AKT: Akash Network Token & Mining Economics
Greg Osuri, Adam Bozanich∗Akash Network, Akash Network(Dated: January 31, 2020)
Akash is a marketplace for cloud compute resources which is designed to reduce waste, thereby
cutting costs for consumers and increasing revenue for providers. This paper covers the economics of
the Akash Network and introduces the Akash Token (AKT). We describe an economic incentive
structure designed to drive adoption and ensure the economic security of the Akash ecosystem. We
propose an inflationary mechanism to achieve economic goals. We provide calculations for mining
rewards and inflation rates. We also present mechanisms for allowing a multitude of fee tokens.

ACKNOWLEDGMENTS

We thank Sunny Aggarwal (Research Scientist, Tendermint), Gautier Marin (Tendermint), Morgan Thomas (Co-Founder, Kassir),and Brandon Goldman (Frm. Lead Architect,
Blockfolio) for providing valuable commentsthat significantly improved the manuscript.

I.

INTRODUCTION

Cloud infrastructure is a $32.4 billion industry[1] and is predicted to reach $210 billion by
2022[2].
By 2021, 94% of all internet applications
and compute instances are expected to be processed by Cloud Service Providers (CSP) with
only 6% processed by traditional data centers[3]. The primary driver for this growthis poor utilization rates of IT resources provisioned in traditional data centers as no morethan 6% of their maximum computing output is delivered on average over the course of
the year [4], and up to 30% of servers are comatose[5] – using electricity but delivering nouseful information services.
With 8.4 million data centers globally, anestimated 96% of server capacity underutilized, and accelerated global demand for cloud∗ greg@akash.network, adam@akash.network

computing, the three leading cloud service
providers — Amazon Web Services (AWS),
Google Cloud, and Microsoft Azure — dominate the cloud computing market with 71%
market share[1] and this figure is expected
to increase. These providers are complicated,inflexible, restrictive, and come at a high recurring cost with vendor lock-in agreements[6].
Increased cloud usage has made cloud cost
optimization the top priority of cloud service
users for three consecutive years[7].
Outside of the large incumbent providers, organizations do not have many options for cloudcomputing. Akash aims to create efficiencies in
the cloud hosting market by repurposing compute resources that go to waste in the current
market.
By leveraging a blockchain, Akash introduces decentralization and transparency into
an industry currently controlled by monopolies.
The result is that cloud computing becomes acommodity, fueled by competitive free market,
available and accessible anywhere in the world,
at a fraction of current costs.
Akash is the world’s first and only Supercloud for serverless computing, enablinganyone with a computer to become a cloudprovider by offering their unused compute cycles in a safe and frictionless marketplace.
In this paper, we present an economic system that uses Akash Network’s native currency,
AKT, to achieve economic sovereignty in our2decentralized computing ecosystem. We also
propose an inflation design for mitigating inherent adoption challenges that face an earlymarket economy — lack of sufficient demand
from the tenants (consumers of computing),
which negatively impacts demand due to lackof supply. We also present a mechanism for astable medium of exchange by solving for token volatility, a major challenge for adoptionof decentralized ecosystems.
Note: This whitepaper represents a continuous work in progress. We will endeavor tokeep this document current with the latest development progress. As a result of the ongoingand iterative nature of the Akash development
process, the resulting code and implementation will likely differ from what this paper
represents.
We invite the interested reader toperuse the Akash GitHub repo athttps://github.com/ovrclk as we continue toopen-source various components of the systemover time.

A.

