These days I have been in frequent conversations with people who have good insights into schools of levels and linearization in contemporary CGE models. Some thoughts are derived from our discussions. These are things at least I would think that have created somewhat communication barriers between schools of CGEMs and NQTMs. One thing that initially draws my attention was due to an argument that linearization is indifferent to implicit or explicit preferences ’slash' technologies. But perhaps before we even think about theories and computational strategies we may want to ask how less good were computers if we all step into a time machine and go back to 20-30 years ago. At that time, an empirical solution in levels might have been much more challenging than it is now today. A mathematical algorithm that crawls toward the solution with a series of linear approximations was probably much more robust. With advances and innovations in the technology of computer advancement, however, all have become ancient history. This probably means that for a less extensive collection of CGE models there is no need to do approximations and the exact hat calculus would be the suitable candidate to calculate counterfactuals. This then makes sense that majority of the school of NQTM modelers do not use the GEMPACK software which typically comes up with solution to errors associated with linearization to iterate the linearization over and over until a new solution in levels is achieved. Pioneers of CGEs have developed this strategy to solve large general equilibrium trade models (e.g., huge contributions to CGE due to Johansen, Dixon and Hertel). If the schools of CGEs and NQTMs ever found a way to communicate, then the CGE modelers would likely explain that they actually obtained the levels solution with the so-called iterative linearization procedure, then undoubtedly NQTM modelers would question why CGE modelers do it that way. The fact is probably that the linearization representation with GEMPACK indeed has their own advantages in solving large CGE models (e.g., see IMPACT working paper), while some younger generations of CGE economists have been locked into this tradition, but similar to what the IMPACT working paper (revised version published in Economic Modeling) argues, with contemporary advances in computers and softwares we might tend to have less need to do approximations (e.g., Johansen matrix inversion) if levels solution is becoming inexpensive and more reliable.