Case study on multi AI model platforms

Introduction

Emerging AI chat platforms have begun advertising access to premium next-generation models– names like GPT-5, Claude 3.5+, or LLaMA-4 – to entice users. These offerings sound cutting-edge and often come with promises of unlimited usage or exclusive features. However, an in-depth investigation reveals a pattern of deception behind many of these claims. Users are frequently getting outdated models, proxy APIs, or repackaged fine-tuned versions instead of the advertised AI powerhouses. This report analyzes multiple such platforms (without naming them directly) and documents the tactics used to mislead consumers, along with technical evidence of these practices. The findings are organized into clear sections with supporting charts, logs, and tables, providing a comprehensive look at how these services operate.

Scope and Methodology: Researchers gathered data from official documentation, user forums (e.g. Reddit, OpenAI and developer communities), customer review sites (e.g. Trustpilot), and direct inspection of API interactions. Evidence such as network logs, response characteristics, and user testimonials were analyzed to identify proxy routing patterns, model fingerprints, credit schemes, and advertising discrepancies. All references are cited in-line for verification. No specific company names are mentioned; instead, we focus on the recurring deceptive behaviors across the industry.

Premium AI Models as Lures

Several platforms use the allure of unreleased or “premium” AI models as bait for paid subscriptions or sign-ups. They prominently advertise access to models that sound one generation ahead of what’s publicly available. For example, one promotion promised early access to “GPT-5 by OpenAI” and “Claude-Sonnet-4.5 by Anthropic”, alongside other exotic model names[1]. These labels invoke the prestige of OpenAI’s and Anthropic’s brands, despite such model versions either not being officially released or not generally accessible. The goal is to make users believe they’re getting a cutting-edge AI far beyond the standard GPT-4 or Claude-2 they might get elsewhere.

In reality, if an offer sounds too good to be true, it likely is. Often, the touted “GPT-5” or similar is nothing more than a rebranding exercise. The platform might be using a fine-tuned older model or even an open-source model with a fancy new name. In the example above, the mention of Claude-Sonnet-4.5 or GLM-4.6 appears authoritative, but these are not standard model names in official releases, indicating the platform itself coined them. This is a red flag that the models are custom or proxy versions, not the genuine next-gen AI the marketing implies. Indeed, users have reported that such models don’t perform at the level expected. In one community discussion, a user wrote “I suspect they’re routing to the lowest-tier GPT-5 model” – effectively saying the supposed GPT-5 felt like a watered-down version[2]. Another user agreed that the performance “does feel a bit GPT-0.5”, meaning it was so inferior it couldn’t possibly be a true advanced model[3]. Such feedback strongly suggests that the advertised model is misnamed, and customers are getting an older or smaller-capacity AI model under the hood.

Platforms also leverage implied endorsements by using terms like “OpenAI” or “Anthropic” in descriptions of their models. By claiming “GPT-5 by OpenAI”, a service insinuates it has an official or special arrangement, which is usually not the case. In reality, no independent service can legitimately offer GPT-5 access to the public at the time of this report – OpenAI’s next-gen models would be in closed testing or not released. Thus, any site claiming GPT-5 is either forwarding your requests to a hidden backend or using a surrogate model.

Proxy Routing and Model Substitution

Behind the scenes, many of these platforms function as proxies. When a user sends a query believing they’re talking to, say, GPT-5, the platform’s backend is often redirecting that query to a different AI model or API.

As shown above, the user interacts with the UI of the AI platform, which promises a premium model. But the platform’s server intercepts the request and routes it to a hidden endpoint – often the official API of an earlier model or a completely different provider. For instance, evidence from one scam site revealed that after users paid for “GPT-4/GPT-5” service, the web requests contained model=gpt-3.5 in the URL[4]. In other words, the site was literally using OpenAI’s GPT-3.5-turbo while pretending to be ChatGPT with GPT-4 or higher. Users only discovered this by inspecting the network traffic or noticing the URL parameter ?model=gpt-3.5 in their browser[4]. This is a smoking gun: the platform was simply a wrapper calling the cheaper GPT-3.5 model and passing the answers back to the user under a false label.

Another telltale sign of proxy usage is hidden in technical headers and logs. If one monitors the requests, they might see connections to official endpoints like api.openai.com or api.anthropic.com in the background. In a legitimate scenario, a platform that truly built its own GPT-5 wouldn’t need to call OpenAI’s API at all. Thus, seeing such calls is strong evidence of a proxy API in use. In our investigation, one platform’s backend logs (captured via a debugging proxy) showed an HTTP request with the payload specifying "model": "gpt-3.5-turbo" – directly contradicting the front-end claim that GPT-4/5 was answering. This kind of model substitution is often done without any disclosure to the user.

Even when not directly forwarding to an external API, some services host an open-source model fine-tuned to mimic a more advanced one. For example, a service might take Meta’s LLaMA-2 model, fine-tune it on some high-quality data, and then brand it as “LLaMA-4”. The naming is deceptive – users assume it’s a successor to LLaMA-2 or 3, but it’s really the same base model with minor tweaks. The output quality in such cases tends to give it away: it may lack the improvements a true next-gen model would have. One forum user noted significant quality degradation when a platform switched them to an unknown model mid-conversation, calling it “undisclosed model substitution” that altered the tone and capability of the AI[5][6]. This complaint, while directed at an official service, echoes the transparency issue prevalent in third-party platforms – users are not told when a different model handles their query. In deceptive platforms, this substitution is intentional from the start.

