In this article
Right now, the AI chatbot landscape is buzzing. Several models have recently released powerful updates: OpenAI’s released GPT-5, Claude — Opus 4.1, Grok moved to the new version, and Gemini has been deveoping their 2.5 model.
I’ve had a closer look at each of the updates and put ChatGPT, Grok, Claude, and Gemini to the test. In this article, I’ll break down where each shines—and where they stumble. If you work in IT, sales or marketing, this is a must-read.
Grok 4: Overview
Grok, the AI system from xAI, has recently moved from version 3 to version 4, with an additional variant called Grok 4 Heavy. The main changes come from its training process. Grok 4 was trained on Colossus, xAI’s 200,000-GPU cluster, using reinforcement learning at pretraining scale. Training efficiency improved six-fold compared to Grok 3, according to the company’s website, and the dataset expanded beyond math and coding into a broader range of verifiable domains.
Source: grok.com
A key addition is tool use. Grok 4 can decide when to run a code interpreter, when to search the web, and when to enter a dedicated research mode. The goal is to handle questions that require real-time or in-depth information. In these cases, it generates its search queries and explores results until it can answer.
Grok 4 Heavy adds parallel reasoning, allowing the model to consider multiple hypotheses at once. This version scored 50% on Humanity’s Last Exam, a 2,500-question benchmark created by the Center for AI Safety and Scale AI. The test is designed to cover a broad range of academic subjects, but like most benchmarks, it does not guarantee equivalent performance in real-world tasks.
The update also introduces visual perception. Users can point a camera at a scene and get real-time analysis within voice chat. Context windows have been expanded: 128,000 tokens for Grok 4, 256,000 for Grok 4 Heavy.
Pricing is split into two subscriptions. SuperGrok is $30 per month and includes Grok 4, Grok 3, visual and voice features, and the smaller context window. SuperGrok Heavy is $300 per month, with early access to new features and the larger context window.
Source: reddit.com
Independent evaluations place Grok 4 near the top of performance rankings, just behind GPT-5 according to Artificial Analysis. However, community feedback is mixed. Some users note limited coding ability and inconsistent writing quality. Others have raised concerns about political bias and the influence of Musk’s style on the model’s tone.
For integration platforms, Grok 4 offers reasoning upgrades, tool use, and multi-modal input. Whether these translate into reliable automation depends on the specific workflows tested.
Features
- Deep Search. DeepSearch enables Grok to iteratively search the web and analyze information, delivering well-researched responses for queries requiring external data.
- Deeper Search. An even more detailed research.
- Think. Think Mode allows Grok to deliberate longer before responding, enhancing the depth and accuracy of answers for complex queries.
- Voice mode. Exclusive to the Grok iOS and Android apps, this feature allows users to interact with Grok via voice input, making it more accessible for on-the-go use.
- Edit image. Allows Grok to perceive and edit uploaded images.
- Fresh news. Gives a summary of the recent news.
Best for
Grok can be used:
- Social media writing and research. Special mode for search on X can be helpful for anyone who actively works with content. Being trained on X data, it can also be used for generating text.
- Research. Grok has several modes, such as DeepSearch and Think Mode, which make it helpful for academic, professional, or personal research.
- Customer support. Grok has potential for a conversational style that sounds natural and engaging.
Weaknesses
Despite its strengths, Grok has notable limitations:
- Elon Musk’s Influence: Grok’s responses sometimes reflect the personality and viewpoints of xAI’s founder, Elon Musk. This can manifest in repeating Musk’s public stances and lead to misinformation relating to historical facts and controversial topics.
- Limited multimodal capabilities. Users report that its coding skills are weaker than those of other models. For image generation, you should also use specialized neural networks.
- Pricing. To use SuperGrok and enjoy higher quotas, you need to pay from $30 to $300 which is higher than the average price on the market.
- Data privacy. Conversations with Grok are not indexed publicly like some competitors, but users should remain cautious about sharing sensitive information, as data handling practices are subject to xAI’s privacy policies.
Speed
Grok 3 is generally fast, with response times comparable to leading LLMs. However, high demand or complex queries (e.g., those requiring DeepSearch) can introduce slight delays. Think Mode, by design, takes longer to deliver responses, prioritizing depth over speed. Web searches are typically efficient but may vary based on server load or query complexity.
