I use Claude, Gemini, and ChatGPT every day—here’s the only one you should pay for


I use Gemini, ChatGPT, and Claude almost every day, both for work and for my own projects. Each service has its strengths and weaknesses, and you can access a lot of the features for free. The paid plans offer even more features, but if you only want to pay for one, there’s a clear winner.

Gemini is great for research

It’s a good choice if you’re all in on Google services

Gemini Suite Logo on black background. Credit: Google

Unsurprisingly for a chatbot built by Google, Gemini is great for search. In my experience, this is something that Claude in particular struggles with; it can’t read through Reddit threads, for example, claiming that Reddit is blocked from its web fetching tool. When I need to find a particular post or piece of information, I usually use Gemini’s free tier.

Gemini also excels at deep research. All three services have deep research tools, but in my experience, Gemini goes deeper and pulls from more sources than either ChatGPT or Claude.

One of the most unique features is Audio Overview, which turns your research report into an AI-generated podcast, which can be an easier way to digest a complex report. I use deep research and the Audio Overview feature on the free tier, as I rarely need to do more than a few deep dives a month.

Gemini also integrates seamlessly with other Google services such as Gmail, Google Docs, and Google Sheets, although you need a paid subscription to take advantage of some of the more useful features. It also currently has the best image generation of the big three.

ChatGPT is more thorough

It has some useful tools

The ChatGPT logo on a gray embossed background. Credit: Andrew Heinzman / How-To Geek

ChatGPT was the first AI chatbot that I paid for, and I used it exclusively for a long time. There’s a lot that it’s really good at, and it’s packed with useful features.

One of the things I use it for most is proofreading. ChatGPT is great at spotting grammatical errors and typos in my work, as well as spotting anything that’s outdated or inaccurate. Using the same prompt, Claude isn’t nearly as good, missing a lot of the things that ChatGPT catches.

Creating custom GPTs and setting up projects is also really useful, but while you can create projects for free, you need to be on a paid tier to create custom GPTs. Once you’ve built them, however, you can use them even without a subscription.

The desktop app has some useful tools, too. The Work with Apps feature on macOS can be really useful; it lets ChatGPT see the content of apps you have open, so you don’t have to keep copying and pasting the output from the Terminal, for example.

Codex, OpenAI’s coding tool, is also very good. Using models such as GPT-5.3-Codex, it can rival Claude in terms of coding capabilities. As well as coding, you can also use Codex app for more agentic tasks, such as asking it to batch rename a folder full of image files with an alt text description of each image.

Claude is great for coding and connectivity

Computer Use is also wild

One of the big reasons that many people use Claude is for coding. Claude Opus 4.6 is one of the strongest models for coding and reasoning right now. I’m not an avid coder, but I’ve used it to vibe code a few personal projects, and it’s very impressive.

Two very useful features in Claude are Cowork and Computer Use. Cowork lets you give Claude a multi-step task, which it then gets on with, using the local files on your computer. For example, you can point it at a folder of scanned receipts and ask it to turn them into an expense report, and Cowork will use OCR to read the information and compile it all into a report for you.

Computer Use lets Claude take control of your computer, using screenshots to “see” the screen and moving the mouse to click UI elements. It works, if fairly slowly, but handing over the keys to your computer to an AI still feels a little scary.

Claude is the one that’s worth the sub

The best features for your money

Claude Cowork creating files and folders in Windows workspace

To my mind, Claude is the one subscription that’s worth paying for. You can do a lot with the free versions of Gemini and ChatGPT, but there are some key Claude features that you can’t access without a subscription.

Cowork (including Computer Use) and Claude Code are all paid features that you can’t access for free, and each one alone is worth the sub. The Dispatch feature also makes the subscription worth paying. It lets you start a task from your phone, which Claude will tackle on your desktop while you’re away, meaning you can get Claude working on tasks wherever you are.

One of the things that I find most useful about Claude is its connectivity. ChatGPT has several connectors that you can use to connect your chatbot to services such as Notion, Spotify, and TripAdvisor. These are hit-or-miss, however; I’ve never been able to get the Notion connector to work. Gemini’s connectors are mostly focused on Google apps.

Claude is the most versatile when it comes to connectivity. It has a large selection of connectors you can use with powerful features. The Notion connector lets you read and write to Notion, for example. It also makes it simple to connect your own custom MCP servers to Claude, allowing you to use Claude to interact with apps and services, although you need a subscription to set up more than one custom connector.

One downside of Claude’s plans is the rate limits. I have a $20 Pro subscription, and I don’t hit the limits too often. Heavier users, however, are finding the limits increasingly frustrating.


You can do a lot with free tiers

Claude, Gemini, and ChatGPT are all very powerful tools, and each excels at specific things. I continue to use Gemini and ChatGPT for free for specific tasks, but for now, Claude is the subscription that I can’t live without.



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Recent Reviews


As I’m writing this, NVIDIA is the largest company in the world, with a market cap exceeding $4 trillion. Team Green is now the leader among the Magnificent Seven of the tech world, having surpassed them all in just a few short years.

The company has managed to reach these incredible heights with smart planning and by making the right moves for decades, the latest being the decision to sell shovels during the AI gold rush. Considering the current hardware landscape, there’s simply no reason for NVIDIA to rush a new gaming GPU generation for at least a few years. Here’s why.

Scarcity has become the new normal

Not even Nvidia is powerful enough to overcome market constraints

Global memory shortages have been a reality since late 2025, and they aren’t just affecting RAM and storage manufacturers. Rather, this impacts every company making any product that contains memory or storage—including graphics cards.

