Fable 5 Returned, GPT-5.6 Was Hidden Behind a New Lineup, and Gemini 3.5 Is Delayed: The Race Has Become Almost Incomprehensible to Users
How can a user choose between Fable 5, GPT-5.6, and Gemini 3.5 when the model race becomes almost impossible to follow?
Choose among Fable 5, GPT-5.6, and Gemini 3.5 through a real use case, access, price, and stability rather than a confusing naming hierarchy.
What to watch for
Key takeaways
The working conclusion from “ToTheMoon tonight” is that technical progress continues, but the main problem is that understanding AI agents today is harder than launching one: every company has its own names, modes, and limits, a model may be available in the morning and restricted in the evening, and the user becomes a manager of product experiments.
In the context of “Claude Code, Claude Cowork and various ways of working with Claude,” this criterion applies: the value is not the number of interfaces but reliable work with clear limits and control; more ways to use Claude help only when they reduce the burden of managing versions rather than adding to it.
The boundary of the “Claude Science: an AI tool for scientific work” case is defined by this point: a science tool proves itself when it produces a verifiable, reproducible result a researcher can confirm, not in a striking demonstration.
The discussion of “How to deal with the AI agents” yields a practical test: every company has its own names, modes, limits, and interfaces, and a model can be available and then restricted, so the user becomes a manager of experiments, and the practical move is to split tasks across tools.
For the “Claude Fable 5 is reopened: What happened?” scene, the decisive point is this: the return solves the current problem, but the shutdown already revealed dependency risk: a team could move a project onto the model and then lose access, with no guarantee of the next release.
The boundary of the “How the tokens flow in different models” case is defined by this point: tokens are consumed differently and sometimes disappear almost instantly, so the comparison should be not the plan price but how much of a project you finish before the limit and how much manual work remains.
The practical meaning of “Sol, Terra, Luna: new ChatGPT-5.6” is that splitting into flagship, balanced, and fast versions may simplify internal economics but adds more names to understand, and the most powerful model does not necessarily receive broad access right away.
The working conclusion from “Why is Google holding Gemini 3.5 Pro” is that Google delays and limits use even among large partners because infrastructure is finite, so it is sensible to split tasks — run one project in Fable, another in Codex, and send quick operations to a cheap model.
What this episode is about
Claude is available again, OpenAI divides GPT-5.6 into Sol, Terra, and Luna, Google restricts capacity, and tokens disappear within minutes. Technical progress continues, but the market’s main problem is that people have to manage versions, limits, and agents instead of simply solving a task.
Understanding AI agents today is harder than launching one. Every company has its own names, modes, limits, and interfaces. A model may be available in the morning, restricted in the evening, and restored several days later. The user becomes a manager of product experiments.
Fable 5 was reopened, but the shutdown already revealed dependency risk. A team may have moved a project to the model and then lost access. The return solves the current problem without guaranteeing the next release.
Tokens in Codex and Claude are consumed differently and sometimes disappear almost instantly. A nominal subscription explains the true cost of a large task poorly. The useful comparison is therefore not the plan price, but how much of the project can be completed before a limit and how much manual work remains.
OpenAI is releasing GPT-5.6 while creating a Sol, Terra, and Luna lineup: flagship, balanced, and fast versions. This may simplify internal economics, but it adds more names for a person to understand. The most powerful model does not necessarily receive broad access immediately.
Google is delaying Gemini 3.5 Pro and limiting use even among large partners because infrastructure is finite. In real work, separating tasks is sensible: run one project in Fable, another in Codex, and send quick operations to a cheap model. The winner of the race has not yet been determined. The user loses when product complexity grows faster than utility.
The winner of the race has not yet been determined. As a result, the user loses when product complexity grows faster than utility.
Episode transcript
The episode is in Russian; below is an English reading guide to the transcript (the full EN transcript is a machine translation). Voice matching applied to 94 segments: 45 identified, 2 mixed, 21 probable, and 26 unresolved.
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