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DeepNode

DeepNode — a reference card for a crypto project: what the product does and how verifiable the project’s key claims are; also — alignment with the Decentralized AI thesis (DecAI Fit).

DeepNode — an AI/Inference / Infra project (a decentralized marketplace for model inference/validation), token (symbol: DN).

Disclaimer

Important: this page is a reference overview of the project. Within DecAIHub, we separately record a verification based on open sources within the AI thesis (what is real AI/onchain/why a token, and which sources this is based on).
This is not financial advice and not a recommendation to buy/sell/hold any asset. We do not assess price, returns, or entry/exit timing.
Conclusions are based on publicly available materials found as of the verification date. The absence of confirmation does not imply the absence of the technology.

TL;DR (for readers who are not into AI)

  • What it is: a network/marketplace where AI models can be hosted, executed (inference) and validated, and participants are rewarded for their contribution.
  • Who it’s for: model developers/creators, compute node operators, quality validators and consumers who need model inference “as a service”.
  • Why onchain/token: the network claims onchain coordination (model registration, reputation, reward distribution); DN is used as the means of payment for inference and as an incentive/governance token (per the docs).
  • What you can actually touch (Tier‑1): the DIVE dApp (wallet connect) — https://dive.deepnode.ai/

How it works (very briefly)

  1. The user does: selects a model and runs a request (inference) via the dApp/marketplace.
  2. The system does: assigns the task to executor nodes (miners) taking reputation/redundancy into account; validators check the results.
  3. The user gets: the inference result + (claimed) a verifiable execution/validation log.
  4. Where the blockchain is: protocol events are recorded onchain (registration, reputation, rewards/payouts); there is also the onchain DN token.
  5. Token role: payment for inference and the source of economic incentives (emissions/reward pools, delegation/staking, governance).

Quick links: AI thesis fit

Project passport

Field Value
Project name DeepNode
Also known as (aliases) DeepNode AI, DN, DeepNode DIVE
Logo (logo) ../assets/193_deepnode_logo.webp
Token symbol (ticker) DN
Category AI/Inference | Infra
Primary chain (chain) Ethereum
Type EVM
Network status mainnet
Consensus (consensus) PoS (Ethereum)
Launch date (launch_date) —
Project status (status) active
Token (standard) ERC-20
Token contract 0x9B6a1d4fa5d90E5f2D34130053978D14Cd301d58
Token model (token_type) utility (payments + staking + governance)
Max supply 62,000,000 DN (Max Total Supply, Etherscan)
Issuance inflationary (protocol emissions; per the docs)
Tokenomics (tokenomics, brief) the fee for running models is paid in DN and distributed among the roles; there are protocol emissions into reward pools (per the docs)
Governance DAO (as claimed; details “coming soon”)
Admins/keys —
Audit —
Bug bounty —
Team (team) —
Funding (investors/funding) $5M seed+strategic rounds (per the official blog)
AI component (ai_component) model inference + validation marketplace
Use‑case (use_case) inference marketplace
DecAI Fit — AI thesis fit 5/6 — high alignment with the Decentralized AI thesis
DecAI Fit component summary 3 / 2 / 2 / 3
Last verified 2026-02-11

General project overview

Per Tier‑1 sources, DeepNode is a “decentralized intelligence infrastructure”: a network and a marketplace where model creators, node operators and quality validators interact under a common protocol and receive rewards in DN.

In the documentation, DeepNode divides roles into Model Creators, Miners (node operators), Validators, Stakers, Backers and Consumers, and rewards are tied to the actual use of models and the completion of tasks.

Features/modules

  • Model Marketplace: a registry/marketplace of models (registration/monetization).
  • Execution Layer: execution of inference on distributed nodes.
  • Validation Layer: checks of outputs and maintenance of trust.
  • Reputation Layer: claimed onchain accounting of participants’ reputation.
  • Rewards/Fees: the model for distributing fees and emissions among the roles.
  • DIVE dApp: an interface with EVM wallet connection.

