ChatGPT-5 vs Claude vs Qwen : The Hidden Costs of Picking the Wrong AI Model
In this comparative overview, Rob Shocks explains how these AI models stack up in real-world scenarios, using the development of 'Newsletter Digest' as a case study. You'll uncover insights into their performance metrics, strengths, and limitations, as well as the hidden costs that could impact your budget. Whether you're a developer seeking reliability, a strategist prioritizing creativity, or someone chasing speed, this breakdown will help you navigate the trade-offs. By the end, you might find yourself rethinking what matters most in an AI partner: precision, adaptability, or efficiency? AI Model Comparison Summary Project Overview: Developing 'Newsletter Digest'
'Newsletter Digest' is a web application that connects to Gmail, aggregates newsletters, and summarizes key stories for users. It also allows users to view individual newsletters in a streamlined interface. The app was developed using a modern tech stack to ensure scalability, responsiveness, and ease of use: Next.js: A React-based framework for building a dynamic and efficient front end.
A React-based framework for building a dynamic and efficient front end. Tailwind CSS: A utility-first CSS framework that enabled clean, responsive design.
A utility-first CSS framework that enabled clean, responsive design. Neon: A Postgres database solution for managing user and application data.
A Postgres database solution for managing user and application data. Prisma: A database toolkit that simplified schema generation and management.
A database toolkit that simplified schema generation and management. Clerk: A user authentication and management tool integrated with Stripe for seamless billing functionality.
The core functionality of summarizing newsletters relied on the capabilities of Claude, GPT-5, and Qwen Coder. These models were tested for their ability to deliver a functional app, their speed, usability, and cost-effectiveness. Comparing the AI Models Claude (Opus 4.1 and Sonnet 4)
Claude proved to be the most reliable and mature AI model for this project. It excelled in generating a fully functional app with minimal errors, particularly in tasks such as database schema generation and implementing app features. Its workflow required fewer corrective prompts, which significantly reduced development time. However, this high level of performance came at a premium, as Claude was the most expensive model in the comparison. For developers prioritizing reliability and efficiency, Claude offers a robust solution, albeit at a higher cost. GPT-5
GPT-5 demonstrated strong strategic thinking and versatility but fell short in implementation compared to Claude. While it made reasonable progress in building the app, it required more corrective prompts and encountered occasional errors during the setup process. The Cursor CLI, used to interact with GPT-5, is still in beta, which introduced some glitches and limited functionality. Despite these challenges, GPT-5 showcased its ability to handle complex tasks with guidance, making it a viable option for developers who can invest additional time in troubleshooting and refinement. Qwen Coder
Qwen Coder stood out for its speed, delivering rapid responses during the development process. However, it struggled to produce a complete and functional app. Its outputs were often incomplete, and it frequently stopped abruptly, requiring significant manual intervention to fill in the gaps. While its speed is promising, Qwen's lack of reliability and functionality placed it behind both Claude and GPT-5 in this comparison. Developers seeking a balance between speed and reliability may find Qwen less suitable for complex projects. ChatGPT-5 vs Claude vs Qwen
Watch this video on YouTube.
Stay informed about the latest in AI Models Comparison by exploring our other resources and articles. Performance Metrics
The three AI models were evaluated based on their overall performance in building 'Newsletter Digest.' The results revealed clear distinctions in their capabilities: Claude: Delivered the most reliable and functional app with minimal errors and a smooth workflow.
Delivered the most reliable and functional app with minimal errors and a smooth workflow. GPT-5: Ranked second, offering decent progress but requiring more corrections and encountering occasional errors.
Ranked second, offering decent progress but requiring more corrections and encountering occasional errors. Qwen: Ranked third, excelling in speed but failing to deliver a complete and reliable app.
Claude's ability to produce a polished and functional app with fewer iterations made it the top performer, while GPT-5's versatility and Qwen's speed highlighted their respective strengths and limitations. Cost Analysis
Cost is a significant factor when selecting an AI model, particularly for projects with budget constraints. Here's a breakdown of the pricing for each model: Claude (Opus 4.1): $15 per million input tokens, $75 per million output tokens.
$15 per million input tokens, $75 per million output tokens. GPT-5: $0.125 per 1,000 input tokens, $0.10 per 1,000 output tokens.
$0.125 per 1,000 input tokens, $0.10 per 1,000 output tokens. Qwen: Pricing varies but is generally more affordable than Claude and GPT-5.
While Claude was the most expensive option, its superior performance justified the higher cost for this project. GPT-5 offered a more affordable alternative with slightly reduced effectiveness, while Qwen's lower cost reflected its limited functionality and reliability. Insights on Development Tools
The development process also highlighted the importance of the tools used alongside the AI models. These tools played a critical role in streamlining the workflow and making sure a smooth development experience: Clerk: Simplified user authentication and integrated seamlessly with Stripe for billing, reducing the complexity of managing user accounts.
