It is very easy to set up Baikal Giant+ with Nicehash. We will discuss all the specifications of this miner and profitability with Nicehash.
About Baikal Giant+
Baikal Giant+ is a Multi-algorithm miner including 7 algorithms such as X11, X13, X14, X15, Quark, Qubit. This miner can give a maximum hash rate of 2Gh/s for a power usage of 450W. Model Giant+ is very popular this year many flocks of miners shifting to new algorithms. Baikal Miners are in high demand since they are also profitable with Nicehash. According to Nicehash, You can make 13.86 USD by providing your computational power to them.
Baikal Giant+ Specifications
- Manufacturer: Baikal
- Hash Rate:2GH/s with a variance of ±10%
- Dimensions:125 x 140 x 300mm
- Weight: 2980g
- Noise: 65db
- Power: 450W
- Fan: 1
- Interface: Ethernet
For more information about Baikal visit its official Website
Before starting with the process of setting up Baikal Giant+ you have to consider some initial steps below,
- Warranty card should not be damaged. In case, warranty sticker is not placed or damaged you can get a new Miner from Baikal.
- All the cables should be inserted very properly.
- Check that all the fans are working properly without any damages.
How to set up Baikal Giant+ with Nicehash?
- Connect the device with PSU via PIN Ports available in your miner.
- Insert your Ethernet cable and complete the connection process.
- Now lets come to mining guide, we have to configure your Baikal Giant+ Miner with Nicehash pool and worker.
- Create an account with Nicehash.
- Set this pool URL for your Miner – stratum+tcp://x11.eu.nicehash.com:3336
- Username as YourBitcoinAddress and Password.
- Start Mining.
- If you have any questions then you are free to comment.
We have discussed the process to set up your Baikal Giant+ with Nice hash and full specifications of this miner. In my opinion, this miner is no more profitable to mine with Nicehash. Meanwhile, you can mine some other profitable coins on this miner and there are various options to mine as this miner supports 7 algorithms.