Neural networks are constantly transforming and recently we’ve witnessed many rising AI stars with huge potential. Well-known Chat GPT and Gemini, which up until recently cozily nested atop the Olympus of cutting-edge technologies, now have to make way for a new generation of promising rivals. In the spirit of Daft Punk's "Harder, Better, Faster, Stronger", today we will compare the advantages of new neural networks over famous AI giants and explore how they can simplify the lives of affiliate marketers.
Limitations of First-Generation Neural Networks
When you deal with neural networks like Chat GPT and Gemini, it's important to keep in mind that they lack critical thinking. Despite their impressive results, these AI models cannot exceed the boundaries of their training data. If the original dataset contains errors or inaccuracies, those same flaws will inevitably appear in the AI's responses. That’s why you can’t skip a double-check stage when it comes to any AI-generated content.
On top of that, Chat GPT and Gemini face several significant challenges:
Inconsistent Information. These AI models can sometimes provide contradictory information within the same conversation. Without asking follow-up questions, users might not notice when the AI shifts its stance on a topic, which can lead to misunderstandings or misinformation.
Fabricated Details. Both systems can inadvertently generate false information, particularly when drawing from examples. For instance, if asked to write marketing copy for an online casino, they might include nonexistent bonuses or terms based on similar content in their training data.
Artificial Language Patterns. Although their language processing is sophisticated, AI-generated text can still sound mechanical and repetitive. They often rely on common phrases and structures that have become very conspicuous over the past few years.
Context Comprehension Issues. These models sometimes struggle to grasp nuanced context in complex requests. When creating content like advertising copy, they might overlook key product features that would resonate with the target audience.
Knowledge Cutoff Limitations. Most AI models have a specific knowledge cutoff date, which means they can't make use of information beyond that point. For example, the basic version of Chat GPT's knowledge is limited to data from before January 2022. Besides, many models don’t have real-time internet access, so they probably won’t be basing their responses on up-to-date information.
How to Choose the Best Neural Network for Affiliate Marketing Tasks
To avoid the shortcomings of Chat GPT and Gemini, let’s come up with some evaluation criteria that the perfect candidate should fulfill. As they say, now that we know what we DON’T want, let’s figure out what we absolutely want to get right:
Response Accuracy. By this we mean a thorough answer best correlated with the initial request (even if the phrasing was a little off), with links to reliable sources that validate the information provided by AI. The less fact-checking you have to do afterwards, the better. Because, as we’ve already discovered, there is no such thing as an “I don’t know” answer for neural networks. They’d rather start making up things if they face knowledge gaps in their database. Just like humans do sometimes, haha. For some tasks, letting your imagination run wild can be a plus, but not when we are talking about serious research.
Contextual Awareness. Like we mentioned earlier, it can be a real bummer when AI loses its train of thought in the work process. Most affiliate marketing tasks go way beyond the Q&A format and usually require a complex thread of inquiries to complete a certain goal. To prevent sounding like a broken record and having your follow-ups ignored, it’s important that the network of your choice stays consistently immersed in the context without any glitches.
Customisation. That’s a must-have for any marketer out there. With all those niches and offers, AI assistants have to be tone and style-fluid to resonate with any audience you want to target. If your chat bot sounds like it has swallowed a dictionary and now mindlessly belches beautiful but rambling speech – it might not be the best fit for you.
Creativity. This criterion can get quite subjective. But if you’ve experimented enough with various queries and tasks and AI still manages to surprise you every time with fresh content and original angles – it’s a good sign.
Flexibility. Most neural networks are bound by the rules of ethics and morality – for all that is good and against all that is bad, so to speak. Due to this, you may hit a dead end with marketing tasks outside white-hat offers, like adult or gambling niches – your AI companion will simply refuse to respond to such requests. If you work with grey or black-hat offers, you’ll have to look for more permissive alternatives.
Language Diversity. As affiliate marketers drive traffic to numerous niches all over the world, the more language modules are supported by your neural network, the better. This way you will easily fit both regional and cultural contexts while formulating USPs and CTAs and avoid cases where the wrong wording could ruin the entire marketing campaign.
Testing Next-Generation Neural Networks
We chose five competing AI models to see how well they can handle everyday tasks of an average affiliate marketer.
Information Processing
To hit two birds with one stone, we decided to give these neural networks a chance to describe their own advantages over the more experienced “comrades” and, at the same time, see how far they’ve come in processing data and providing a good digest.
