RENDER vs AKT vs IO: The Revenue Question

Why revenue is the question that matters

Most DeAIDeAIDecentralised AI. An umbrella term for blockchain-based projects that build AI infrastructure (compute, data, inference, models, agents) without a single central provider controlling the system.Like the difference between streaming a movie from Netflix and sharing it via BitTorrent. Netflix is fast and polished but one company controls what you can watch and what you pay. BitTorrent is messier but no single operator can shut you out.Read more → tokens have no revenue. Their value comes entirely from emissionsEmissionsNew tokens created and distributed by a blockchain protocol over time as rewards to validators, stakers, or miners. Emissions fund network security and participation at the cost of diluting existing holders.Like a company that pays employees partly in newly printed shares. Every year the total number of shares goes up, which means existing shareholders own a slightly smaller slice of the same company unless the company grows faster than the printing.Read more →: participants earn tokens funded by inflationInflationThe annual rate at which new tokens are created and added to the circulating supply. Most networks use inflation to pay validators, stakers, and infrastructure providers from freshly minted tokens rather than real revenue.Like a landlord who raises the rent every year. If your salary goes up at the same rate, you break even. If it doesn't, you get poorer without noticing, because the number on your payslip hasn't changed but the ground under it has shifted.Read more →, trade them for dollars, and the system works until it doesn’t. The few projects that have figured out how to generate real revenue from real customers are worth studying closely, because revenue is what separates infrastructure from speculation.

Render, Akash and io.net are the three largest decentralised compute networks by market cap. All three connect GPUGPUGraphics Processing Unit. Originally designed to render video game graphics, GPUs turned out to be exceptionally good at the massively parallel math that AI models need. Modern AI training and inference runs almost entirely on GPUs.Like a factory with 10,000 workers doing the same simple task in parallel, versus a CPU which is more like 10 workers each doing different complex tasks. AI training involves doing simple math a million times per second on a million numbers, which is exactly what the GPU factory is designed for.Read more → providers with customers who need compute. All three have tokens. But their revenue models, their customer bases and their relationship with decentralisation are fundamentally different. Those differences explain why Render scores highest on returns (72/100) despite scoring lowest on freedom (32/100) in our dual-score system.

The three models at a glance

Render: centralisation as a product strategy

Render’s revenue story starts with OctaneRender. OTOY built one of the most widely used GPU rendering engines in the creative industry, with native integrations into Blender and Cinema 4D. The Render Network is OctaneRender’s distributed backend: studios submit rendering jobs to a network of GPU operators instead of buying their own render farms.

The burnBurnPermanently removing tokens from circulation by sending them to an address that no one controls. Burns reduce total supply, which (all else equal) makes each remaining token worth more of the network's value.Like a company buying back its own shares and shredding them. The company's total value stays the same, but each remaining share now represents a slightly bigger slice of that value.Read more → mechanism is straightforward. When a creator pays for a rendering job, 95% of the RENDER spent is permanently burned. 5% goes to OTOY as a service fee. Node operators receive newly minted RENDER from an emission pool. If burns exceed emissions, the tokenTokenA digital unit of value or access rights tracked on a blockchain. Tokens can represent ownership in a project, a right to use a service, a share of future revenue, or simply a tradable asset with no underlying claim.Like a physical poker chip a casino issues. The chip itself has no value. What makes it worth something is what it lets you do at the casino, what the casino has promised, and how much other people will pay you for it.Read more → becomes deflationary.

According to Render Foundation reports, burns grew 279% year-over-year through 2025. Monthly burns increased from roughly 20,000 RENDER in January to 121,000 in September. Over 1 million RENDER have now been permanently burned. Sixty-nine million frames have been rendered, with 35% of all-time volume in 2025 alone. The trajectory is real.

The problem: monthly emissions of roughly 492,000 RENDER still outpace burns. BME is net inflationary today. The system needs substantially more rendering demand before it flips deflationary. That’s a lot of rendering.

