The recent update to AI Autoblogger upgraded the default Anthropic Claude Sonnet model to version 4.5, the latest and most capable release yet. However, the “OpenAI GPT” option still defaults to GPT-4.1-2025-04-14 instead of the newest version, GPT-5.
At first, this may seem odd – why not switch to the latest OpenAI model? But it’s neither an oversight nor laziness. It’s a deliberate engineering decision to ensure your campaigns run smoothly, regardless of the “experimental genius” that OpenAI rolls out next.
What would happen if we just switched to GPT-5
If GPT-4.1 was silently replaced with GPT-5, all existing user campaigns would suddenly start generating empty results – the plugin would simply stop posting new articles across your autoblogging networks. The issue wouldn’t be with the plugin itself – it’s baked into the OpenAI model.
GPT-5 belongs to a class of reasoning models that spend part of your paid tokens on internal “thinking” before producing an answer. Users can’t see or control how many of these tokens are used, yet they’re billed for them anyway.
When “thinking” eats your entire token budget
Predictably, if you set a generation limit too low – say, around 1,000 tokens – GPT-5 may spend most or even all of it on internal reasoning, leaving nothing in the output. In such cases, the log will usually end with: “Finish reason: length.”
Increasing the token limit sometimes helps – doubling it, for example, might finally produce a result – but that also doubles the cost. There is no guaranteed threshold at which GPT-5 will always succeed. It simply requires a much larger token budget to operate reliably.
GPT-5 often consumes two or more times the tokens (and therefore the cost) of GPT-4o or GPT-4.1 to produce a similar result. For large-scale autoblogging, this inefficiency quickly becomes unsustainable.
A bigger issue is that OpenAI never discloses how the proportion of reasoning tokens is calculated in the final bill. Users only see the total number of tokens consumed and have no way of knowing how many went toward generating actual text versus internal model processes. This makes cost prediction nearly impossible, turning GPT-5 usage into a financial roulette.
Where transparency matters more than freedom
Unlike AI Autoblogger, CyberSEO Pro and RSS Retriever plugins don’t use fixed lists of models. Users can directly enter the ID of any supported model (AI engine), such as openai-gpt-5, gemini-2.5-flash, or xai-grok-4-latest. While this flexibility gives you more freedom, it also poses more risk. You may connect to the latest model and end up dealing with bugs, empty responses, or unpredictable token costs.
OpenAI is transparent enough to state in its documentation: “Reasoning tokens are billed as part of output tokens.” However, it never clarifies what percentage of tokens go to reasoning. According to U.S. law (FTC Act §5), this could be considered a material omission – a significant lack of disclosure that misleads consumers about what they’re paying for.
It’s like buying a “100% beef” burger, only to later find out that most of it is soy protein. The label looks honest, but the substance isn’t.
Until OpenAI discloses the token structure – specifically, how many tokens are allocated to reasoning versus actual output – using GPT-5 will remain economically opaque. Users can’t verify what they’re paying for or accurately estimate the real cost of a finished result.
What to choose and why it matters
GPT-5 has obvious limitations: it’s slow, expensive, and unpredictable. For large-scale autoblogging, where stability, speed, and reliability are paramount, these limitations are a serious issue. Long response times can cause server-side timeouts, which can break entire publishing workflows.
Stick with GPT-4.1, GPT-4o, or GPT-4o mini if your goal is to generate consistent content and use tokens predictably. These models are still the best choice for autoblogging because they are fast and efficient. When prompted wisely, they can produce natural, human-like text that easily passes AI detectors.
GPT-5 is better suited for experiments or niche scenarios, not production-level campaigns. They’re slower, more costly, and unpredictable enough to halt automated publishing altogether. That’s why AI Autoblogger continues to rely on GPT-4.1 by default – not out of conservatism, but out of rationality. It simply makes more sense to pay for content than for artificial “thinking.”
