Rolling bearings operated at small oscillation angles or exposed to vibrations during standstill show typical damage after only a short period of operation. This can be false brinelling damage, so-called standstill marks or classic fretting damage (fretting corrosion, tribo-oxidation). It is important to differentiate here according to the amplitude-ratio x/2b, which indicates the ratio between the rolling element Motion (x) and the Hertzian contact half-axis (b). Depending on this ratio, suitable laboratory test methods must be used to test the lubricating grease practically for the particular application. For this purpose, the Fafnir wear test, according to the standard of the American Society for Testing and Materials ASTM D4170, is also listed in the current high-performance multi-use specification of the National Lubricating Grease Institute (NLGI) as a release test for lubricating greases. In Europe, the SNR-FEB2 test is frequently used, which is also required to release greases in the blade bearings of wind turbines, among other things. In the case of standstill marks due to very small oscillation angles or vibrations, the Mannheim Tribology Competence Center (KTM) has developed a special test now established in the industry. The oscillating angles vary in these three different standard tests in the range from ±6° in the Fafnir test to ±3° in the SNR-FEB2 test to ±0.5° in the KTM standstill marking test; the x-to-2b ratios range from 5.5 (Fafnir) to 3.4 (SNR) to 0.5 (KTM). This paper will explain the scientific basis for these special operating and test conditions and compare test results of specially prepared model greases in these three standard rolling bearing tests, two test variations and a classical fretting test under oscillating sliding friction (ASTM D7594). The paper’s main objective is to show that the suitability of grease for such an application depends strongly on the prevailing operating conditions. Different tests in this field are, therefore, not interchangeable. Good results in one test do not automatically mean good results in a similar test at first glance. Therefore, selecting the right test for the application is important.