Why it scores highest on returns. Render has something most DeAI projects don’t: a moat. OctaneRender is proprietary software with genuine Hollywood adoption (Beeple, Apple Vision Pro, Stability AI). Studios already using OctaneRender have a natural path to the network. The burn mechanism directly ties usage to token scarcity. The 644M hard cap with declining emissions gives a clear path to deflation at scale. And major exchange listings (Binance, Coinbase, Kraken, OKX) provide institutional-grade liquidityLiquidityHow easily a token can be bought or sold without moving the price. High liquidity means you can enter or exit large positions quickly at the quoted price. Low liquidity means even small trades can swing the market.Like the difference between selling a house and selling a share of Apple stock. The house might be worth more on paper, but finding a buyer at that price takes weeks. The Apple share converts to cash in one click.Read more →.

Why it scores lowest on freedom. Render is, functionally, OTOY’s product with a token attached. The network is permissioned; operators must be approved by the Foundation. The rendering engine, node client, job routing and allocation algorithm are all proprietary closed-source software. Nine public GitHub repos contain near-zero operational code. OTOY’s treasury holds 23.3% of supply with no vestingVestingA schedule that locks up tokens allocated to insiders, investors, and team members, releasing them gradually over months or years. Vesting prevents insiders from dumping on public buyers immediately after launch.Like a new employee's stock options at a startup. You don't get all the shares on day one. They unlock over four years so you stick around and do the work rather than cashing out and leaving.Read more →. If OTOY disappeared, the network would likely cease to function.

The uncomfortable truth. Render’s returns score is high precisely because it’s centralised. Proprietary rendering is the moat. Permissioned access ensures quality. Foundation controls who participates. All of this produces a better product, which drives adoption, which drives burns, which drives token value. Decentralisation would likely reduce output quality and weaken the revenue modelModelA trained neural network that takes inputs (text, images, audio) and produces outputs (more text, classifications, generated content). In DeAI the model is the thing that actually does the work.Like a very experienced apprentice who has spent years watching thousands of masters make furniture. They can't explain how they know when a joint is right, but they can make a chair that looks and functions like a Chippendale. The training is invisible. The output is what matters.Read more →.

Akash: freedom as infrastructure

Akash takes the opposite approach. Anyone with qualifying hardware can become a provider: no application, no approval, no permission required. The entire stack is open source under Apache 2.0. On-chain governanceDAODecentralised Autonomous Organisation. A way to coordinate decisions and manage a treasury using token-weighted voting instead of a traditional company structure. Token holders propose and vote on changes directly.Like a shareholder-run company where every shareholder can vote on every decision, the votes are public, and the company can't do anything the shareholders don't approve. The coordination is messier than a normal company but nobody has unilateral control.Read more → has processed 300+ proposals with 42% voter turnout. The token is both the stakingStakingLocking up a cryptocurrency to help secure a blockchain network, usually in exchange for rewards. The locked tokens act as a security deposit that can be taken away if the staker misbehaves.Like putting down a large rental deposit for an apartment. You get the money back if you behave, you earn interest while it's locked, and the landlord takes it if you trash the place.Read more → asset (securing the Cosmos chain) and the payment currency for compute.

Revenue is modest but verifiable. Akash generated $3.15M in on-chain revenue in 2025, growing 128% year-over-year. Messari publishes quarterly reports that anyone can audit. Unlike Render, where USD revenue isn’t disclosed, every dollar of Akash revenue is a Cosmos transaction you can trace.