Outdated Model Fingerprints and Quality Tells

How can users notice that they’re getting an outdated model in disguise? There are often subtle and overt differences in the AI’s responses and behavior that serve as fingerprints of an older model. Experienced users of GPT-4 or Claude might immediately sense when a response “feels” like GPT-3.5 quality or worse. Key indicators include:

• Speed of Response: Advanced models with bigger neural networks (like GPT-4 or a hypothetical GPT-5) usually take slightly longer to generate replies due to their complexity. If a service claiming GPT-5 returns answers nearly instantly, that’s suspicious. In one case, users observed the purported GPT-5 on a platform was answering faster than even GPT-3.5 would, indicating it might be a smaller, faster model running behind the scenes.
  Figure: Comparison of average response generation time for a complex query. The platform’s supposed “GPT-5” answered in a fraction of the time it takes true large models (GPT-4 or a genuine next-gen model), suggesting it’s using a lightweight engine. Faster isn’t always better – in this context it hints at a less capable model.
• Depth and Accuracy of Answers: Users often report that the answers from these platforms lack the depth or accuracy expected of a cutting-edge model. For instance, GPT-4 is known for more nuanced and correct answers on complex topics. If the “GPT-5” you’re using makes basic mistakes or gives shallow responses, it’s likely not a real upgrade. One platform’s “GPT-5” was so unimpressive that a user bluntly stated “Don’t use GPT-5. It’s the dumbest model… it’s on par with 4o (an older variant). Even Claude is better.”[8]. Such comments underscore that the model didn’t behave like an improvement at all – it was arguably a downgrade.
• Known Limitations Resurfacing: Each AI model has known limitations or quirks. For example, if the service claims to offer an advanced Claude model but it still shows the exact same weaknesses as Claude 1 (older version), then it likely is the older version. In an FTC complaint, a user who subscribed to a “Claude Pro Max” plan expecting higher limits and performance found that “nearly every session ends after just a few responses due to internal errors or silent cutoffs”, despite the plan promising 10× higher usage[9].
• Model Self-Identification: In some cases, users have tried directly asking the AI what it is. While a deceptive platform could intercept or script the answer, occasionally the underlying model might reveal itself. For example, one might ask “What model or version are you?” A genuine GPT-4 or GPT-5 might have a certain way of responding, whereas an older model might answer differently. In one community report, a user noticed that no matter which model they selected in the interface, the AI eventually admitted it was “GPT-5” responding (likely because the platform forced that answer)[5]. The consistency and honesty of model identification can therefore hint if something is off.

Misleading "Unlimited" Plans and Credit Restrictions

A common advertising strategy is to boast “Unlimited” usage of these AI models. Many platforms entice users with tags like “Unlimited GPT-4 chats” or “No cap on requests” for a flat subscription. However, upon closer inspection, these claims are often exaggerated or outright false.

Hidden Daily or Hourly Limits: Some services do grant “unlimited” access in the sense of no pay-per-request fees, but they implement quiet rate limits or quotas. One user who paid for a year of an “unlimited” AI writing plan reported “I barely got started... when I was told I had to quit for the day. So, not very unlimited.”[11]. This practice is seen across various platforms: they advertise no limits to attract customers, yet in the terms or in practice they enforce message limits, time-based resets, or throttle the response speed.

Credit Systems in Disguise: Other platforms use a credit system but mask it behind “unlimited for subscribers”. For instance, they give new users a certain number of free tokens or credits (say, a “$200 credit” as a signup bonus[12]) to suggest a huge value. In reality, those credits correspond to a finite number of uses. Once you exceed the “fair use” amount, you might start experiencing declined requests or prompts to buy more credits.

User Experience Issues: Credit Traps, Cancellation, and Support Evasion

Beyond the technical misrepresentations, these deceptive platforms often engage in shoddy business practices that trap the user financially and emotionally:

• Credit Traps and Automatic Billing: Once a user has signed up, the platform may start charging on a schedule without clear consent. Many users report difficulty cancelling these subscriptions.
• Inability to Export Data or History: Users might realize they cannot export their chat history or content. Scams and low-quality services rarely bother implementing this.
• Support Evasion: A hallmark of scammy operations is non-existent customer support. Users have recounted sending multiple emails with zero response[16][17].
• False Advertising and Impersonation: Some platforms actively impersonate the branding of more reputable services, leveraging trust to steal users[15].

Technical Evidence and Comparisons

To solidify our findings, this section presents a few visual comparisons and technical proofs gathered during the investigation.

Conclusion and Recommendations

Our investigation reveals a disturbing trend of deceptive practices among certain AI platforms advertising “premium” model access. They exploit the hype around the latest AI while secretly serving up older or smaller-scale models. They lure customers with promises of unlimited usage and breakthrough capabilities, yet impose hidden limits and deliver subpar performance.

Key Findings Recap:

• Model Mislabelling and Proxy APIs.
• The “Unlimited” Myth broken by hidden quotas.
• User Traps making it hard to leave.
• Quality Discrepancies showing signs of older-generation output.

Impact on Users: The consequences for users caught in these schemes range from financial loss to wasted time and potential misinformation.

In conclusion, while the allure of “next-gen AI for cheap” is strong, both users and honest developers must navigate carefully. The Aibs Technology Research Team will continue to monitor this space and advocate for transparency and integrity in AI services.