Accuracy
Grok strives for accuracy by leveraging real-time web data and a robust training dataset. Its DeepSearch mode enhances reliability by cross-referencing multiple sources. However, inaccuracies can occur, particularly when handling niche topics or unverified online content. For example, Grok may occasionally provide outdated or speculative information if web sources are unclear. Users are advised to verify critical information independently.
Trustworthiness
As mentioned above, Grok’s alignment with Musk’s worldview can lead to responses that feel opinionated or skewed, particularly on politically charged topics. This contrasts with models like ChatGPT, which may prioritize neutrality but risk being overly diplomatic.
xAI implements filters to manage sensitive content, but Grok’s contrarian nature may occasionally produce provocative or polarizing responses, requiring careful user interpretation.
ChatGPT-5: Overview
GPT-5 is OpenAI’s current flagship language model, released in August 2025. It consolidates and replaces earlier models such as GPT-4.1 and GPT-4o, operating as a unified system with three components: a standard model for most queries, a deeper reasoning variant (GPT-5 Thinking) for complex problems, and a real-time router that selects which to use based on the conversation. The routing design means not every request triggers the heavier reasoning process, balancing speed, cost, and output consistency.
The model is available to all ChatGPT users. Plus subscribers receive higher usage limits, while Pro subscribers get unlimited access and GPT-5 Pro, a version with extended reasoning. Team, Enterprise, and Education plans also provide high limits for organizational use.
OpenAI has targeted three main areas for improvement: writing, coding, and health. In writing tasks, GPT-5 is designed to help structure and refine ideas into coherent text, with adjustments to reduce excessive agreement and add more deliberate follow-ups. In coding, it shows particular gains in generating complex front-end projects and debugging large repositories. For health, GPT-5 is built to flag possible concerns, ask clarifying questions, and provide information aligned with physician-defined criteria. On HealthBench Hard, it scores 46.2%, the highest among OpenAI models to date.
Performance gains extend to multiple benchmarks. In math, GPT-5 scored 94.6% on AIME 2025 without tools. In coding, it achieved 74.9% on SWE-bench Verified and 88% on Aider Polyglot. For multimodal tasks, which include image, video, spatial, and scientific reasoning, it reached 84.2% on MMMU. Compared to the o3 model, GPT-5 Thinking performs better while producing 50–80% fewer output tokens.
To reduce errors and misleading outputs, GPT-5 incorporates measures to lower hallucination rates, improve adherence to instructions, and implement “safe completions” for higher-risk queries. Evaluations using LongFact and FActScore benchmarks show improvements in factual accuracy for open-ended prompts.
The system supports multimodal input — text, images, and voice — with a 256,000-token context window. Built-in tools include web browsing, voice interaction, and calendar access. Multiple model sizes (including mini and nano) are available for lower latency and cost-sensitive use cases.
Source: openai.com
GPT-5 remains a transformer-based generative model trained to predict the next word in sequence, but with expanded reasoning, improved safety controls, and a broader scope across real-world tasks. Its benchmark results set new highs for OpenAI, though, as with all evaluation metrics, performance in controlled tests may not fully reflect outcomes in production use.
Features
- Deep Research. Runs iterative web searches and synthesize findings into a single, sourced reply for queries that need external data.
- Think longer. Gives the model extra deliberation time for harder problems.
- Canvas. Canvas is an in-app workspace for editing texts. It keeps prompts and edits together so you can shape drafts, move elements, and re-run instructions without losing context.
- Image generation. Image generation turns text prompts into images and offers basic image editing and variations from user-supplied inputs.
- Study and education. It’s aimed at teaching and clarification rather than completing graded work for users.
- Web search. The web search tool performs live lookups to fetch current information.
- Vision. Vision allows the model to interpret images and other visual inputs. Upload a photo or screenshot and the model can describe it, extract text or data, answer questions about the scene, or perform basic visual reasoning.
- Voice input. Voice input adds speech recognition and spoken responses to the chat experience.
Best for
As a content marketer, I spend a lot of time trying out different AI models for various types of content. ChatGPT is the best tool on the market for writing texts, emails, and social media posts. The texts feel more natural, and the model is also relatively successful at adjusting style. And all this even in the free version.
You can also build ChatGPT automations for customer service and customer support, as the answers generated by this model will sound less robotic.