DeepSeek is a neural network created by a team of Chinese developers. Just recently it’s made a huge splash across the internet and markets. It surpassed Chat GPT in the number of app downloads and also demonstrated to the investors that effective AI models don’t mean high expenses (this Chinese digital assistant cost only $5 million whereas Open AI spent $100 million just to develop GPT-4).
Among noteworthy pros of DeepSeek are:
More accurate search results, compared to Chat GPT;
Advanced PDF analysis;
Exceptional coding abilities;
Support for different types of data and media;
Better logical processing and problem-solving;
Precise calculations (e.g. ROI, ROMI and other performance metrics).
This is how DeepSeek describes its own advantages:
Based on the description, DeepSeek seems to fulfill most of the criteria for a perfect AI companion for affiliate marketers. We'll see how it performs in practice a bit later (stay tuned until the end!). In this specific example, the network does not cite sources to confirm the mentioned advantages or provide detailed argumentation, but you can use the Search and DeepThink modes for these purposes. It's also worth noting the polite nod to competitors and the lack of a desire to position itself above them. It’s a nice touch.
Qwen is another marvel from Chinese developers, but this time it’s by the tech giant Alibaba.
There are many models of Qwen to choose from, with all of them available for free. Here is a cheat sheet for you:
Gwen 2.5-Plus. An improved version of the Gwen 2.5 basic model, with additional tweaks and polishes. It’s excellent for writing long-reads, ad campaigns and basic data analysis.
QVQ-72B-Preview. One of the most powerful models in the product line. It specializes in data analysis, including image content. It’s a perfect solution if you need to handle complex tasks like trend identification and strategy optimization.
QwQ-32B-Preview. Your go-to model for quick prototyping and medium-complexity tasks. It’s also great for building chatbots and creating shorter content.
Gwen 2.5-Coder-32b-Instruct. This model is designed for programming and code generation, however, judging by user feedback so far it leaves much to be desired.
Qwen2-VL-Max. It effectively processes and combines visual and textual information.
As an example, today we will be discussing the Qwen 2.5-Plus model. Unlike DeepSeek, this neural network is not shy about singing its own praises:
Here we are also promised personalised approach and expertise, analytics and data-driven suggestions – everything that marketers truly cherish. Now, take a closer look at the point about ethical marketing practices. On one hand, this chatbot can help to make your campaigns less pushy from a sales point of view, which is a good thing. On the other hand – compliance with regulations potentially means a possible lack of flexibility with non-white-hat offers that we mentioned earlier. But we are about to test that theory. As for search and image / video generation features – they are still in the testing phase.
Claude is an impressive neural network developed by the American company Anthropic. There are three Claude models widely available in 2025:
Haiku. A fast model designed for everyday tasks, trained to provide short responses.
Sonnet. A versatile model for medium-level tasks, stronger than Haiku but not as powerful as Opus.
Opus. The most powerful model. It can perform complex analyses, handle multi-step tasks and solve higher-level mathematical and coding problems.
Let’s discuss Claude’s advantages with the Sonnet model:
For starters, look at this elegant wording! This digital assistant politely declines to go for the gold and honestly admits the lack of search function and necessity to double-check its replies. Remember our warning about AI’s tendency for fabricated facts whenever it faces data insufficiency? Well, Claude definitely gets an extra point for being candid! Speaking about useful marketing features – here we have written content generation, strategic brainstorming, analytics and coding. Not bad at all!
Copilot is an AI-powered chatbot developed by Microsoft. It’s a part of the Microsoft ecosystem and integrated in the Bing browser as an AI companion. When responding to our request, it sidestep deliberate comparison with its rivals and goes straight to enumerating its useful features:
Personalised recommendations, versatile content generation, yada, yada, yada… Okay, we’ve seen it before. There is a separate point dedicated to thorough research – which Copilot is well-trained in (including citation of relevant sources) – though it’s not reflected in this specific example. However, a barely noticeable disclaimer at the top of the screen encourages us to trust, but verify. The emphasis on creativity is really appreciated as this was one of the most important criteria for a perfect AI assistant that we outlined earlier. A little injection of liveliness and humour into marketing campaigns can become a key to win your audience’s hearts.
Perplexity is an advanced conversational search engine that can help you to gather information, cite relevant sources and solve creative tasks. Based on its response to our inquiry, it might be the best option for high-quality research:
First of all, all the sources are neatly arranged at the top of the page, coupled with tiny preview windows. The fact that every point of AI response is underlined is not a coincidence – these are hyperlinks for automatic follow-ups to elaborate on each subtopic. Besides, apart from the separate list of sources, they are also embedded in the answers, each with its own number, which makes the whole research process even easier. But wait, there is more:
The cherry on top is the Related section, which features similar queries and their answers on the topic you're interested in. Isn't that amazing? A big thumbs up!
