Akash Network (AKT) sustainability report

Akash Network is present on the following networks: Osmosis.

Osmosis is a sovereign chain built with the Cosmos SDK, reaching agreement through CometBFT, the Byzantine fault tolerant engine that carried the name Tendermint Core until its rename in 2023. Blocks are committed in rounds: a validator from the active set proposes, the set votes in a prevote stage and then a precommit stage, and the block is finalized the moment precommits representing more than two thirds of bonded voting power are collected. Nothing is probabilistic about this, so a committed block cannot be reorganized away and no confirmation depth needs to be observed. The guarantee the engine provides is that honest validators never commit conflicting blocks while fewer than one third of bonded voting power misbehaves; past that point the chain halts instead of forking.

Validators are ranked by the stake bonded to them, self-bonded and delegated counted together, and the highest ranked fill a fixed number of active slots, which on this network is seventy, a deliberately tighter set than several of the chains it interoperates with. Delegation lets holders of the native asset assign their weight to an operator and share in that operator's rewards, and it carries the same downside the operator carries. Bonded stake takes a fortnight to unwind, roughly half the period used elsewhere in the ecosystem.

What sets this network apart from a general-purpose Cosmos chain is that its exchange lives inside the state machine rather than in contracts deployed on top of one. Pool creation, routing a swap across several pools, concentrated liquidity positions, and the accounting of trading fees are all protocol modules that validators execute as part of processing a block, so a trade is a consensus-level state transition carrying exactly the same finality as a transfer. The protocol also runs an arbitrage module of its own, which inspects a proposed block for price discrepancies its pools have opened and captures the correction for the protocol rather than leaving it to outside searchers. A number of recurring operations, issuance and reward distribution among them, are processed once per daily epoch instead of every block.

Akash Network is present on the following networks: Osmosis.

Three groups are paid on this network, and the balance between them has shifted markedly. New units of the native asset are minted on a daily cadence along a schedule that steps down by a third every seven hundred and thirty days, and governance decides how each day's issuance is split. Liquidity provision was once the largest claim on that issuance; it has since been removed from the split entirely, on the argument that trading revenue rather than subsidy now sustains the pools. The staking share has been cut back as well, with most of each day's issuance now directed into the community fund alongside a fixed development allocation. Bonded stake is increasingly compensated from revenue instead: transaction fees collected in the native asset accrue to stakers, and fees paid in other accepted denominations are converted first.

That revenue comes from trading. Every swap pays a spread factor to the providers of liquidity in each pool it touches, and separately a taker fee to the protocol, set by default at a tenth of a percent and overridden route by route by a delegated fee committee that prices heavily traded pairs down and thin ones up. Taker fees collected in the native asset are split so that the larger part is destroyed and the remainder is paid to stakers. Taker fees collected in other assets are divided between the community fund and a buyback that acquires the native asset before splitting it the same way, which ties the rate of destruction directly to trading volume. Liquidity providers may bond their positions for additional incentives, and a superfluid arrangement lets the portion of a bonded position represented by the native asset be delegated to a validator at the same time, so one unit of capital both secures consensus and backs a pool.

Ordinary transactions pay gas at a base price that climbs when blocks fill and falls back when they empty, resting on a governance-set minimum, a mechanism intended to price out spam rather than to raise revenue; fees may be paid in a whitelisted set of denominations, not only the native one. Validators must charge at least five percent commission. Signing two conflicting blocks costs a validator and its delegators a share of bonded stake and permanent exclusion from the set, while missing too many blocks results in jailing rather than confiscation.

Akash Network is present on the following networks: Osmosis.

The reported consumption for this network is a modeled estimate rather than a measurement taken from a meter, and it is built from the machines that keep the chain running. The first task is to size that machine population. It comprises the seventy validators in the active set, the bonded candidates waiting outside it, and the full, archive, and indexing nodes that serve the trading interfaces, routing services, and relayers connecting this chain to its neighbors. The count is approximated from peer discovery on the public network, from what operators publish about their own deployments, and from the chain's own on-chain register of who is bonded.