Definitions

Akash Token (AKT): AKT is the native
token of the Akash Network. The coreutility of AKT acts as a staking mechanism to secure the network and normalize compute prices for the marketplace
auction. The amount of AKTs staked
towards a validator defines the frequency
by which the validator may propose a
new block and its weight in votes to commit a block. In return for bonding (staking) to a validator, an AKT holder becomes eligible for block rewards (paid inAKT) as well as a proportion of transaction fees and service fees (paid in any of
the whitelisted tokens).
Validator: Validators secure the Akash net-

work by validating and relaying transactions, proposing, verifying and finalizing blocks. There will be a limited
set of validators, initially 64, required tomaintain a high standard of automatedsigning infrastructure. Validators chargedelegators a commission fee in AKT.
Delegator: Delegators are holders of the
AKT and use some or all of their tokens to secure the Akash chain. In return, delegators earn a proportion of thetransaction fee as well as block rewards.
Provider: Providers offer computing cycles(usually unused) on the Akash networkand earn a fee for their contributions.
Providers are required to maintain astake in AKT as collateral, proportional
to the hourly income earned; hence, every provider is a delegator and/or a validator.
Tenant: Tenants lease computing cycles offered by providers for a market-driven
price set using a reverse auction process(described in section below).

II.

NETWORK OVERVIEWThe Akash Network is a secure, transparent,and decentralized cloud computing marketplace that connects those who need computing
resources (clients) with those that have computing capacity to lease (providers). Akash
acts as a supercloud platform providing a unified layer above all providers on the marketplace so as to present clients with a single
cloud platform, regardless of which particularprovider they may be using.
Tenants use Akash because of its cost advantage, usability, and flexibility to move between
cloud providers, and the performance benefits

3
stakers as describe in sec. IV A.

App E

App D

App C

App B

Containerized Applications

App A

of global deployments. Providers use Akash because it allows them to earn profits from either
dedicated or temporarily-unused capacity.
A unit of computing (CPU, Memory, Disk)is leased as a container on Akash. A container [8] is a standard unit of software thatpackages up code and all its dependencies, so
the application runs quickly and reliably fromone computing environment to another. A
container image is a lightweight, standalone,
executable package of software that includes
everything needed to run an application: code,
runtime, system tools, system libraries, andsettings.
Any one with a physical machine (ie, computer, server) can slice the machine’s resources
into containers using a process called virtualization. Docker is a company that provides
widely adopted container virtualization technology, and it is common to refer to containers as “docker images.” The relation between
a physical computer and a container is illustrated in fig. 1).
All marketplace transactions are on the
Akash blockchain. To lease a container, thetenant (developer) requests a deployment byspecifying the type(s) of unit(s), and the quantity of each type of unit. To specify a type ofunit, the tenant specifies attributes to match,such as region (e.g. US) or privacy features(e.g. Intel SGX). The tenant also specifies the
maximum price they are willing to pay for eachtype of unit.
An order is created in the order book (uponacceptance by a validator).
The provider(s) that match all the requirements of the order then place a bid by competing on price. The provider that bids thelowest amount on the order wins (and match
requirements), upon which a lease is createdbetween the tenant and the provider for theorder. For every successful lease, a portionof the lease amount (Take Fee) is paid to theContainer Runtime (Docker)

Host Operating System (Linux)

Physical Server (Bare Metal / Cloud VM)

Figure 1: A simple illustration ofcontainerized applications in relation to thephysical servers

A.

Proof of Stake Based Consensus

Akash employs a blockchain secured by a
Proof-of-Stake consensus model as a Sybil resistance mechanism for determining participationin its consensus protocol and implements theTendermint [9] algorithm for Byzantine faulttolerant consensus. Tendermint was designed
to address the speed, scalability, and environmental concerns with Proof of Work with the
below set of properties:a) Validators take turns producing blocks
in a weighted round-robin fashion, meaning the algorithm has the ability to seamlessly change the leader on a per-blockbasis.
b) Strict accountability for Byzantine faults
allows for punishing misbehaving validators and providing economic security forthe network.
Anyone who owns an Akash token can bond(or delegate) their coins and become a valida-4tor, making the validator set open and permissionless. The limited resource of Akash tokens
acts as a Sybil prevention mechanism.
Voting power is determined by a validator’sbonded stake (not reputation or real-world
identity). No single actor can create multiple
nodes in order to increase their voting power
as the voting power is proportional to theirbonded stake. Validators are required to post
a “security deposit” which can be seized andburned by the protocol in a process known as“slashing”.
These security deposits are locked in abonded account and only released after an“unbonding period” in the event the stakerwishes to unbond. Slashing allows for punishing bad actors that are caught causing any
attributable Byzantine faults that harm thewell-functioning the system.
The slashing condition and the respective
attributable Byzantine faults and punishments
are beyond the scope of this paper. (For more
information on these, please review Akash Network Technical White paper).