The customer base is crypto-native but growing. Venice.ai processes billions of inferenceInferenceRunning a trained AI model to produce an answer. Inference is what happens when you type a prompt into ChatGPT and get a response. The model takes your input, computes a best guess, and returns it.Like asking an expert for their opinion. The training was the decades they spent becoming an expert. The inference is the 30 seconds it takes them to answer your specific question.Read more → tokens through Akash. ElizaOS uses AkashChat as its default inference APIAPIApplication Programming Interface. A structured way for one piece of software to talk to another. In DeAI, APIs let applications request inference from a model without running the model themselves.Like a waiter in a restaurant. You don't walk into the kitchen and cook your own meal. You tell the waiter what you want, they tell the kitchen, the kitchen cooks it, and the waiter brings it back. The API is the waiter.Read more →. Morpheus has a one-click Console template. Gensyn runs H100 nodes for reinforcement learningRLReinforcement Learning. A training paradigm where an AI agent takes actions in an environment, receives rewards or penalties for the outcomes, and learns a policy that maximises long-term reward. Used heavily for aligning modern LLMs.Like training a dog with treats. Good behaviour gets a treat. Bad behaviour gets nothing or a reprimand. Over many repetitions the dog learns which behaviours produce treats and starts doing them on purpose.Read more →. Average lease value doubled year-over-year to $25.03, indicating higher-value workloads replacing the low-value spam that plagued the network in early 2025.

Akash’s marketplace benchmarks show 70-85% savings versus AWS SageMaker for equivalent GPU workloads. AkashML offers inference at $2-4 per million tokens versus OpenAI’s $15.

Where it falls short on returns. No supply cap; 8% nominal inflation dilutes holders. BME (Burn-Mint EquilibriumBurn-Mint EquilibriumA tokenomics model where network fees burn tokens while new tokens are minted and paid to suppliers. The system tries to balance burns and mints so circulating supply stays roughly stable when usage scales.Like a business that spends a dollar of revenue for every dollar of wages it pays. Money flows in and out at the same rate, so the total cash in the company stays flat. The rate of flow tells you how big the business is.Read more →) activated on 23 March 2026, burning AKT on-chain and reducing effective inflation to roughly 7.1% at current usage. That’s progress, but the burns are still modest relative to emissions. Staking yields roughly 7.3% nominal, which nets approximately zero real yield after inflation. Liquidity is thinner than Render: no Binance listing, $1-5M daily volume versus Render’s $41M.

Where it wins on freedom. Permissionless participation, open-source everything, on-chain governance, verifiable revenue. If Overclock Labs disappeared tomorrow, the network would continue operating. That’s the test of decentralisation, and Akash passes it.

The P/Revenue ratio tells a story. At roughly 32x, Akash is priced like an early-stage SaaS company with real revenue. Render at 696x is priced on narrative. The market is paying a 20x premium for Render’s brand, liquidity and Hollywood associations.

io.net: the unverifiable claim

io.net is the most aggressive of the three. It claims $20M+ in annualised revenue, extrapolated from a self-reported $5.7M in Q1 2025 (an 82.6% quarter-on-quarter increase), 327,000 registered GPUs, and partnerships with Dell Technologies. Named enterprise customers include Leonardo.Ai (19M users, 50% GPU cost reduction), Wondera ($2.48M savings versus AWS) and UC Berkeley’s RAIL Lab (92.8% cost savings).

The revenue figures are self-reported. Messari publishes quarterly reports with network metrics, and token data is verifiable on-chain, but the core revenue and utilisation numbers come from io.net. The gap between headline metrics and reality is the persistent concern: 327,000 registered GPUs but only 6,720 daily verified active, after a 2024 Sybil attack inflated GPU counts with 1.8 million fake devices. The market has noticed. io.net’s ~$32M market cap pricing it at roughly 1.6x claimed revenue is the market saying “we aren’t confident in these numbers.”

The Incentive Dynamic Engine burns at least 50% of post-supplier revenue by purchasing and burning IO tokens. In theory, this creates strong deflationary pressure. In practice, with unverifiable revenue, the burn mechanism is unverifiable too.

io.net launched in June 2024 and is down 98% from its all-time high. Significant unlocks run through 2030. Its core platform is proprietary with no on-chain governance. The enterprise case studies are compelling if true, but “if true” is doing a lot of work in that sentence.

