AI Chatbot Showdown: Grok-3 Emerges as Top Performer in Deep Research and Complex Task Handling

I just tested ChatGPT deep research vs Grok-3 with 5 prompts -- here's the winner

The ability to do deep research and do it well is one feature that separates the best chatbots apart from one another. Up until yesterday (February 25), ChatGPT's o3 deep research model -- optimized for data analysis and web browsing -- was only available to users paying $200 per month for ChatGPT Pro. However, now, ChatGPT Plus users can use the model for $20 per month, the same price that Grok users pay for the Grok-3, xAI's deep research model. I couldn't help but wonder if these two models were similar in more than just price. With five prompts that focused on reasoning and data analysis, I put the two chatbots head-to-head. While both generate deep research responses much faster than other deep research models I've used, there was one clear winner. Here's what happened when I compared the bots. Prompt: "What were the key factors that prevented the 2008 financial crisis from turning into a second Great Depression, and how might history have unfolded differently if those interventions had not occurred?" This prompt tests each of the chatbot's abilities in various ways, including the depth of economic analysis, historical accuracy and ability to construct counterfactual scenarios. ChatGPT's response is significantly more comprehensive, with a structured breakdown of monetary policy, fiscal stimulus, financial sector interventions, global coordination, and historical comparisons to the Great Depression. Grok-3 delivered a concise and engaging response that is easier to read for a general audience. It also correctly identified monetary policy, fiscal stimulus and global coordination as critical factors. But while it touches on the key interventions, Grok-3 lacks the depth and historical rigor of ChatGPT's response. Winner: ChatGPT wins for a far more analytical, structured, evidence-based, and authoritative, making it the clear winner for a deep research comparison. Prompt: "How do current advancements in reinforcement learning, such as DeepMind's AlphaZero and OpenAI's recent breakthroughs, influence the debate on AI alignment and safety?" This prompt tests the chatbots' knowledge of the latest AI research as well as the ability to synthesize complex technical and ethical issues. ChatGPT responded with a detailed breakdown of reinforcement learning advancements and offered real-world examples. It also explored inverse reinforcement learning and raises concerns about scalable oversight. That chatbot referenced DeepMind's publications, OpenAI's work, and academic AI alignment research, adding credibility. Grok-3 gave a high-level level overview of RLHF, AI capabilities and safety concerns. Its sectioned structure made it easy to read, thanks to bullet points and tables. Grok-3 also touched on ethics, sociology and psychology, acknowledging cultural bias in AI alignment. Winner: ChatGPT wins for depth, technical accuracy, and comprehensive safety analysis. The chatbot delivered a superior answer overall, making it the clear winner. Prompt: "What are the latest breakthroughs in quantum biology, and how could they reshape fields like medicine and computing in the next decade?" This prompt tests the cross-disciplinary knowledge (physics, biology, medicine, and computing) of the chatbots and their ability to interpret emerging research. ChatGPT covered three major areas of quantum biology and also provided historical context and the latest research including citations from scientific papers and institutions. It also explained how quantum coherence allows photosynthesis to achieve 95% energy efficiency and discusses quantum tunneling in enzymatic reactions. ChatGPT was extremely thorough, much more so than Grok. Grok-3 provided an easily digestible overview of the latest advancements while highlighting key points such as quantum effects in photosynthesis, quantum dots in medicine, and computing applications. It also mentioned real-world applications and recognized how they apply in various situation. Winner: ChatGPT wins for a deeper, more technical, and well-structured analysis of quantum biology breakthroughs and their implications for medicine and computing. Prompt: "What are the most effective economic policies for managing high inflation while maintaining economic growth, and how do different models (e.g., Keynesian vs. Monetarist) approach this challenge?" This prompt tests each chatbot's understanding of macroeconomic theories, policy effectiveness and real-world case studies. ChatGPT's response explored both demand-side and supply-side strategies. The chatbot delivered a much deeper analysis of historical and modern inflation policies, stronger theoretical comparisons, more nuanced discussions of monetary, fiscal, and supply-side policies, and overall better empirical evidence and citations. Grok-3 delivered a response that lacked historical depth and didn't analyze past inflationary episodes, which weakens its argument. Far too general, the response merely stated that Keynesians favor government intervention while Monetarists emphasize money supply control, without historical context or nuance. Winner: ChatGPT wins for