Weaknesses
ChatGPT might not be the go-to tool for debugging simple code or writing it from scratch. If you use it to check and improve your code, it provides valuable feedback that can be helpful for learning.
However, practice shows that it also often misses mistakes or glitches in the code or introduces them while fixing another problem.
Speed
ChatGPT is one of the fastest models on the market. However, due to high demand, it may sometimes lag. Generating images can also take anywhere from a minute to up to 10 minutes, depending on demand.
Accuracy
ChatGPT is generally accurate in its answers. It can also access the web to search for relevant information.
But fact-checking is still necessary when you’re searching for information. For instance, when I requested a reading list tailored to my interests, half of the books listed didn’t exist.
Trustworthiness
GPT-5’s responses are about 45% less likely to contain a factual error than GPT-4o. In Thinking mode, GPT-5 is roughly 80% less likely to produce a factual error than OpenAI’s o3. When reasoning, GPT-5 more reliably recognizes tasks it cannot complete and communicates those limits clearly. In evaluations using impossible coding problems and prompts with missing multimodal inputs, GPT-5 (with Thinking) showed lower deception rates than o3.
OpenAI applies safety filters and other controls, but there are important caveats. Search engines can index shared ChatGPT conversations; although shared content is anonymized, it may still be publicly discoverable. Many users also report that ChatGPT is overly agreeable, frequently giving positive feedback even when ideas are flawed or incorrect — a behavior that raises ethical concerns for use in consulting, education, or psychotherapy.
Claude 4.1 Opus: Overview
Claude Opus 4.1 is Anthropic’s most advanced publicly available language model as of August 2025. It is available to paid Claude users, through Claude Code, and via the API, Amazon Bedrock, and Google Cloud’s Vertex AI. Pricing remains the same as Opus 4.
The model is built on a transformer-based architecture and trained on licensed data, publicly available sources, and Anthropic’s reinforcement learning methods. It supports up to 200,000 input tokens and 32,000 output tokens, enabling it to process large codebases, full-length documents, or extensive datasets without losing context. Opus 4.1 introduces “hybrid reasoning,” which allows it to respond quickly to straightforward queries or take more time for multi-step, complex tasks. This approach is designed to improve planning, tool use, and performance in autonomous workflows.
Coding is a primary focus of the update. Claude scores 74.5% on SWE-bench Verified, with marked improvements in multi-file refactoring and debugging in large repositories. It identifies necessary fixes precisely while avoiding unrelated code changes. These capabilities make it more effective for advanced software maintenance and collaborative development.
Beyond coding, Opus 4.1 is positioned for AI agent applications, with strong performance on TAU-bench and other long-horizon task benchmarks. It can synthesize insights from large sets of structured and unstructured data, such as patent databases or academic research, and generates more structured, natural writing than previous versions.
Anthropic reports a 98.76% compliance rate in refusing policy-violating requests, an increase over Opus 4. Safety evaluations found no significant regressions in political bias, discriminatory behavior, or child safety responses. The model is rated at AI Safety Level 3 (ASL-3), reflecting its focus on reducing harmful outputs while maintaining responsiveness.
Features
Claude doesn’t have a variety of modes, like other tools in this article. But it has Extended Thinking, which is similar to Deep Research. It encourages the model to think longer to solve complex problems.
It also allows users to use Claude Artifacts, which can be powerful if you're building something or working with data.
Source: claude.ai
The switches in the interface allow you to switch between different conversation styles, such as normal, concise, or explanatory. It also allows you to perform a search not just on the web, but in your Google Drive, Gmail, Calendar, or GitHub. This can make it a helpful tool for IT professionals.
Best for
Claude Opus 4.1 is particularly well-suited for:
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Software development. Especially large-scale refactoring, debugging, and automation of coding workflows.
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Research and analysis. Handling long academic papers, datasets, or legal documents in a single session.
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Data-heavy projects. Summarizing and analyzing complex, multi-part datasets or large archives of information.
Weaknesses
Despite its strengths, Opus 4.1 has some limitations:
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No image generation. Focuses on text and code, without built-in visual creation tools.
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Slower extended thinking. The long reasoning mode can introduce delays for large or complex queries.