1.

Limits on Number of Validators

Akash’s blockchain is based on Tendermint
consensus which gets slower with more validators due to the increased communication complexity. Fortunately, we can support enoughvalidators to make for a robust globally distributed blockchain with very fast transaction
confirmation times, and, as bandwidth, storage, and parallel compute capacity increases,
we will be able to support more validators in
the future.
On Genesis day, the number of validators Vi
is set to Vi (0) = Vi,0 = 64 and the number ofvalidators at time t year will be:Vn (t) = dlog2 (2t) · Vi,0 e(1)

So, in 10 years, there will be Vn (10) = 277
validators as illustrated in fig. 2

Figure 2: Number of validators over the years

III.

AKT: THE AKASH NETWORKTOKENThe primary functions of AKT are in staking (which provides security to the network),lease settlement, and in acting as a unit of measure for pricing all currencies supported by themarketplace. Although AKT can be used forsettling transactions in the marketplace, theleases can be settled using a multitude of tokens as described in later sections of this paper.
However, transaction fees and block rewards
are denominated in AKT. The income stakers earn is proportional to the tokens staked
and length of staking commitment. That said,
AKT performs three main functions: Resolve,
Reward, and Reserve.

A.

Resolve

Akash relies on a blockchain in which a set ofvalidators vote on proposals. Each proposal isweighed by the proposer’s voting power, which

5is the total tokens they staked and the tokens
bonded to them (stakers can delegate voting
power to validators).

B.

RewardUsers of AKT stake tokens to subsidize operating and capital expenditures. Stakers are
rewarded proportional to the number of tokens
staked, the length of lockup time, and the overall tokens staked in the system. Lockup times
can vary anywhere from one month to one
year. Flexibility in lockup encourages stakers
who stake for shorter periods (bear markets),
in a self-adjusting inflationary system that isdesigned to optimize for lower price pressureduring bear markets.

C.

Reserve

Fees on Akash can be settled using a multitude of currencies along with AKT. However, the market order book uses Akash Token(AKT) as the reserve currency of the ecosystem.
AKT provides a novel settlement option to lockin an exchange rate between AKT and the settlement currency. This way, providers andtenants are protected from the price volatilityof AKT expected to result from its low liquidity. In this section, we also present a mechanism “Transaction Ordering using Consensus
Weighted Median” as described in sec. IV D toestablish exchange rates without the need foran oracle.

A.

For every successful lease, a portion of thelease amount (Take Fee) goes to a Take Income Pool. The Take Income Pool is later distributed to stakers based on their stake weight(amount staked and time remaining to unlock,described in detail in the following sections).
The Take Rate depends on currency used forsettlement. The proposed take rates at Genesis when using AKT (TokenTakeRate) is 10%
and 20% when any other currency(TakeRate)is used. The TokenTakeRate and TakeRateparameters is subject to community consensus
managed by the governance.

B.

SETTLEMENT AND FEES

This section describes various fees incurredby users of Akash Network.

Settlement with Exchange Rate
LockinThe lease fees are denominated in AKT, butthey can be settled using any whitelisted tokens. There is an option to lock in an exchange
rate between AKT and the settlement currency.
This protects providers and tenants from theprice volatility of AKT expected to result fromits low liquidity.
For example, suppose a lease is set to
10 AKT s and locks an exchange rate of
1 AKT = 0.2 BT C. If the price of AKT
doubles, i.e., 1 AKT = 0.4 BT C, the tenant
is required to pay 5 AKT . Conversely, if theprice of BTC doubles while keeping the priceof AKT same, i.e., 1 AKT = 0.1 BT C, then
the tenant is required to pay 20 AKT .

