Tag Archives: cryptocurrencies

Top 50 of Crypto Mining – June 2019

Today, June 14, 2019, we released the second biannual list of Top 50 cryptocurrency mining pools.

We do this in conjunction with the Top 500 supercomputing list that is released twice a year, in June and November. That list has been a matter of national pride for the US, Japan, China, and many other countries.

Cryptocurrency mining is a specialized form of supercomputing, producing billions of dollars of economic value per year.

In the Information Age, money has become information. Bitcoin is energy converted to information and encapsulated as secure immutable transactions on a time chain. This is money in the Internet, that we call Money 3.0. Currently it is primarily a store of value, a sort of digital gold, but it continues to grow use cases as a medium of exchange, and unit of account.

Cryptocurrency mining operations are large-scale, run on clusters, but also consist of highly decentralized pools that anyone can join and contribute their equipment to the effort, for proportionate rewards. Most mining is done on custom ASIC computing rigs, highly optimized for the relevant crypto consensus algorithm.

Using statistics readily available on the hashing rates and block production rates for the large mining pools, we can tabulate the economic value produced by these pools.

We consider only mined coins, that is, those that use some type of Proof of Work algorithm such as Bitcoin’s Nakamoto consensus.

We do not consider coins created with other types of consensus mechanisms, since they require no significant supercomputer-class computation. This includes coins produced through premining, Proof of Stake, distributed Byzantine Fault Tolerance and the like since supercomputing resources are not involved.

While there are a number of lists that provide hash rates and block production rates for pools mining a single coin, our lists are the first aggregation of which we are aware.

This raises the question as to how to compare mined coins that have radically different hashing rates and whose consensus algorithms, although often similar to Bitcoin conceptually, differ in the details.

We settled on the economic value of the mined coins that are produced. This enables us to make comparisons across coins when rank ordering the list of mining pools.

We compare the dollar value of a day’s mining from a given pool, with that of other pools, across the top eight mined cryptocurrencies.

The top 10 mined coins have market caps above $0.5 billion dollars, and the #1 coin, Bitcoin, as of our snapshot taken on May 30, 2019, had a market cap of $154 billion.

When we rank order the top 50 mining pools we find that the top eight mined coins in economic value are: Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC), Bitcoin Cash (BCH), Zcash  (ZEC), Bitcoin SV (BSV), Dash (DASH), and Monero (XMR). All of these except Monero are ASIC-friendly, and production is dominated by ASIC miners and clusters. Monero relies on GPUs.

For Bitcoin, Ethereum, and Litecoin we have used 30 day averages as of May 30, 2019 for block production and hash rates; for the other coins 7 day average data was available.

From Table 1  below, which is across all pools, not just the Top 50, we see that total annual economic value run rate (extrapolated from the recent average daily values) is about $8.6 billion. About 2/3 of the economic value created is from Bitcoin production alone, with about $15 million produced per day recently. Ethereum amounts to around one-quarter of that at almost $4 million per day. The next six coins add another $4 million daily. Overall around $24 million per day is currently being mined from all pools.

Table 1: Top 8 Mined Coins (all mining pools, not just Top 50)

Coin Algo New / day Hash Rate Price 5/30/19 US$ Mined per Day M$ Yearly M$
Bitcoin SHA256 1800 47.1 Exa 8701 15.662 5,717
Ethereum Ethash 13,600 172 Tera 284 3.862 1,410
Litecoin Scrypt 14,825 352 Tera 118 1.743 636
Bitcoin Cash SHA256 1800 1.36 Exa 469 0.844 308
Zcash Equihash 7200 4 Giga 87 0.626 228
Bitcoin SV SHA256 1800 2.03 Peta 222 0.400 146
Dash X11 1693 1.68 Peta 172 0.292 107
Monero CryptoNight 1934 329 Mega 95.1 0.184 67

23.61 8,619

The locations of top mining pools can be multi-country. The next Table summarizes the major host countries for the Top 50 pools; China, the US, and Hong Kong account for 70% of the top 50 pools and almost all of the top 10 operators. China alone is responsible for nearly half of the annual value produced by the Top 50 pools. The Mixed category includes various combinations of US, China, the EU, Russia, or other Asian or European countries. This category has grown as Chinese operators begin to move to other geographies, as a result of pressure from the government to constrain cryptocurrency mining in China.

Table 2. Host Countries, Top 50 Pools

Country # Top Pools Daily M$ Annual M$
China 18 10.717 3911.7
US 11 4.77 1742.5
Hong Kong 6 2.77 1009.6
Mixed 12 2.69 980.4
Other 3 1.18 430.0
Totals 50 22.12 8,074

Table 3: Top 10 Pool Operators (aggregated results)

MultiPools Coins Number Daily M$ Annual M$ Country
BTC(dot) com BTC, BCH 2 3.06 1115 China
F2Pool BTC, ETH, ZEC, BSV, LTC 5 2.76 1007 China
Antpool BTC, LTC, ZEC, BCH, DASH 5 2.38 868 Hong Kong
Poolin BTC, ZEC, LTC, BSV 4 2.26 825 China
SlushPool BTC, ZEC 2 1.62 592 US
BTC.Top BTC, LTC, BCH 3 1.47 537 China
ViaBTC BTC, LTC,BCH 3 1.34 488 US
Huobi.Pool BTC, ETH 2 0.69 251 China
NanoPool ETH, XMR 2 0.50 182 US, EU, Asia
Bitcoin(dot)com BTC, BCH 2 0.34 124 US
30 16.41 5,990

We have aggregated, for the top 10 operators, their results across all of the top eight coins, and summarized in Table 3. Some operators mine two different coins, others mine as many as five of the top eight. These pools account for, when broken out by coin, 30 of the entries in our Top 50 list. 