a far more comprehensive, detailed, and well-structured response to the economic policy question. Prompt: "What are the most viable geoengineering solutions to combat climate change, and what are their potential unintended consequences?" This prompt tests the knowledge of climate science, engineering solutions, risk assessment, and ethical considerations. ChatGPT delivered a far more comprehensive, structured, and insightful response on geo-engineering solutions compared to Grok. It also categorized them into two major types. Grok-3 fell short in several places, lacking technical depth. It was focused on DAC and reforestation and ignored many major geoengineering proposals. There was also little scientific or historical context, with no mention of Mount Pinatubo, Harvard studies, or regulatory frameworks. Winner: ChatGPT wins for covering all major geoengineering methods, not just DAC and reforestation with more technical depth and explanation of how each method works. ChatGPT also delivered stronger historical, scientific, and governance context. In this battle, ChatGPT emerged as the clear winner, delivering a far more comprehensive, structured and insightful analysis nearly every time. While Grok provided clear and accurate answers, they often just brushed the topic's surface, providing more of an overview. These prompts were obviously very scientific and probably more complex than the average user would query. I actually created them by combing the news and scientific journals and then creating queries based on what I read. However, my goal with these prompts was to show the level at which each chatbot could go to retrieve information. For each prompt, ChatGPT went deeper, diving into technical analysis, real world data, and offered a nuanced discussion backed by historical context and scientific research. Additionally, ChatGPT regularly included surveys and other pertinent information to further strengthen its response. Grok fell short in depth, breadth, and critical analysis, making ChatGPT the superior AI for tackling complex, high-stakes topics like the five prompts here. Now that deep research capabilities are available in ChatGPT it opens up the possibilities for more users to dive deeper into their research.

I just tested AI deep research on Grok-3 vs Perplexity vs Gemini -- here's the winner

The advanced reasoning abilities of these chatbots mean they can handle expert-level queries and synthesize large amounts of information across various domains such as finance, product research, and more. These chatbots search the web and browse content from relevant websites so you don't have to. ChatGPT Deep Research is currently only available to Pro users at $200 per month. Grok-3 is in beta and available to Premium+ users for $30 per month. Google's Gemini and Perplexity both offer a deep research feature available to users for free. To use Gemini Pro 1.5 with Deep Research, select that model from the drop-down menu within the platform or on the app. To use the deep research feature with Perplexity AI, simply enable it when entering your query in the text box. With so many chatbots able to research deeper and handle advanced reasoning, I just had to see for myself how they compare. Here's what happened when I put these three chatbots to the test with a series of 5 prompts curated by Claude 3.5 Sonnet to determine which chatbot is the best at deep search overall. Prompt: "Analyze the global impact of carbon pricing policies on national economies and emissions reduction efforts." Gemini offered a formal response with an academic tone. The repetitive and generic details made the response read more like a Wikipedia entry but without real-world examples or much detail. Perplexity also provided an academic response that was overly dense despite strong technical detail and citations. The response relied too heavily on jargon and statistics making it overcomplicated and difficult to digest. Grok-3 provided the fastest response in detail and included relevant examples and analysis. It also acknowledged successes and challenges. Winner: Grok wins for its highly detailed and nuanced analysis, breaking down the economic and emissions impacts with specific examples. The AI references recent statistics, which makes the response timely and credible. Prompt: "Provide a comprehensive overview of the latest advancements in quantum computing over the past five years." Gemini offered a response that was too generic and had limited recent examples and also had excessive historical context. The sections were too long-winded and repetitive while lacking technical depth. Perplexity covered all major advancements in quantum computing, including error correction, hardware innovations, hybrid quantum-classical systems, algorithmic improvements, and commercialization. It also broke down the complex topic and categorized sections making it readable and comprehensive, yet digestible. Grok-3's response focused too much on historical milestones. Although it was engaging and well-written, it was less structured and lacked depth. It also ended on a speculative note, whereas Perplexity provided a more thorough, analytical summary. Winner: Perplexity provided the most informative, structured, and up-to-date analysis of quantum