In a series of articles, we aim to present an ICP tokenomics framework that enables us to analyze the relationship between various factors influencing the supply and demand of ICP. This framework will offer a quantitative basis for assessing the state of ICP tokenomics over time and evaluating potential changes.
In this first article, our focus is on the demand for cycles, which are utilized to pay for operations on the Internet Computer (IC). By extrapolating the observed historical growth in cycle demand, we can estimate the required number of node machines in the IC network to support this demand.
Through a comparison of the current required and available nodes on the IC, we estimate that we currently have an excess capacity of approximately eight times the demand.
Based on the historical growth-rate factor of cycles, which stands at 4.76 year-on-year, we define three scenarios with low, medium, and high year-on-year growth rate factors. Under these scenarios, the projected number of nodes required on the IC will range from 8,000 to 200,000 node machines in six years’ time. The timeframe for a significant ramp-up of new additional nodes falls between the end of 2025 and the end of 2027.
ICP tokens can be used to pay for the usage of the IC. By converting ICP tokens to cycles, developers can pay for installing smart contracts, known as canisters on the IC, and cover the resources those canisters utilize (storage, CPU, and bandwidth). The conversion rate of ICP to cycles is pegged to a basket of fiat currencies (XDR), resulting in fluctuations based on the market price of ICP. This ensures predictability in the cost for developers to acquire fuel for running their applications.
Subnets & node machines
The IC consists of multiple subnet blockchains. Each subnet consists of some number of decentralized, independently owned and controlled node machines that run the software components of the Internet Computer blockchain protocol. Running multiple subnets in parallel allows for unlimited scalability of the IC. The Network Nervous System (NNS) plays a crucial role in coordinating the subnets by assigning nodes to specific subnets and determining the protocol version they should run.
Given the varying security, size, and feature requirements of different canisters, not all subnets have the same configuration. For instance, the system subnet hosting the NNS does not charge any cycles for its canisters as they should be accessible in all circumstances.
The Internet Computer (IC) currently comprises 35 subnets with 549 active node machines, and there is a total of 1235 available node machines. Most subnets are composed of 13 nodes, with a few exceptions. Notably, the NNS subnet consists of 39 nodes, the II subnet consists of 28 nodes, and the SNS subnet consists of 33 nodes.
The graph below illustrates the development of the burn rate in trillion cycles since the beginning of last year. We use trillion [T] cycles as the unit because 1 T cycles cost 1 XDR.
From the graph, it is evident that the burn rate has shown a significant and relatively steady increase over the analyzed time period. It’s important to note that the drop from Dec '22 to Jan '23 can be largely attributed to an efficiency improvement, specifically the introduction of timers. These timers allow canisters to perform periodic tasks at a lower frequency than heartbeats.
From Jan '22 to Apr '23, the amount of cycles burned increased by a factor of 7.04, which corresponds to a monthly increase factor of 1.14 (calculated as 7.04 raised to the power of 1/15) or a yearly increase factor of 4.76 (calculated as 1.14 raised to the power of 12).
Recalling our earlier analysis on the cycle burn-rate capacity of nodes on the Internet Computer:
- The current maximum burn-rate capacity of a 13-node subnet on the Internet Computer is 7,800T cycles per month, equivalent to 600T cycles per node per month.
- By implementing performance optimizations and enhancements in the cycle pricing framework, the burn-rate capacity could increase by a factor of 20 within 4 years.
- Assuming an average subnet utilization of 30%, the current average capacity of a node is 180T cycles per month, and the projected capacity in 4 years is 3,600T cycles per month.
For our analysis, we assume that burn-rate capacity grows via a constant growth factor from 180T cycles currently to 3,600T cycles in four years.
It is important to note that this analysis assumes no significant increase in the hardware performance of the node machines. This assumption is reasonable since the IC already operates on highly powerful node machines, and any hardware performance improvements are expected to be relatively small compared to the aforementioned enhancements.
Based on the historical observations from the previous section, we can derive estimates for the future growth of the cycle burn rate.
Several key factors influence the future cycle burn rate, including the increasing usage of existing operations, the introduction of new features, and potential pricing changes such as the implementation of charges for queries. Given the challenge of forecasting growth development accurately, we recommend applying a range of scenarios for the analysis. For our projection horizon, we consider the time period until May 2029, which is eight years after genesis.
Medium-growth scenario: In this scenario, we assume that the cycle burn rate will increase by a factor of 4.76 year-on-year, aligning with the observed historical growth.
Low-growth scenario: In this scenario, we assume a more conservative increase in the cycle burn rate by a factor of 3.5 year-on-year. To determine this factor, we sort the 15 monthly returns from Jan '22 to Apr '23, excluding the top 5 and bottom 5 values. The average of the remaining 5 returns is 1.11 month-on-month or 3.5 year-on-year. This represents a 25% reduction compared to the observed historical growth.
High-growth scenario: In this scenario, we anticipate a more accelerated increase in the cycle burn rate, driven by the introduction of new features such as the launch and operation of many SNS DAOs or the growing usage of chain-key Bitcoin. We assume a factor of 6 year-on-year, which is 25% higher compared to the observed historical growth and thus symmetrical to the low-growth scenario.
Using these scenarios, we can project the number of nodes required to support the projected cycle demand. We divide the projected monthly cycle demand of the IC by the average burn-rate capacity of a node, round up to the closest multiple of 13 as the assumed number of nodes in subnets, and then add the number of 80 nodes in system subnets for which no cycles are charged. It is important to note that this calculation could be further refined, for example, by including spare subnets to accommodate sudden increases in demand.
According to our calculation as of Apr '23, sustaining the current cycle burn rate of 13.3K T cycles per month would require 158 nodes. Comparing this to the current number of available nodes on the IC, which is 1235, we currently have a surplus compute capacity of a factor of 7.8 (1235/158).
The following graph depicts the required number of nodes at the end of the projected time horizon, May 2029, for the three selected growth scenarios (low/medium/high).
Based on the scenario projections, we can determine the point in time when the number of required nodes exceeds the current number of available nodes on the IC, which is 1235. This point in time is significant because it indicates when a significant increase in the number of new nodes will be necessary.
- High-growth scenario: November ‘25.
- Medium-growth scenario: September ‘26.
- Low-growth scenario: November ‘27.