Each machine is then represented by a hardware profile. The client software publishes the processor, memory, disk, and bandwidth a node needs to stay in sync, and a machine meeting those requirements stands in for the node. This chain sits at the demanding end of the range for its family, because validators execute swap routing, concentrated liquidity accounting, and the protocol's own arbitrage checks inside block processing rather than delegating them to a contract layer, and because several recurring tasks are batched into a daily epoch that produces a pronounced load spike. Electrical draw for the representative machine comes from controlled measurement of comparable equipment across its load range, idle draw included, since nodes are powered continuously. Draw multiplied by population over the reporting period gives the network total, from which a per-asset share is apportioned using observed on-chain activity.

Two caveats matter. The population and the hardware mix are inferred from public observation and stated software requirements, not from operator disclosure, and where evidence is missing the assumption chosen raises rather than lowers the estimate, so the figure is likelier to overstate than understate. Second, a correction: earlier assessments attributed to this network a share of another chain's consumption on the grounds that the other chain contributed to its security. That is not how this network is secured. It has its own validator set, its own bonded stake, and its own penalties, and the estimate here covers only the machines that run it. Figures are restated as observation improves.

Akash Network is present on the following networks: Osmosis.

Because electricity is generated differently from one grid to the next, the renewable share reported for this network depends on establishing where its machines are. Locations are inferred from publicly observable network data: the addresses validators and other nodes advertise to their peers, the hosting ranges into which those addresses fall, and whatever operators choose to publish about their own infrastructure. The output is a distribution of the node population over countries and regions, never a precise site for a given machine. Where the distribution cannot be established with confidence, the observed distribution of a network with a comparable consensus design and comparable rewards is substituted, on the assumption that similar economics lead operators to similar places.

Every region in that distribution is then paired with published statistics on the composition of its electricity generation, and the network's estimated consumption is weighted across the regions to yield the proportion met from renewable sources. The generation statistics are taken from Share of electricity generated by renewables, compiled by Our World in Data with major processing from Ember's yearly electricity data and the Energy Institute's Statistical Review of World Energy.

Energy intensity is reported as a marginal quantity and should not be read as consumption divided by transaction count. It answers a narrower question: how much additional energy the network draws when one further transaction is included in a block. That distinction is particularly sharp here. Validators run continuously and commit blocks on a fixed cadence whether or not there is trading to process, so nearly all of the draw is a standing cost, and the incremental cost of one more swap, which is executed by the same validator process as any other message, is very small by comparison.

The method's weakest link is geolocation. An address identifies a hosting provider rather than a customer, machines behind large commercial cloud regions are assigned to the advertised region rather than to a physical building, and the grid statistics are averages over a country or region that ignore any supply arrangement an individual facility has made. Where a stand-in distribution has been used, its representativeness remains an assumption.

Akash Network is present on the following networks: Osmosis.

Emissions figures are constructed from the energy estimate and the geographic estimate together. The distribution of nodes across regions is inferred from publicly observable network data, with the distribution of a structurally comparable network standing in where direct observation is insufficient. Each region's share of estimated consumption is then multiplied by the emissions released per unit of electricity generated on that region's grid, and the results are summed to give the network total.

Carbon intensity values are taken from Carbon intensity of electricity generation, compiled by Our World in Data with major processing from Ember's yearly electricity data and the Energy Institute's Statistical Review of World Energy, and published under the Creative Commons CC BY 4.0 license.

The distinction between the two reported scopes is worth spelling out. Scope 1 captures emissions from sources the infrastructure's operators control directly, essentially combustion happening on their own premises. Validators and supporting nodes for this network are conventional servers housed in data centers and supplied from public grids, so there is ordinarily nothing of that kind to record and the scope 1 figure is reported at or close to zero rather than omitted. Scope 2 captures the emissions embodied in the purchased electricity that those machines consume, and in practice the entire footprint falls under it. Greenhouse gas intensity mirrors energy intensity in construction: it expresses the emissions attributable to one additional transaction at the margin, not an average obtained by dividing a total by a count.

Every uncertainty already present in the consumption and location estimates propagates into these figures, and the intensity data introduces another. Published grid intensities are annual averages across a region; they cannot reflect the hours at which a node's consumption actually falls, nor any generation a particular operator has contracted for directly. Where the evidence is thin, the conservative assumption is preferred, meaning the reported emissions are more likely to sit above the true value than below it, and every figure is revised as the underlying observation improves.