C.
IV.

Take Fee

Fees Using a Multitude of Tokens

In order to avoid issues of network abuse(e.g. DOS attacks), all transactions and leases
on Akash are subject to fees. Every transaction
has a specific associated fee, GasLimit, for6
processing the transaction, as long as it does
not exceed BlockGasLimit.
The GasLimit is the amount of gas which
is deducted from the sender’s account balance
to issue a transaction.
Unlike most other blockchain platforms that
require fees to be paid in the platform’s native
cryptocurrency, such as Ethereum [10], Bitcoin[11], and Neo [12], Akash accepts a multitude
of tokens for fees. Each validator and provider
on Akash can choose to accept any currency
or a combination of currencies as fees.
The resulting transaction fees, minus a network tax that goes into a reserve pool, aresplit among validators and delegators basedon their stake (amount and length).

D. Transaction Ordering using
Consensus Weighted MedianIn order to prioritize transactions when multiple tokens are used, validators need a mechanism to determine the relative value of thetransaction fee. For example, let us assume
we had an oracle to inform us that the relativevalue of BTC is 200 AKT, and that of ETH is
0.4 AKT. Suppose we have two transactionsof equal gas cost, and the transaction fees onthem are 10 BTC and 6000 ETH, respectively.
The first transaction’s fee is equivalent to 2000
(10 x 200) AKT and the second transaction’s
fee is equivalent to 2400 (6000 x 0.4) AKT. The
second transaction will have a higher priority.
In order to get these relative values without using an oracle, we can employ a Consensus Weighted Median using Localized Validator
Configuration [13] mechanism.
In this method, each validator maintains a
local view of the relative values of the tokens
in a config file which is periodically updated,
and the relative value is achieved by using
a weighted mean, meaning they submit their“votes” for the value of each token on-chain asa transaction.
Lets say for example, there are fivevalidators {A, B, C, D, E} with powers{0.3, 0.3, 0.1, 0.1, 0.2} respectively.
They
submit the following votes for their personalviews of each token:
A : AKT = 1, BTC = 0.2
B : AKT = 2, BTC = 0.4
C : AKT = 12, BTC = 2
D : AKT = 4, BTC = 1
E : AKT = 1.5, BTC = 0.5
These values are stored on-chain in a ordered
list along with their validator that placed thevote.
AKT : [1A , 1.5E , 2B , 4D , 12C ]BTC : [0.2A , 0.4B , 0.5E , 1D , 2C ]The proposer takes a weighted mean (bystake) of the votes for each whitelisted token
to determine a consensus relative value of eachtoken, where w̄(xn ) = W eightedM ean(xn ) :AKT : w̄([1, 0.3], [1.5, 0.2], [2, 0.3], [4, 0.1], [12, 0.1])
BTC : w̄([0.2, 0.3], [0.4, 0.2], [0.5, 0.2], [1, 0.1], [2, 0.2])
which give us the relative value for each token: AKT = 2.8 and BTC = 0.58 respectively.

V.

TOKEN ECONOMICS AND
INCENTIVES

Providers earn income by selling computing
cycles to tenants who lease computing services
for a fee. However, in the early days of the
network, there is a high chance the providers
will not be able to earn a meaningful income
due to a lack of sufficient demand from thetenants (consumers of computing), which inturn hurts demand because of lack of supply.
To solve this problem, we will incentivize
the providers using inflation by means ofblock rewards until a healthy threshold can beachieved.

7
In this section, we describe the economics ofmining and Akash Network’s inflation model.
An ideal inflation model should have the following properties:• Early providers can provide services at
exponentially lower costs than in themarket outside the network, to accelerate adoption.
• The income a provider can earn is proportional to the number of tokens they
stake.
• The block compensation for a staker is
proportional to their staked amount, thetime to unlock and overall locked tokens.
• Stakers are incentivized to stake forlonger periods.
• Short term stakers (such as some bearmarket participants) are also incentivized, but they gain a smaller reward.
• To maximize compensation, stakers are
incentivized to re-stake their income.