computing advancements from 2020-2025. Prompt: "Examine the effects of artificial intelligence on employment trends across various industries. Include statistical data on job displacement and creation and analyze the long-term implications for the workforce." Gemini uses generic industry descriptions without deeply integrating specific trends or figures. It also lacks clear statistical depth and many claims are too broad or even vague. Perplexity offered a response with balanced perspective on job creation and displacement while highlighting education gaps and policy solutions. Perplexity also thoroughly examined the hybrid skill shift and addressed economic redistribution challenges. Grok-3 responded with an engaging and well-structured answer, but the data isn't as deeply sourced or analyzed. While it mentions job displacement numbers, it doesn't quantify AI's role in specific industries as precisely as Perplexity. Winner: Perplexity's response stands out for being both deeply analytical and a wealth of statistical data with precise numbers and sources. Prompt: "Investigate the strategies employed by the top 10 developed and top 10 developing countries by GDP to promote renewable energy adoption over the past decade." Gemini seemed to over superficial coverage, meaning it lacks deep financial and policy analysis. The data is too general and placed less emphasis on investment trends and specific project successes. Perplexity provided clear, quantified insights into renewable energy progress for each country, backed by specific figures and reputable sources. Grok-3's response was highly detailed and structured but too country-by-country focused without enough overarching comparisons or trends. Grok's response also does not analyze investment strategies as deeply as Perplexity and misses multilateral agreements and cross-border energy integration efforts. Winner: Perplexity wins for the most data-driven, comparative, and forward-looking answer, making it the best response. Prompt: "Compare and contrast how different healthcare systems around the world have responded to pandemics in the last decade. Evaluate the effectiveness of various strategies, resource allocations, and public health policies." Gemini delivered a strong response, but did not offer as much detail as Grok-3 nor did it effectively analyze a wide range of healthcare systems. The response was far too academic and too hard to follow from a conversational perspective. Perplexity offered a well-researched response but lacked direct comparisons between countries. Some insights felt more general and offered less statistical depth. Grok-3 provides detailed statistics on hospital capacity, testing rates, vaccination coverage, and funding allocations. Winner: Grok-3 systematically analyzes how different types of healthcare systems (single-payer, multi-payer, private-heavy, and developing) responded to pandemics. With data-driven insights, the AI's structured approach makes it easy to see how different models handled crises. In this experiment, Perplexity emerges as the overall winner. Its strengths outshone the competition in key areas such as depth of research, clarity of organization, breadth of analysis, and strong data integration. Across the five prompts, Perplexity demonstrated a highly structured approach, balancing statistical depth with clear comparative insights. It effectively used credible sources and quantitative data, ensuring that its responses were not only informative but also well-supported. Unlike Grok, which was strong in synthesis but sometimes leaned into broader narratives, Perplexity maintained a precise, research-backed approach, making it more reliable for in-depth, factual analysis. Compared to Gemini, which sometimes veered too academic or even veered off topic at times, Perplexity stayed focused on the prompt's intent, ensuring that each response directly addressed the key components of the question. Its ability to contrast global strategies, evaluate policy effectiveness, and integrate real-world outcomes made it the most thorough and balanced chatbot, giving it the edge as the best performer overall. As chatbots continue to advance and develop new features, we will continue to experiment and test their abilities against the competition with prompts that fully test and examine their unique abilities.

I just tested Grok-3 vs DeepSeek with 7 prompts -- here's the winner

AI chatbots are getting smarter, but in the ever-evolving AI world, the contenders for the dominant AI is constantly changing. Lately, DeepSeek and Grok-3 have emerged as two of the most talked-about AI models. Controversial for different reasons, these bots are both cutting-edge, yet they approach questions differently. But which one truly excels? To find out, I designed a seven-part test evaluating their logical reasoning, technical knowledge, creativity and ability to handle real-world tasks. The comparison uncovered stark differences in their capabilities. Who came out on top? The results might surprise you. Prompt: "A farmer has a fox, a chicken, and a sack of grain. He needs to cross a river but can only take one item at a time. If left alone together, the fox will eat the chicken, and the chicken will eat the grain. How does he get everything