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Limited free access. Full capabilities are available only to paid Claude Pro, Max, Team, and Enterprise users, or via API.
Speed
Comparable to other models.
Accuracy
Opus 4.1 demonstrates state-of-the-art accuracy in coding benchmarks. It also enjoys the support of the community, many claiming it to be the best coding assistant. Anthropic says Claude Opus 4.1 improves software engineering accuracy to 74.5%.
Trustworthiness
Anthropic emphasizes safety and reliability, with improved refusal systems and bias checks. While designed to be neutral, users should remain aware that no AI model is completely free from bias or occasional factual errors, and independent verification is recommended for critical use cases.
Gemini: Overview
Source: developers.googleblog.com
Gemini is a multimodal AI system developed by Google DeepMind, succeeding earlier models such as LaMDA and PaLM 2. It is available in multiple variants tailored to different performance and cost requirements. As of mid-2025, the leading public versions are Gemini 2.5 Pro and Gemini 2.5 Flash, both featuring a 1-million-token context window. This capacity allows the models to handle the equivalent of about an hour of silent video, 11 hours of audio, or roughly 700,000 words in one session.
A new variant, Gemini 2.5 Flash-Lite, is in preview. It is designed as a cost-effective upgrade within the 2.5 family, offering the lowest latency and cost among current models.
Gemini functions as both a standalone chatbot and as an integrated assistant across Google products. It is built into Workspace tools such as Gmail, Docs, and Sheets, where it can draft, summarize, and generate content. On supported Android devices, Gemini replaces Google Assistant as the default AI interface. After connecting Google Workspace, users can schedule tasks directly within the Gemini app by simply entering a date and time.
The model is multimodal, capable of processing and generating text, images, audio, and video, which allows you to automate content creation with Gemini.
Features
- Deep Research. Runs iterative web searches and compiles results into a synthesized, source-backed answer for queries needing external information.
- Canvas. Provides an interactive workspace where you can develop, edit, and organize text or visual content within a persistent project view.
- Image. Generates images with Imagen from text prompts and can make variations or edits to existing visuals.
- Guided Learning. Offers structured, step-by-step explanations, exercises, and feedback to support learning and skill development.
- Voice input. Lets you interact with the model using spoken prompts and receive responses by voice or text.
Best for
Gemini's strength lies in its deep integration with the Google ecosystem. For users who are already deeply entrenched in Google's products, Gemini can be a powerful productivity partner. It excels at tasks that require real-time information and complex reasoning, and its multimodal capabilities make it an excellent tool for deep research and data analysis from various sources, including text and video. It can generate code from scratch and is particularly helpful for Android development with its integration into Android Studio.
Weaknesses
Users have reported issues with it providing inaccurate information, such as creating a reading list with books that don't exist. There have also been concerns about bias in its outputs, particularly in image generation, which led Google to pause the feature temporarily.
Gemini may also have a longer response time for simple requests compared to other models. Additionally, its reliance on and integration with Google's ecosystem can be a limitation for users who prefer different platforms, as it has limited third-party integrations.
Speed
Gemini is generally fast and efficient, but its performance can vary. Response times may be longer for simple tasks, and the generation of images and other content can be subject to delays, especially during periods of high demand.
Accuracy
Gemini is generally accurate and can access the web to provide up-to-date information. It is designed to provide multiple perspectives on subjective topics and includes a "double check" feature that uses Google Search to help users assess the accuracy of its responses. However, fact-checking is still necessary, as Gemini can still produce inaccuracies.
Trustworthiness
Gemini's trustworthiness has been a subject of discussion, particularly concerning privacy and data usage. Users' interactions with the AI can be used for training, and while there are options to opt out, this is a consideration for those with privacy concerns.
Summing up
The newest AI models—GPT-5, Grok 4, Claude Opus 4.1, and Gemini 2.5 show that all the major players are working at making their models more multimodal and more powerful. Yet, each one has its own vibe: ChatGPT remains a state-of-the-art universal model with powerful multimodal capabilities. Gemini works best with other tools from Google's ecosystem. Grok works best for new research and social media marketing, and Clause excels at codings and debugging (at least, in comparion to other models).
Benchmarks show they’re all improving, but how they perform in real life depends on what you need. For businesses and devs, it’s less about who tops the charts and more about which AI fits your workflow, budget, and reliability goals.
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