30 days. Additionally, they delegate (voting
power) to validator v by bonding their stake
via BindValidator transaction.
A staker is a delegator and/or a validator
to whom delegators delegate. Every provider
is a staker, but not every staker is a provider;there can be stakers who are pure delegators
providing no other services, and there can be
stakers who are pure validators providing noother services.
At any point, a staker can: a) Split theirstake (or any piece of their stake) into twopieces. b) Increase their stake l by adding
more AKT. c) Increase the lock time T , where
T > Tmin .
Stakers choose to split their stake because
the compensation is dependent on lock time L
which will be addressed in later sections.

C.

General Inflation Properties
1.

A.

Motivation

Akash Network aims to secure early adoption by offering exponential cost savings as avalue proposition for tenants, and the efficiency
of a serverless infrastructure as an additional
value proposition for tenants and providers.
These value propositions are extremely compelling, especially for data and compute intensive applications such as machine learning.

B.

Stake and Bind: Mining Protocol

A provider commits to provide services forat least time T and intends to earn service
income r every compensation period Tcomp =1 day. Providers stake Akash tokens s andspecify an unlock time t1 , where minimal locktime t1 − t should not be less than Tmin =Initial Inflation

If we assume Akash will have the same number of tokens locked as NuCypher [14] andDASH [15]: λ = 60%, then 1 − 40% of the
supply of AKT will be in circulation. The
adjusted inflation rate for inflation, I will be:

I∗ =

I
,
1−λ

(2)

Considering that ZCash [16] had I ∗ = 350%
(turn around point during the overall bull market), which makes I = 140% APR, it is reasonably safe to set the initial inflation to be
I0 = 100% APR (meaning 1/365 per day).

2.

Inflation Decay

Assume that all miners have the maximum
compensation rate. We define the inflation

8
decay factor (time to halve the inflation rate)
to be T1/2 = 2 years in this case. Inflation
depending on the time passed from the Genesist, then looks like:I(t) = I0 · 2

−T t

1/2



t
, (3)
= I0 exp − ln 2
T1/2

3.

We will reward the full compensation (γ = 1)
to the stakers who are committed to stake atleast T1 = 1 year (365 days). Those who stakefor Tmin = 1 month will get close to half thecompensation (γ ≈ 0.54). In general,In this case, the dependence of the token
supply on the time t is:

M (t) = M0 +Z t
0I(t) dt = M0 +γ=

I0 T1/2− t
1 − 2 T1/2
ln 2
(4)

If we let I0 be the relative inflation rate, thenI0 = i0 M0 . For 100% APR, i0 = 1 and I0 =M0 , which gives us the maximum number oftokens which will ever be created (as illustrated
in fig. 3):
i0 T1/2≈ 3.89 M0 ,Mmax = M (∞) = M0 1 +ln 2(5)where M0 is initial number of tokens.

Staking Time and Token Creation



0.5 + 0.5

min(Ti , T1 )T1

Ti,initial > Tmin ,


,

(6)

(7)

where the unlocking time Ti means the timeleft to unlock the tokens: Ti = t1 − t. t1 is thetime when the tokens will be unlocked, andt is the current time. The initial Ti cannot
be set smaller than Tmin = 1 month, but it
eventually becomes smaller than that as time
passes and t gets closer to t1 .

Shorter stake periods (for lower rewards)
result in a lower daily token emission. Considering that miners will most likely stake forshort periods during a bear market, we can
expect token emission to decline during a bearmarket, which will help to boost the price.
Therefore we can expect this mechanism tosupport price stability.
∗
The emission half decay time T1/2=∗∗
T1/2 /γ , where γ is the mean staking parameter, is also prolonged when γ < 1. T1/2 prolongs to 4 years instead of 2 if all stakers haveγ ∗ = γ = 0.5.