The lesson. Revenue claims without full verifiability carry a discount. Akash’s $3.15M of fully on-chain revenue is more valuable as an investment signal than io.net’s $20M of self-reported annualised revenue, because you can trace every dollar of one on a blockBlockA batch of transactions added to a blockchain at a set interval. Each block cryptographically links to the previous one, creating an append-only chain that can't be rewritten without redoing all the work since.Like a page in a ledger. Every page has a fixed number of entries, every page references the previous page, and once a page is filled and signed off it can't be edited without visibly invalidating every page that came after. The chain is just a very long series of these sealed pages.Read more → explorer and you can’t do the same for the other.

The revenue comparison that matters

Strip away the marketing and look at what each token actually does with revenue:

Render has the longest-running BME implementation. Akash activated its own BME in March 2026 and has the most trustworthy revenue data. io.net has the strongest revenue growth claim, but the verification gap keeps it discounted.

The freedom-returns trade-off

This is the core question for investors. Does centralisation produce better returns?

The data says yes, for now. Render’s proprietary engine, permissioned network and curated operator base produce a higher-quality product that attracts higher-value customers. Hollywood partnerships are real. OctaneRender integration is a genuine moat. And the market rewards this with a $696M valuation.

Akash’s open, permissionless model produces a more ideologically pure product but a messier one. The spam attack in early 2025 exposed that cost directly. Provider count has fallen to 69 active providers. Customer base is crypto-native rather than Hollywood-grade. One-seventh of Render’s valuation.

But markets aren’t always right about time horizons. Akash has three structural advantages that may matter more over the long term:

1. Verifiable revenue builds trust. As institutional capital enters DeAI, auditable on-chain revenue will be a prerequisite for serious allocation. Render’s opaque revenue reporting will become a liability.

2. Permissionless scales differently. Render’s permissioned model requires Foundation approval for every new operator. Akash’s permissionless model lets anyone with hardware join. At scale, the permissionless model adds supply faster.

3. BME is now live. Akash activated its burn mechanism on 23 March 2026. It now has both verifiable revenue and an on-chain burn mechanic. Burns are modest at current usage (~7.1% effective inflation versus 8% nominal), but the mechanism works. At a 32x P/Revenue versus Render’s 696x, AKT could be the more attractive risk-adjusted position if compute revenue scales.

My framework

I hold both RENDER and AKT. Different positions for different theses.

RENDER is a bet on rendering demand and the OctaneRender moat. If you want to run a node yourself, see how to earn with Render. I accept the centralisation. I’m not buying it for the sovereignty thesis. I’m buying it because 69 million rendered frames and 279% burn growth (per Render Foundation reports) suggest real product-market fit, and the BME mechanism will reward that adoption if it continues.

AKT is a bet on permissionless compute becoming the default. The revenue is smaller but growing, verifiable and diversifying beyond crypto-native customers. BME went live in March 2026 and is now burning AKT on-chain, though modestly. At 32x P/Revenue with 128% growth, the valuation is reasonable if the growth trajectory holds.

I don’t hold IO. Self-reported revenue with a verification gap, 98% drawdown from ATHATHAll-Time High. The highest price a token has ever reached. ATH is usually quoted as a reference point for how far the current price has fallen (or risen) since the peak.Like the record lap time on a racetrack. It tells you what the car has been capable of at its absolute best, not what it will do today. Whether that record gets broken again depends on conditions that may or may not come back.Read more →, ongoing token unlocks and no on-chain governance make it too opaque for my risk tolerance. The enterprise partnerships and revenue growth may be real; $5.7M in Q1 2025 is genuine traction if accurate. If io.net closes the gap between headline metrics and verifiable on-chain data, I’ll reassess.

The broader lesson: freedom and returns are genuinely in tension for compute networks today. The sovereignty stack maps this tension across all five layers of the DeAI infrastructure. Render proves that centralisation can produce better short-term returns. Akash bets that freedom produces more durable infrastructure. Both can be right on different timescales. The question is which timescale you’re investing for.