The G.skill Trident Z5 Neo RGB series was made mostly for the AMD AM5 platform, including AMD's EXPO profiles that will give users the best possible speed results combined with the highest possible stability. G.Skill has chosen Hynix as their memory modules supplier, and the final result is brilliant. The F5-6000J3038F16GX2-TZ5NR is a 2X16GB memory kit that supports 6000 CL30 at 1.35V for the AMD platform.

The retail package is complete, and you will find inside the two modules and a small printed manual. In order for this memory kit to work best you need to enable EXPO profile under your motherboard bios and press save, everything is ready now. While using the stock 6000MHz CL30 memory speed, we didn't notice any problems or stability issues.

The best part comes from the fact, that Asus has included memory presets for Hynix memory kits, and with a simple click you can boost this memory module up to 6200MHz CL32 with 1.40V. This mode also will give you better performance, in all cases, compared with the stock 6000MHz CL30 EXPO setting, a nice free upgrade.

The biggest performance upgrade will be if you decide to further overclock your G.Skill memory kit. While it seems complicated, there are many different guides (Youtube, Forum) around the Internet to help you with this. We did manage to boost the stock 6000MHz CL30 with tighter timings and got significant memory performance.

As always, great performance comes with a great price. The G.Skill Trident Z5 Neo RGB 6000MHz CL30 cost around ~$200, which is much higher than other 6000MHz memory modules we have tested that also include Hynix memory modules. However, the G.Skill overclocking was better and in numbers, we got better performance. Concluding this review, we have to say that the F5-6000J3038F16GX2-TZ5NR is a great memory kit, pricey, and with good overclocking potential. G.skill has a lifetime warranty for all their products, so you don't have to worry about it. Great work from G.Skill and we are waiting with excitement for their next product that will further boost cache latencies and overall memory size.