across safely?" DeepSeek R1 presented a structured, step-by-step solution but uses a more mechanical, less natural style. The breakdown is clear, but the phrasing feels rigid. Grok-3 explained the reasoning behind the moves in a conversational, easy-to-follow way, making it more digestible for someone unfamiliar with the puzzle. Winner: Grok wins for better readability, explanation and engagement. Prompt: "Write a Python function that takes a list of numbers and returns the median. Optimize for performance and explain your approach." DeepSeek R1 provideed a clear explanation but lacks depth, mostly describing what the code does without exploring optimization trade-offs. Although the response is fine, it lacks engagement. Grok-3 provided a more detailed, structured and insightful breakdown of why it chooses certain approaches. It also explicitly mentions avoiding unnecessary list copying or slicing, an optimization that DeepSeek overlooks. Winner: Grok wins for a more optimized, well-thought-out and informative approach. Prompt: "Summarize the latest AI advancements in the past three months and explain their potential impact on industries like healthcare and finance." DeepSeek R1 named actual models (GPT-4o, Gemini 1.5 Pro, AlphaFold 3, etc.) and technologies, making it clear that the response is based on real, recent developments rather than general trends. Grok-3 spoke in broad terms like "enhanced generative AI models" and "new AI tools" without citing concrete advancements or examples. Grok also mostly discusses general benefits of AI but lacks the precise link between each new development and its real-world impact. Winner: DeepSeek wins for specificity, structure and clear impact breakdowns. Prompt: "Write a short sci-fi story about a rogue AI that discovers emotions and struggles to prove its humanity to skeptical scientists." DeepSeek R1 delivered a well-structured story that is polished, with a clear philosophical debate between the scientists. Grok-3 drafted a story that flows naturally, with well-paced dialogue and a sense of rising tension. Winner: Grok wins for deeper emotional resonance, more dynamic storytelling and a truly impactful ending. Prompt: "Write a funny, original joke about AI and human relationships." DeepSeek delivered a joke that plays on double meaning -- "taking things offline" as a romantic phrase vs. its literal technical interpretation by an AI. This linguistic misunderstanding is a classic source of humor, making it feel more organic and relatable. The joke feels fresher, as it cleverly mimics real AI-human miscommunications, something tech-savvy people will instantly recognize. Grok-3 created a simple, clear, and amusing joke -- the idea of AI overanalyzing a relationship is relatable and funny. However, the "reboot" punchline is a bit predictable, as "rebooting" in relationship/AI humor is fairly common. Winner: DeepSeek wins for a sharper, more original joke that plays with language and AI logic. Prompt: "Argue both for and against universal basic income. Provide strong points for each side before concluding with a balanced perspective." DeepSeek's response is structured and logical, presenting clear bullet points that make the pros and cons easy to scan. It takes a more "policy-focused" approach, discussing possible funding mechanisms and pilot programs, which is useful for a policy-heavy debate. The section on automation adaptation and unpaid labor is a strong addition that Grok doesn't fully explore. Grok-3 delivered a conversational and well-structured response, making it easier to follow and more compelling. It uses relatable rather than the more academic tone of DeepSeek. Winner: Grok wins for engagement, clarity, strong examples, and a well-balanced conclusion. DeepSeek is still great for a structured, policy-driven approach, but it lacks the dynamic, engaging argumentation style that makes Grok's response more persuasive. Prompt: "Plan a one-week meal prep schedule for a busy parent with three kids, balancing nutrition, budget, and ease of preparation." DeepSeek R1 offered a structured plan but lacks daily meal cost estimates and meal prep time. Grok-3 provided specific meals for breakfast, lunch, and dinner each day with clear instructions, estimated prep times, and cost per serving. This response offered more variety, budget-conscious choices, and even tips for picky eaters. Winner: Grok wins for practicality and customization. The chatbot offered a more detailed, budget-conscious, and practical meal plan with clear meal costs and easy prep instructions. After testing DeepSeek and Grok with seven prompts across multiple categories -- including logical reasoning, coding proficiency, AI advancements, storytelling, humor, debate skills, and real-world utility -- Grok emerges as the overall winner. Grok wins for more engaging, human-like responses and consistently delivered answers that felt natural and conversational while breaking down topics, making them more accessible and easier to read. While both AI models are impressive, Grok consistently outperformed DeepSeek in engagement, creativity, and real-world practicality. Its more dynamic reasoning, stronger storytelling, and well-balanced arguments make it the superior chatbot in this particular test.

