I appreciate the long reply (no sarcasm) and the compliment regarding the salary haha (it makes for a nice aspirational goal, to have good total comp). I probab

I appreciate the long reply (no sarcasm) and the compliment regarding the salary haha (it makes for a nice aspirational goal, to have good total comp). I probably can't respond to the whole post but feel like we can come to an understanding. You mentioned 10_000 perceptibly parallel tasks so I threw together a small example - what if we had 10_000_000 concurrently executed tasks instead? This takes 1.2-1.5GB of RAM to run but it can give you a good showcase that .NET ThreadPool can take a lot of punishment and this is far from the worst you could see in one enterprise codebase or another: var tenMillionTasks = Enumerable .Range(0, 10_000_000) .Select(async i => { // Force the yield - this way the methods will continue the execution // in the form of scheduled continuations (work items), so that we pay // for context switching too, similar to a more realistic scenario. await Task.Yield(); for (var j = 10_000; j >= 0; j--) { // This is an okay proxy for doing some work since the // JIT is fairly conservative and won't auto-vectorize this // because its computation budget is prioritized on more impactful // optimizations like inlining, CSE, devirtualization, etc. // (this is completrly compensated by portable SIMD API) i++; } return i; }); // Scales linearly with the number of CPU cores var results = await Task.WhenAll(tenMillionTasks); var average = results.Average(); Console.WriteLine($"Done! The avg is {average}"); You can try it yourself if you're interested. To do so you can get an SDK from https://dot.net/download https://dot.net/download, execute 'dotnet new console', paste the code to Program.cs and then execute 'dotnet run -c Release'. This is more stressing to the runtime and is likely more fair than another comparison posts a year ago or so here on HN where that evaluated various runtimes by having the task simply wait for a period of time. Nonetheless, you can replicate that too by adding 'var delay = Task.Delay(TimeSpan.FromSeconds(5))' before tasks variable and replacing the lambda passed to .Select with 'async _ => await delay' to see how small the task overhead is.