (200K-256K tokens), making them better suited for large documents. Claude tends to be more structured and reliable for summarizing or extracting from complex inputs. o3 is stable but lighter. Gemini supports large contexts but works best when grounded within its own ecosystem.