The total supply over time (eq. 4) at γ ∗ =6 1will then look like:
Figure 3: Token supply and tokens locked
over years with an initial inflation of 100%
APR that is halving every 2 years



∗ 
i0 γ ∗ T1/2
− T ∗t
1/2
M (t) = M0 1 +
1−2
.
ln 2
(8)

9
D.

Delegate Pool Distribution

E.

The exponential is a solution of a differential
equation where inflation is proportional to theamount of not yet mined tokens:

I(t) =

ln 2(Mmax − M (t))
T1/2

(9)

dM = I(t) dt.

(10)

where M (t) is the current token supply with
M (0) = M0 and dt can be equal to the mining
period (1 day). Each validator can triviallycalculate its dM using few operations using
the token supply M from the last period. The
amount of mined tokens for the validator poolp in the time t can be calculated according to
the formula:δmv,t =

sv ln 2δM (t),
S T1/2

(11)

X

(12)

δMt =

δmv,t ,v

where sv is the number of tokens boundto the validator’s delegate pool v and S is
the total number of tokens locked. Instead of
calculating all the sum over v, each validator
can add their portion δmv,t .
The distribution factor for a delegate boundto pool v is:
1
κ=
2



γ
s
+
γv
Sv


,

(13)

γv is the aggregate stake compensation factor for the pool and Sv is the sum of all tokens
bound to the pool.

Mining strategies and expectedcompensation

In this section, we look at three possibilities: a staker liquidating all the compensation
while extending the lock time (Liquidate mining compensation), a staker adding all the compensation to their current stake, and a miner
waiting for their stake to unlock after time T .
Each of these possibilities could have different distributions of γ. Let’s consider γ = 1
and γ = 0.5 as the two extreme values of γ.
Let’s take the amount of tokens locked to be
λ = 60%, as in DASH.

1.

Liquidate Mining Compensation

In this scenario, all stakers in the pool are
liquidating all their earnings every Tcomp period. The total amount of tokens staked in the
network can be expressed as S = λM . Assume
all the delegators have equal amounts of stakebound to the pool. The amount of stake stays
constant in this case, and equal to mi = s,making mv = sv and γ = γv where, γv is themean staking parameter of the pool. Then,the pool mining rate (i.e. the cumulative poolreward) is:drv
Sv ln 2= γv
(Mmax − M (t)) . (14)dt
λM (t) T1/2
When we substitute M (t) from eq. 8 andintegrate over time, we find total pool compensation:rv (t) = Sv

M (t)
γ
ln
,
∗
γ λ
M0

(15)

If ∆rv (t) = rv (t) − C where C is validator’scommission, that brings individual staker’s
compensation to be:10r(t) = κ · ∆rv (t) =

1
2



γ
s
+
γv
Sv



M (t)
s(t) = s(0)M0· ∆rv (t)(16)

If γ = 1 (staking for 1 year) and λ = 60%(60% of all AKT are staked). With C = 0.1 ·r(t), staker compensation in AKT starts from
0.45% per day, or 101.6% during the first yearof staking.
We should note that if other miners stakefor less than a year (γ ∗ < 1), the inflation rate
decays slower, and the compensation over agiven period will be higher.

 γ ∗γ λ.

(18)Assuming the validator commission is 1%,
if γ = 1 (staking for 1 year+) and λ = 60%(60% of all nodes in the network are staking),
delegate compensation in AKT starts from
0.45% per day, or s(1) − s(0) = 176.5% during
the first year of staking.

3.

Take mining compensation and spindown

When the node spins down, the staker does
not extend the time for end of staking t1 ,and the compensation is constantly decreasing as the time left to unlock becomes smallerand smaller, effectively decreasing γ gradually towards 0.5. This is the default behavior.
To avoid this, the staker should set t1 large
enough, or increase t1 periodically.
Figure 4: Daily compensation over time
assuming 60% tokens locked for lock times of
1 year and 1 month

2.