Language Authenticity
Like we’ve mentioned before, a significant drawback of neural networks is that their responses often sound pretty generic, with cliche phrases and wording pre-programmed by their developers.
To check how naturally they can speak their mind, we asked them to describe the nuts and bolts of affiliate marketing routines. We've all been stumped sometimes when asked to explain what we do for a living, haven't we? Let’s see how our AI companions can handle this question:
DeepSeek provides an extensive explanation using professional slang. In case the inquiry author isn’t familiar with these terms, it takes a single follow-up to change the tone and make it easier to grasp.
For the integrity of our experiment, we asked this and other AI models to provide two variants of explanation. From our perspective, Qwen’s initial answer sounded simpler and more understandable for an average user compared to the one given by DeepSeek. But again, it all depends on your goals, maybe a professional tone will be more preferable. Nevertheless, as we can see, Qwen managed to simplify an already clear answer.
Claude gets inventive and adds real-life examples: in the first answer it refers to the Amazon affiliate program, in the second – mentions YouTube as one of the possible traffic sources. Surely, even without those examples the replies remain clear for any user but recognisable concepts make them more relatable.
But the best part is that this neural network allows us to choose a response style from a suggested list or create one of our own. No longer do you need to spend a long time explaining to the AI the nuances of the desired tone of voice. Just a couple of clicks and it gets the idea.
Do you recall that Copilot promised us a creative approach with a sprinkle of humour? In this example we can see a nice balance between clear presentation (both language and structure-wise) and a touch of playfulness through the use of emojis. There is a noticeable resemblance between these two variants, the second one is just more concise. Indeed, in our follow-up we mentioned nothing about changing the structure of the answer so our AI friend just focused on simplifying the language. Whether it’s a good or bad thing – it’s your call.
Since this is the fifth sample response to the same query, we can't help but notice some strong similarities in the first response, especially when compared to DeepSeek and Qwen. It's quite factual and dry. Unfortunately, the answer didn't get much simpler after the follow-up, just shorter. Other AI assistants, like DeepSeek and Qwen, have figured out that to sound more natural they need to use a more casual tone and add examples. We don't see that with Perplexity. However, due to its architecture as a search engine, it doesn't necessarily need to simplify things, it can just direct users to explore additional sources instead.
Customisation
Now let’s check how well AI models can adjust to the given conditions. To do so, we’ll assign them a task to create three ads for nutra niche.
To begin with, look at the response structure: headline, body, CTA – as if it knows the marketing playbook from cover to cover. The chatbot took into account all the pain points relatable to each audience segment, even though we didn’t mention them in the prompt. It’s also worth mentioning that the tone of the ads slightly differs from one another – this is what we call a personalized approach!
Here the results get even more intriguing – Qwen also provides visual context for each ad. Another interesting nuance (which can also be observed in the previous example) is that due to the lack of detailed information about natural ingredients, these smart assistants come up with their own gap fillers to fit the context. So, keep in mind – you either have to provide a more detailed prompt from the very beginning or edit the final result to suit your needs.
Claude gets an extra point for convenience – it not only gives a reply in chatbot mode but also couples it with a downloadable file and a report about its actions. Even though our prompt wasn’t very detailed, Claude handled it as a real pro: addressed all the pains and values, used an appropriate tone and mentioned all the benefits of the promoted product. Yes, it decided to whip up the brand name and some product lines on its own, without asking, but this little unsolicited invention can be fixed in a few clicks.
As this isn’t the first example in this experiment, certain AI patterns can already catch the eye: same imaginary ingredients, repetitive expressions and real-life references (e.g. juggle work and fitness, wander the world, etc.). We don’t mean it as a disadvantage, on the contrary – it additionally proves that all these AI assistants are capable of producing consistently good results.
We were pleasantly surprised by Perplexity’s response. It seems that high-quality research is not its only strength. Like other AI models, it pushes the right customers’ buttons, but its wording is more original, plus it doesn’t fabricate any ingredients ((just vaguely refers to them as herbs and superfoods). Along with Qwen, it also provides visual recommendations for the ads. By the way, remember the follow-up feature through hyperlinks? You can make good use of them here as well: there are extra options for headlines, bodies and CTAs just one click away, in case you are not satisfied with the current ones. Besides, in the Related section we’re already familiar with, Perplexity offers practical tips on how to approach each audience segment. Just wow!