Simplified user authentication and integrated seamlessly with Stripe for billing, reducing the complexity of managing user accounts. Cursor CLI: Provided access to multiple AI models but, as a beta tool, had limited features and occasional glitches that impacted usability.
Provided access to multiple AI models but, as a beta tool, had limited features and occasional glitches that impacted usability. Neon (Postgres DB): Worked effectively for database management, especially when paired with Prisma for schema generation and maintenance.
While most tools performed well, the beta status of Cursor CLI highlighted the need for further refinement to improve its reliability and feature set. Looking Ahead: Future Considerations
As of August 2025, the AI landscape continues to evolve, with emerging models like Grok and Gemini showing potential to disrupt the market. Developers should remain vigilant for advancements in AI capabilities and pricing structures. For now, Claude remains the preferred choice for projects requiring maturity, reliability, and comprehensive functionality. GPT-5 offers a strong alternative for tasks that demand strategic thinking and creative input, while Qwen Coder's speed may appeal to developers working on less complex applications. Continued refinement of tools like Cursor CLI and exploration of new technologies will further enhance the app development process, paving the way for more efficient and innovative solutions.
Media Credit: Rob Shocks Filed Under: AI, Top News
Latest Geeky Gadgets Deals
Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Times
19 minutes ago
- Times
Silicon Valley's revolution is coming — if it can find the power
T he world was a different place in 1910, when the McCalls Ferry Dam spanning the Susquehanna river in Pennsylvania was finally completed and its turbines started spinning. The first Ford Model T had just rolled off the line. The Wright brothers had pulled off their maiden flight just a few years prior. And in cities, the miracle of electrification was taking hold. More than a century later, McCalls Ferry, since renamed Holtwood Hydroelectric, is once again at the forefront of a brave new era. This time it's artificial intelligence and, more specifically, the race to secure the immense electrical capacity required to power the data centres being built to handle that next query to your favourite chatbot. Google's owner, Alphabet, last month agreed a $3 billion (£2.2 billion) deal to upgrade and source power from Holtwood and another hydro facility, as a part of a frenetic global build-out in which it will spend $75 billion in the next year on data centres and the power plants to run them. Between now and 2029, global spending on data centres and associated infrastructure could hit $3 trillion, according to banking giant Morgan Stanley — an epic infrastructure boom akin to railroads and canals.
Daily Mail
an hour ago
- Daily Mail
HAMISH MCRAE: Why now could be the time to sell your shares
It's a tricky time for investors. Quite aside from all the geopolitical stuff in Alaska, the trade disruption, inflation climbing again, and all that, there are troubling signs for the world economy. Yet there is also FOMO, the fear of missing out, and anyone who has remained fully invested in global equities will so far have been well rewarded. You can see this tension in the markets. The FTSE 100 duly hit an intraday all-time high of 9,222 early on Friday morning, only to worry that this might not be such a great idea after all and slither back down. The S&P 500 closed on Thursday at a record high, but weakened on Friday too. There's that nagging doubt that we're in the final phase of what has been a great bull market and something nasty is around the corner. The professionals are picking this up. Goldman Sachs has warned of the possibility of a sharp sell-off in the S&P 500, with more than a 10 per cent chance of a decline in the next three months and more than a 20 per cent chance next year. Those percentages may not sound very high, but if there is to be one of those classic October crashes, it's good to have a warning on the record. Here in London, Longview Economics has a model that is signalling that the S&P 500 is a strong sell, noting 'signs of froth and speculation' and asking that tough question: 'Is the market about to sell off (or even crash)?' It is neutral on this, acknowledging that it might be being overcautious. But it also points out that whenever a company produces disappointing results, its shares get hammered. Taking the US market as a whole, it is one of those situations where it has to keep pedalling hard to keep the bicycle upright, with any slowdown or wobble potentially ending up in a crash. There is a long list of things that might lead to a wobble. Looking at the world economy, we don't yet have any real feeling for the damage to growth or inflation from Donald Trump's tariffs. But put it this way: tariffs cannot boost global growth or cut overall inflation. They have to be negative, and it is not as though the world economy is in great shape. Look at us here. Thanks to a not-too-dreadful second quarter after the strong start, the UK does seem to be the fastest-growing economy in the G7 so far this year, as Rachel Reeves has said. Sure, that follows a very weak second half last year, and sure, it is puffed up by an unsustainable increase in public spending. But you do have to ask that if we are the best, what on earth is happening to the others? There's the evidence of rising inflation, particularly here but also in the US, and the impact that will have on long-term interest rates. Our ten-year gilt yield touched 4.7 per cent in Friday trading. Some institutions are forced to hold Government debt, but for the rest of us, it can't be a good idea to lend to governments that have no serious intention of cutting their fiscal deficits. There are all sorts of troubling signs of a slowdown. Houses are taking longer to sell in America and demand for graduate jobs there is weak. Walk down any High Street and count the number of voids. Our hospitality sector is struggling. We know we will be clobbered with higher taxes come the autumn. The fact that things feel fragile here does not mean FTSE 100 shares will be directly hit because more than three-quarters of their profits come from abroad, either in exports or earnings from overseas. But there are parallels: a lot of people across Europe as well as in America are tightening their belts. How long before that shows up in the profit and loss accounts of multinationals? You see the point. On a very long view, it is always right to invest in global equities. If you get out, it's always difficult to know when to get back in. The UK market certainly offers good value vis-a-vis the US one but, as Bloomberg reported on Friday, the strategists do not expect the FTSE 100 to end the year above 9,000, the average being 8,950. If shares are likely to fall, it may not be a bad idea to sell a few before they do. To be clear, I am not predicting an October crash, but these are indeed tricky times and it would be nuts not to acknowledge that.