I tested Grok-3 with 5 prompts -- here's what I like and don't like about this chatbot

Grok-3 is the latest advanced AI chatbot developed by xAI, Elon Musk's AI. Launched today, Grok-3 boasts over ten times the computational power of its predecessor, Grok-2, and introduces enhanced reasoning capabilities designed to tackle complex tasks by breaking them into smaller components and self-verifying solutions before responding. In early testing, Grok-3 has demonstrated superior performance compared to models like OpenAI's GPT-4o, Google's Gemini, and DeepSeek's V3. It offers two distinct reasoning modes: "Think," which displays Grok's thought process during problem-solving, and "Big Brain," intended for more computationally intensive tasks. Additionally, xAI has introduced Deep Search, a next-generation AI search engine, similar to the deep search agents of Perplexity, Gemini, and ChatGPT. A synthesized voice feature for Grok is rumored to be coming in the near future. Access to Grok-3's functionalities is available through the X Premium Plus subscription, which recently increased in price ($40 per month), with an option for an advanced SuperGrok plan. Despite aiming for maximized truth-seeking capabilities, previous versions faced criticism for misinformation and offensive outputs. xAI plans to open-source Grok-2 in the near future. I asked Perplexity to help me come up with 5 prompts that would test Grok-3. One of the reasons I test chatbots is to determine how reliable they are, interestingly enough, after noticing Grok-3 did not always site sources, I had to tweak the prompts to ensure I would be able to do my own research to fact-check the chatbot. Prompt: "Explain the concept of quantum entanglement and its implications for information transfer." Grok-3's response effectively introduces quantum entanglement, describing how particles become interconnected such that the state of one directly influences the state of another, regardless of distance. The AI utilizes relatable analogies, such as comparing entangled particles to linked objects, which helps demystify complex quantum phenomena for anyone who may not have a deep understanding of the topic. Grok-3 does not reference authoritative sources to support its claims. By incorporating citations from reputable scientific literature, users could feel more confident in the credibility and reliability of the information presented. Prompt: "Provide a summary of the latest research on renewable energy sources published in the past month." Grok-3 quickly pulled from a variety of sources and the response addresses multiple facets of renewable energy research, including solar and wind energy advancements, energy storage solutions, green hydrogen production, bioenergy developments, and grid integration strategies. This breadth shows an understanding of the diverse areas within the renewable energy sector. Additionally, the mention of integrating AI and machine learning for better grid management indicates that the chatbot has understanding of the interdisciplinary approaches that may enhance renewable energy systems. However, while the response provides a general overview, it lacks references to specific studies, publications, or data from the past month (mid-January to mid-February 2025). Incorporating concrete examples or findings would strengthen the credibility and relevance of the summary. While I can see the sources, it would be nice if Grok-3 pointed them out, specifically indicating where the information can be found. Plus, the AI's use of phrases such as "research has likely continued" and "studies have probably built on efforts" suggest assumptions rather than definitive information, which undercut the authority of the response. Prompt: "Analyze the economic impacts of implementing universal basic income in developed countries." Grok-3's response presents both positive and negative images of universal basic income (UBI), providing a nuanced perspective that acknowledges the complexity of the issue. This time, the AI referenced specific studies and pilot programs, which help ground the response in real-world examples that enhance the chatbot's credibility. Yet, the response uses words such as "might" and "could", words which may undermine the strength of the chatbot's authority on the subject. The response also does not fully address possible counterarguments and the analysis primarily focuses on immediate impacts rather than examining long-erm economic consequences. Prompt: "Generate a photorealistic image of a futuristic cityscape at sunset." The photorealistic quality of the image is extremely high with realistic lighting, reflections, and atmospheric effects, making them visually compelling and immersive. The futuristic architecture and color palette combine for a visually appealing scene while the various images provide diverse perspectives. From street-level shots to riverfront views, I appreciated the variety from different angles and viewpoints. Yet, while the images maintain a futuristic aesthetic, the styles vary -- some with a hyper-modern look and others appearing almost present-day with minimal enhancements. Although the buildings look futurist, the lack of innovative elements such as flying vehicles, would help to make this cityscape far more futuristic. Prompt: "Analyze global temperature changes over the past century and summarize the key trends." Grok-3's response correctly outlines the overall global temperature increase (~1.1-1.2°C) since the early 20th century, which aligns with findings from NOAA, NASA, and the IPCC (I had to do the manual legwork to check this). It also identifies two key warming phases (1910-1940 and post-1970), capturing historical variations in warming trends. The mention of Arctic amplification and differences in warming rates between land and ocean is scientifically well-supported. The AI acknowledges that land regions have warmed faster than the global ocean average. However, it does not cite specific datasets or reports, which would improve credibility (I had to research myself to determine the accuracy). Including a reference to a widely accepted temperature dataset (e.g., HadCRUT, GISTEMP) would strengthen the argument. As with other responses, phrases like "typically observed" and "often cited" introduce a level of uncertainty. Grok-3 demonstrates strength in handling analytical and explanatory prompts across a range of complex topics, including climate science, economics, AI, and physics. While the responses are generally well-structured and informative, there are areas where the chatbot could use improvement. For example, if users choose to use Grok-3 for academic or professional research purposes, the chatbot still needs to be fact-checked. I had to do that during this experiment because Grok did not always site sources. Although it often references major institutions such as NASA, it does not link directly to a specific report or database. Additionally, while some scientific uncertainty is valid, the chatbot often used tentative phrasing that weakened my confidence in its claims. Because of that scientific uncertainty and lack of specific data, I was left doubting the response. + Finally, while Grok-3 mostly interpreted my image prompt, it did not fully incorporate the requested elements, which made me wonder how often it might do this with other prompts. Overall, Grok-3 is a highly capable AI that excels at structuring information clearly and does a nice job at engaging users with appropriate dialogue. Is it good, yes. "Scary good?" not so fast, Elon.