u/Anxious_Check_6147

It’s been something of a mantra for a while now: use a frontier model for planning, then delegate the implementation to low-cost models, and finally verify the implementation using the frontier model (and then ask the cheap one to do the corrections)

I’m not saying it isn’t the best approach, but speaking from my own experience… I have my doubts.

Let’s say GPT-Sol Medium (or Terra High) are my planner models, and something like DeepSeek V4 Flash or Gemini 3.7 Flash handles the implementations. What I’ve noticed with this workflow is that the number of correction rounds resulting from the review is often enormous, no matter how clear the plan is. In this scenario, I end up burning ‘expensive’ tokens on planning and the review rounds, whilst also burning cheap tokens (which also add to the cost) through constant implementation and correction, which ultimately amounts to a waste of time and money.

So now I’m trying a different approach: once the planning agent has defined the plan, why change it? That agent already has the context to implement it in a single shot and, if anything, I have the implementation reviewed by a couple of low-cost agents. I know it sounds counterintuitive, and I don’t have any large-scale data to back up this approach either, but my feeling is that it works better for me.

TL;DR;

I don’t think this is the most likely scenario, but it is possible, and it would make sense: the threat of a price rise is a trial balloon designed to trigger spikes in usage and test the capacity of their systems.

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If DeepSeek has a serious capacity issue that has come to light due to the surge in usage caused by the community’s enthusiasm for the improved version of DeepSeek V4 Flash, DeepSeek had two options:

• Announce and implement the price increase straight away.
• Say nothing, and announce it once they had something concrete and finalised, or when V4 Pro GA was released.

What this vague and unspecific announcement achieves is that people are now in ‘let’s use DeepSeek as much as possible whilst it’s still cheap’ mode, which is, in fact, causing an even greater overload on the servers than if they hadn’t announced the increase at all.

So what if DeepSeek has used this almost intimidating message about the price rise to test its systems ahead of the V4 Pro GA release and hasn’t actually decided whether it will actually implement the announced price rise?

After all, despite V4 Pro’s larger size compared to version V3.2, the inference cost, according to research papers, appears to be lower than that of V3.2 due to the optimisations they’ve implemented.