FAQ

How many tokens will ever be in existence? We will start with 100 million tokens,and the maximum amount of tokens ever created will be 389 million, as illustrated in fig. 3

Re-stake mining compensation

Instead of liquidating mining compensation,
it could be re-staked into the pool in order
to increase the delegator’s stake. In this case,the actual stake s is constantly increasing with
time:
ds
s
ln 2
=γ
(Mmax − M (t)) .
dt
λM (t) T1/2

4.

(17)

If we substitute S(t) from eq. 8 and solve
this differential equation against s, we get:

What is the inflation rate? The inflation rate will depend on how many short-term
miners and long-term miners are working inthe system. Depending on this, the initial inflation will be between 50% APR (if all miners
are very short term) and 100% APR (if all miners commit for a long term). The inflation will
decay exponentially every day, halving sometime between 2 years (if all the miners are longterm) and 4 years (if all the miners are shortterm). fig. 5

1121-day “unbonding” period – considered lockup – and there is no incentive to commit for
more extended periods. Whereas, stakers in
Akash can choose to commit for one month toa year, for which they will receive ~54% and100% compensation respectively.

B.

Figure 5: Annual inflation over the years
when tokens are locked with long and shortcommitments

VI.

RELATED WORKThe majority of proof of stake networks suchas Ethereum 2.0 [17], Tezos [18], and Cardano[19] all use a single token model. However,there seem to be networks that are experimenting with more novel models. In this section, we
will review some of these systems and explore
the differences with Akash’s token model.

A.

Cosmos Hub

Akash and Cosmos Hub use Tendermint [9]Consensus Algorithm and share a core set ofvalues with interoperability and user experience. Similar to Cosmos’s Atom [13], AKT’s
primary utility is to provide economic security
to the network. Akash’s model variously improves Cosmos’s model. First, AKT provides amechanism to normalize compute prices for themarketplace auction. Secondly, Akash introduces a mechanism to lock in an exchange rate
to a reserve currency of choice to mitigate market drive volatility risk of AKT when leasing
computing for more extended periods. Finally,
Akash’s block reward distribution is proportional to the time and amount of a stake, unlike
Cosmos’s model where the distribution is homogeneous for a fixed time. Cosmos imposes aNEO

According to NEO’s white paper [12]:NEO network has two tokens.
NEO representing the right to manage NEO blockchain and GAS representing the right to use the NEO
Blockchain.
At the surface, NEO’s primary utility is astaking token and GAS is the fee token. However, after closer observation, NEO’s model isvery different from Akash’s model.
Firstly, NEO is used as a mechanism todetermine how many votes each NEO accountgets without a requirement to stake tokens.
Each account can vote for as many validator
candidates as they wish and each validator
candidate they vote for receives the number ofvotes equivalent to the amount of NEO in thevoter’s account.
With regards to the fee, NEO’s chain only
supports a single fee token, unlike Akash’s
multi-token model.
Furthermore, unlike
Akash, NEO does not provide volatility protection for the GAS tokens.

C.

EOS

EOS’s delegated proof of stake consensus [20]has similarities with Akash’s model but is extensively different. In EOS, each token holder
can stake their tokens in order to vote for block
producer and in return, they are rewarded in12resource units such as CPU, RAM, and NET
that can be spent for transactions on the network. However, like in NEO, the staking token
EOS is not staked by the block producers, and
it is not slashable in the case of misbehavior.
In EOS, staking means, stakers are putting
tokens in a lockup period and not necessarily
contributing to the functionality of the network. Stakers earn rewards in CPU, RAM, andNET that are used to purchase computational
resources on the network. These resources are
not transferrable. CPU and NET are only
spendable by the receiver, whereas RAM canbe traded with other users in a Bancor-stylemarketplace [21].
EOS burns these resources upon spending,instead of giving them to block producers. The
validator compensation model is unclear, considering transaction fees is not the primarymechanism. EOS is seemingly a single token network, despite having nuances and additional steps.

VII.

CONCLUSION

This paper explains the network and mining economics of Akash Network and presents
various incentives and utilities of different tokens in the staking and fees mechanisms. The
Akash Token (AKT) acts as staking token andreserve currency for the network while using a
multitude of tokens for settlement.

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