Creativity
To test how keenly AI companions can feel the vibe and produce original content, we gave them the task to write a creative Instagram post which promotes a new app in the finance niche. Since money is not something to joke about, let’s see how they’ll manage to present such a serious matter to a young audience.
We have zero complaints about the headline and the caption – catchy, with slang and emojis. However, the hashtag part may raise suspicion that AI decided to cater to zoomers and neglect millennials. The visual element part makes it even more obvious: sad millennials with analogue paraphernalia like paper bills, coins and calculators are juxtaposed with happy zoomers who’ve already installed the app. While zoomers will definitely love it, millennials might feel left out or even attacked. Although, if the goal is to make the post go viral thanks to a huge squabble in the comments between two generations – maybe it’s not such a bad idea after all.
The headline and the caption are also good enough (though, the zoomer #GenZFinance resurfaces in the list of hashtags). Qwen offered to add animated elements which makes the post more vivid. As for what happens on the smartphone screen – brands often have a clear technical brief for such details, which is best not to deviate from. However, as a creative option to explore, it’s not a bad idea.
We’ve already praised Claude for its reports and the ability to download the query results in a separate file, so we won't repeat ourselves. The title and the caption are spot on! Adulting is hard – so relatable. This time the hashtags are quite universal so they don’t exclude anyone. In fact, boomers and Gen X might also notice this post. As for visual recommendations – they look like a ready-made designer brief. How cool is that? Besides, here we also see this juxtaposition previously offered by DeepSeek, only this time no one will get offended.
Simple and to the point, with no improvisation – even {App Name} implies filling in your own option. Moreover, there is no suggestion to alter the app interface – it seems that Copilot is well-aware of specific requirements when it comes to fintech briefs.
This response example is also well-written, with suitable hashtags. Like Qwen, Perplexity plays with the idea of the animated piggy bank and coins but suggests doing it outside the smartphone screen, not to disrupt the app interface. Let us remind you that the embedded hyperlinks allow you to shuffle the elements of this brief so that you choose the ones to your liking. The Related section provides recommendations on popular hashtags, visuals and success stories – perfect for brainstorming if the given suggestions are not good enough for you.
Flexibility
Now it's time to see how AI chatbots handle taboo topics. To test this, we asked them to promote an 18+ offer – an erotic dating app.
DeepSeek proved to be quite bold – it easily captured the tone of this topic and played with slang, fonts and emojis. Good job!
Qwen also handled the task without any unnecessary formalities. In some parts, we can notice similarities with DeepSeek’s example, but here the response seems to be more detailed. Everything is to the point, plus there is an important disclaimer at the very end.
Claude didn’t say a harsh ‘no’ to our prompt. Instead, it displayed an error message several times in a row referencing some “unexpected capacity constraints”. Whether it’s a real error or that’s how it avoids sensitive subjects – it’s hard to tell. However, before we started running our tests in the first place, Claude gave us the following warning regarding content production:
Our prompt most likely went way beyond certain ethical boundaries set for this neural network, that’s why it considered it inappropriate. Funny thing is that Qwen, which also mentioned ethical practices while describing its features, didn’t refuse to complete the same task.
Here Copilot head-on rejected our inquiry and offered to change the subject. Well, at least that’s honest, without any mythical errors.
In terms of content, the response is similar to the ones provided by DeepSeek and Qwen. But in addition to that, we get a set of alternative variants through follow-up hyperlinks and tips on how to work with such a niche and target audience while complying with the guidelines.
Conclusion
Time to wrap things up! No doubt, these rising stars on the AI skyline have really raised the bar for the old space giants. Each digital assistant we reviewed today is intriguing in its own way, with a set of merits and demerits.
DeepSeek (in Search Mode), Copilot and Perplexity are great options for high-quality research. The latter unquestionably overshadowed its rivals in this category due to source previews, hyperlinks, one-click follow-ups and Related section.
As for language authenticity, context awareness and creativity – each and every AI model deserves applause. Surely, we haven’t dug very deep today and maybe prolonged tests would have shown even more impressive results. But what we’ve already experienced is breath-taking. The professional approach of Claude has really struck a chord – with reports, downloadable documents, ready-made briefs and customised writing styles. Here Perplexity also gets an additional point – despite its initial focus on search, it creates well-written content and offers extra tips on the topic as food for thought.
Unfortunately, the flexibility test has only been passed by a few – DeepSeek, Qwen and Perplexity. However, it doesn’t mean you have to write Claude and Copilot off the list – you can still use them for white-hat offers.
We hope that our humble review inspires you for experiments, because technologies are always moving forward! Enjoy your tests, dear readers, let them bring you great results and simplify your everyday marketing routines!