Since NVIDIA sells GPU and memory bundles to its partners, which they then solder onto PCBs and add cooling to create full-blown graphics cards, this means that NVIDIA doesn’t just have to battle other tech giants to secure a chunk of TSMC’s limited production capacity to produce its GPU chips. It also has to procure massive amounts of GPU memory, which has never been harder or more expensive to obtain.

While a company as large as NVIDIA certainly has long-term contracts that guarantee stable memory prices, those contracts aren’t going to last forever. The company has likely had to sign new ones, considering the GPU price surge that began at the beginning of 2026, with gaming graphics cards still being overpriced.

With GPU memory costing more than ever, NVIDIA has little reason to rush a new gaming GPU generation, because its gaming earnings are just a drop in the bucket compared to its total earnings.

NVIDIA is an AI company now

Gaming GPUs are taking a back seat

A graph showing NVIDIA revenue breakdown in the last few years. Credit: appeconomyinsights.com

NVIDIA’s gaming division had been its golden goose for decades, but come 2022, the company’s data center and AI division’s revenue started to balloon dramatically. By the beginning of fiscal year 2023, data center and AI revenue had surpassed that of the gaming division.

In fiscal year 2026 (which began on July 1, 2025, and ends on June 30, 2026), NVIDIA’s gaming revenue has contributed less than 8% of the company’s total earnings so far. On the other hand, the data center division has made almost 90% of NVIDIA’s total revenue in fiscal year 2026. What I’m trying to say is that NVIDIA is no longer a gaming company—it’s all about AI now.

Considering that we’re in the middle of the biggest memory shortage in history, and that its AI GPUs rake in almost ten times the revenue of gaming GPUs, there’s little reason for NVIDIA to funnel exorbitantly priced memory toward gaming GPUs. It’s much more profitable to put every memory chip they can get their hands on into AI GPU racks and continue receiving mountains of cash by selling them to AI behemoths.

The RTX 50 Super GPUs might never get released

A sign of times to come

NVIDIA’s RTX 50 Super series was supposed to increase memory capacity of its most popular gaming GPUs. The 16GB RTX 5080 was to be superseded by a 24GB RTX 5080 Super; the same fate would await the 16GB RTX 5070 Ti, while the 18GB RTX 5070 Super was to replace its 12GB non-Super sibling. But according to recent reports, NVIDIA has put it on ice.

The RTX 50 Super launch had been slated for this year’s CES in January, but after missing the show, it now looks like NVIDIA has delayed the lineup indefinitely. According to a recent report, NVIDIA doesn’t plan to launch a single new gaming GPU in 2026. Worse still, the RTX 60 series, which had been expected to debut sometime in 2027, has also been delayed.

A report by The Information (via Tom’s Hardware) states that NVIDIA had finalized the design and specs of its RTX 50 Super refresh, but the RAM-pocalypse threw a wrench into the works, forcing the company to “deprioritize RTX 50 Super production.” In other words, it’s exactly what I said a few paragraphs ago: selling enterprise GPU racks to AI companies is far more lucrative than selling comparatively cheaper GPUs to gamers, especially now that memory prices have been skyrocketing.

Before putting the RTX 50 series on ice, NVIDIA had already slashed its gaming GPU supply by about a fifth and started prioritizing models with less VRAM, like the 8GB versions of the RTX 5060 and RTX 5060 Ti, so this news isn’t that surprising.

So when can we expect RTX 60 GPUs?

Late 2028-ish?

A GPU with a pile of money around it. Credit: Lucas Gouveia / How-To Geek

The good news is that the RTX 60 series is definitely in the pipeline, and we will see it sooner or later. The bad news is that its release date is up in the air, and it’s best not to even think about pricing. The word on the street around CES 2026 was that NVIDIA would release the RTX 60 series in mid-2027, give or take a few months. But as of this writing, it’s increasingly likely we won’t see RTX 60 GPUs until 2028.

If you’ve been following the discussion around memory shortages, this won’t be surprising. In late 2025, the prognosis was that we wouldn’t see the end of the RAM-pocalypse until 2027, maybe 2028. But a recent statement by SK Hynix chairman (the company is one of the world’s three largest memory manufacturers) warns that the global memory shortage may last well into 2030.

If that turns out to be true, and if the global AI data center boom doesn’t slow down in the next few years, I wouldn’t be surprised if NVIDIA delays the RTX 60 GPUs as long as possible. There’s a good chance we won’t see them until the second half of 2028, and I wouldn’t be surprised if they miss that window as well if memory supply doesn’t recover by then. Data center GPUs are simply too profitable for NVIDIA to reserve a meaningful portion of memory for gaming graphics cards as long as shortages persist.


At least current-gen gaming GPUs are still a great option for any PC gamer

If there is a silver lining here, it is that current-gen gaming GPUs (NVIDIA RTX 50 and AMD Radeon RX 90) are still more than powerful enough for any current AAA title. Considering that Sony is reportedly delaying the PlayStation 6 and that global PC shipments are projected to see a sharp, double-digit decline in 2026, game developers have little incentive to push requirements beyond what current hardware can handle.

DLSS 5, on the other hand, may be the future of gaming, but no one likes it, and it will take a few years (and likely the arrival of the RTX 60 lineup) for it to mature and become usable on anything that’s not a heckin’ RTX 5090.

If you’re open to buying used GPUs, even last-gen gaming graphics cards offer tons of performance and are able to rein in any AAA game you throw at them. While we likely won’t get a new gaming GPU from NVIDIA for at least a few years, at least the ones we’ve got are great today and will continue to chew through any game for the foreseeable future.



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