Daily Mail
an hour ago
- Daily Mail
Trump launches 'Manhattan Project' as one of America's largest companies set to be nationalized
The Trump administration has launched their own 'Manhattan Project,' as reports have suggested one of America's largest chipmakers could be partly nationalized. Intel. Corp, one of the most capable semiconductor manufacturers in the US, has been in talks with the Trump administration as the US government is seeking a stake in the company. 'This feels like the Manhattan Project - or the run-up to World War II,' MIT AI computer scientist Dave Blundin said on a podcast with MIT engineer Peter Diamandis. 'It's every bit as important as the space race was, as the nuclear arms race was. Actually, it's more important.' The consideration to nationalize the company, a move typically done in times of national urgency, comes as the US is looking to get ahead of China in the AI and tech arms race. Intel's advanced abilities to manufacture semiconductors would allow the US to give up its reliance on foreign fabrication plants (fabs), especially in Taiwan which controls more than 60 percent of the market, in order to power artificial intelligence, defense and the economy. The talks remain ongoing and finer details continue to be made clear, but the idea would be that the US government would pay for the stake in the company, one person close to the matter told Bloomberg. Another stressed that the talks do not ensure that the deal is definitive, and the discussion could end without a deal being made. The move, according to AI and tech experts on Diamandis' podcast Moonshots, echoes the 'Manhattan Project' as a sort of a 'national survival strategy.' 'The reason the US needs to protect Taiwan fundamentally... is because the fabs are there. If the fabs all move to the US, then why would the US defend Taiwan?' Blundin said. Concerns have been raised about the decision to nationalize the company, as he added: 'They're putting the whole industry on a kind of war footing, like mobilization for conflict, except the battleground is supply chains and chip fabs.' Intel told Bloomberg, while declining to comment on the discussion with the Trump administration, that the company is 'deeply committed to supporting President Trump's efforts to strengthen US technology and manufacturing leadership.' 'We look forward to continuing our work with the Trump administration to advance these shared priorities, but we are not going to comment on rumors or speculation,' the company added. White House spokesman Kush Desai told the outlet: 'Discussion about hypothetical deals should be regarded as speculation unless officially announced by the administration.' The move comes after two AI companies agreed last week to hand over 15 percent of their chip sales revenue in China to the US government in exchange for export licenses. Nvidia and Advanced Micro Devices (AMD) entered an unprecedented arrangement with the White House to promote and sell their semiconductors in China last week, three people familiar with the situation told the Financial Times. 'In the short term, this is fantastic. In the long term, wow, could this turn bad in a hurry,' Blundin said. 'It's good for the US economy, but we're going to use that to fund [the] US catching up in the chip wars.' 'Very, very good business deal and incredibly slippery slope precedent.' The deal could pour more than $2 billion into the US government, the New York Times reported, although Trump did not reveal what the money may be used for. Just as sources say Trump and the AI companies entered the agreement, the president declared he would impose a 100 percent tariff on the imports of semiconductors and chips unless the company is 'building in the United States.' News of Trump's discreetly entered agreement with Nvidia and AMD has been slammed by experts who say the move could have detrimental repercussions when it comes to US-China relations. 'This is an own goal and will incentivize the Chinese to up their game and pressure the administration for more concessions,' Liza Tobin, who previously served as China director at the National Security Council, told The New York Times. The move to sell microchips to China has been heavily criticized, as many see it as a threat to national security and a move against America's best interests.