The #1 operator is BTC.com based in China, and it produces $3 million a day of economic value. F2Pool, Antpool, and Poolin each produce over $2 million of cryptocurrency per day. These  large operators are responsible for $6 billion of the $8 billion annual production by the top 50 pools. Three of the five largest operators are in China, one is in Hong Kong, and one is in the US.

The winners in this race, for this second list, are Bitcoin, naturally, with BTC.com again as the top pool, and China as the host country for the most top mining pools, including both #1 and #2 positions. Hong Kong has the #3 pool. The US has the second largest number of mining pools.

The economic value of mining has increased substantially. In the first list of November, 2018 we looked at the Top 30 pools, responsible for some $5.5 billion of annual run rate of mining. This new list of Top 50 pools indicates $8.1 billion of annual cryptocurrency creation (even the Top 30 for this list amounts to well over $7 billion).

We intend to update this list again in November, 2019. Suggestions and comments may be sent to: stephen.perrenod@orionx.net

A presentation with the full Top 50 list is available at SlideShare.net


Overall: coinmarketcap.com, coinwarz.com, cryptoslate.com

BTC: btc.com 

ETH: btc.com, etherscan.io

BCH: btc.com, cash.coin.dance 

LTC, ZEC, XMR, DASH: miningpoolstats.stream

Cryptocurrency topics: orionx.net/blog


Central Bank Digital Currency is not Cryptocurrency as Envisioned

Recently the International Monetary Fund produced a research report on Central Bank Digital Currencies, titled “Casting Light on Central Bank Digital Currency”, and available here:


Even the title is interesting in its omission of the terms cryptocurrency and blockchain.

The basic concept they were evaluating was that of central bank controlled digital currency issued for the benefit of retail users (individuals and non-banking businesses). These would exist alongside existing fiat currencies and be intended for domestic use primarily. Their value would have to be tethered to the related fiat.

The study reached several initial conclusions:

  * CBDC could be the next milestone in the evolution of money.

  * It is a digital form of fiat money, issued by the central bank.

  * The ability to meet policy goals is one major issue.

  * The demand for CBDC depends on the attractiveness of alternatives (cash, e-money).

  * The case for adoption could vary from country to country.

  * Appropriate design and policies should help mitigate risks.

  * Cross-border usage would raise a host of questions.

A number of central banks around the world are studying CBDCs. This table from the IMF report indicates their publicly stated rationales, which include diminishing use of cash as other payment channels e.g. mobile become popular, efficiency gains for payment and settlement, and greater access for the unbanked or lightly banked to financial services.


But the key point is that CBDCs are quite antithetical to Bitcoin and mined cryptocurrencies in general (we exclude in this comparison airdrops, premined, and other largely centralized, but private, forms of cryptocurrency). CBDCs are closest to the tethered cryptos, but maintained by the fiat issuing authority itself.



Created by miners running hashing protocols Created by central bank
Predefined monetary policy Variable monetary policy set by central bank committee
Transnational usage Domestic usage primarily
Open triple entry ledger Central bank permissioned ledger
Validation by private computer nodes Validation by central bank

There is very little in common between Bitcoin and mined cryptocurrencies in general, and hypothetical CBDCs. Most existing fiat is already digital; a small portion is cash.

The main new alternative, besides existing fiat cash, for CBDCs are private payment channels (private e-money) such as PayPal and M-Pesa in Africa. These are similar to stored value cards with prepaid fiat balances, but with mobile interfaces. Here the account balances are managed by private companies, usually with a known partner, and a user needs to trust the company holding the balance.

Both new private money channels and CBDCs threaten to disintermediate balances held in bank checking and savings accounts. So do cryptocurrencies, of course.

These balances are used as reserves for banks to issue loans, so if they were moved to a cryptocurrency or a central bank ledger they are no longer available for lending (fractional reserve banking).

A fundamental difference is that cryptocurrencies are assets whereas fiat money is debt-based, created when banks issue loans. CBDCs in their basic form are not available as reserves for bank lending.

CBDCs would in essence just be a different form of fiat, tethered to fiat, and with the same accounting unit and value.

Cryptocurrency represents a challenge to the banking system and to central banks. It seems that the IMF may be encouraging central banks to sacrifice the interests of banks in order to maintain, and even increase, their own power.

The CBDC framework, like cryptocurrency, would move deposits away from the banks. Unlike cryptocurrency, which holds balances on an open ledger, accessed by private keys, CBDC balances would be held for individuals and businesses at the central bank. This means the central banks would be able to restrict access to funds owned by individuals. One can assume they would do this during crises or under court order.

Central banks could even apply interest to CBDC deposits, possibly even with negative interest rates during times of slackened growth.

Fractional reserve banking and the economy as a whole are based on the provision of credit by commercial banks, backed only by a small percentage of reserve balances held with the central bank. If deposits move in large amounts to CBDCs or cryptocurrencies, both of which are assets in the name of the depositor, the system of credit provision in the economy will have to be significantly transformed.

Or a system that allows banks to participate and hold reserves based in CBDC would have to be developed.

CBDCs of the simplest type discussed in this IMF paper seem like a way to protect the prerogatives and increase the power of central banks, and co-opt cryptocurrency. The losers would be traditional banks because their lending power would be decreased.