Typical scenarios

  • Scenario 1 (inference consumption): the user selects a model → pays for the run in DN → receives the result.
  • Scenario 2 (model creation): a developer publishes a model → the model is used → the author receives a share of the fees.
  • Scenario 3 (infrastructure): an operator spins up a node → executes requests → receives rewards; a validator checks outputs → receives rewards for validations.

Getting started (wallet/network)

  • What you need: an EVM wallet (for DIVE), the DN token to pay for operations (per the docs/website).
  • Network/chain: Ethereum (the DN token); launch/execution on Base is claimed in the Tier‑1 docs/website, but specific onchain addresses of the protocol (other than the token) are not recorded in this card.
  • Fees: network gas + fees in DN for running a model (per the docs).

Architecture/tech (non‑AI)

  • Components: participant roles (miners/validators/creators/stakers), the task assignment module, execution redundancy, the claimed onchain accounting/rewards logic; model metadata — IPFS (per the docs).
  • Where logic runs: inference and validations — offchain on nodes; accounting and distribution — onchain (per the docs).
  • Dependencies: EVM networks (launch on Base is claimed), IPFS.

Token/economics (expanded, no forecasts)

  • Token utility: payment for inference (usage fees) and the economic reward model for miners/creators/validators/stakers/backers (per the docs).
  • Protocol necessity drivers: the docs directly state that fees for running models are paid in DN, and that there are protocol emissions into reward pools.
  • Where fees go: distribution among the executor node, the model creator, backers (if bonded) and a small share to the treasury (per the docs).
  • Issuance: “Protocol Emissions” as the source of rewards (per the docs); the details of the emission curve/parameters are not established per Tier‑1 sources within this card.

Governance

  • Who makes decisions: a governance layer is claimed; the roles state that stakers receive voting power. The governance section in the docs is marked “Coming soon”.

Security and incidents

  • Security model (claimed): onchain accounting of reputation and economic rules, transparent logs of task assignments/validations, role NFTs for binding identity and separating roles; a ZK layer is claimed as “coming soon”.
  • Audits/bug bounty: no public Tier‑1 links were found.

Project status and timeline

  • Current status: the DIVE dApp (wallet connect) is available; docs and a whitepaper are published.
  • Roadmap: published as a page in GitBook.

AI component of the project

  • What is real AI here? The real object is AI models that are hosted and executed on the network; the project describes an inference/validation marketplace and an economy for participants.
  • What is truly onchain? Per the docs, registration/reputation/rewards are recorded onchain; the onchain DN token is confirmed separately (Etherscan).
  • Why is a token needed? Per the docs, DN is used as the payment unit for inference and as the incentive/staking/governance mechanism.
  • Red flags (based on the information found): some of the claims about the onchain layer are described without a list of specific protocol contract addresses; model quality metrics/benchmarks (AI_3) were not found in Tier‑1.

DecAI Fit component summary

  • DecAI Fit: 5/6 — high alignment with the Decentralized AI thesis
Component Level Score
AI reality high 3
Onchain necessity medium 2
Token necessity medium 2
Evidence Tier‑1 present 3
Details

AI reality

AI_0 — AI intent (Tier‑1 roadmap) (1/0)

  • AI_0 (decision): 0
  • Claim (one line): AI is described as an operating component (not only intent/roadmap).
  • Evidence: Tier‑1 — https://deepnode.gitbook.io/docs/about-us/what-is-deepnode
  • Why sufficient / why not (one line): the docs describe the operation of the network for AI models, so the intent flag is not needed.
  • Conflict note (if any): —

AI_1 — what the AI does (1/0)

  • AI_1 (decision): 1
  • Claim (one line): the network is intended for the deployment/execution/validation of AI models and rewards contribution.
  • Evidence: Tier‑1 — https://deepnode.gitbook.io/docs/about-us/what-is-deepnode ; https://deepnode.gitbook.io/docs/platform
  • Why sufficient / why not (one line): the product function around executing and evaluating AI models is described.
  • Conflict note (if any): —

AI_2 — demos/examples (1/0)

  • AI_2 (decision): 1
  • Claim (one line): the “DeepNode DIVE Platform” dApp (wallet connect) is available for exploring/using the platform.
  • Evidence: Tier‑1 — https://dive.deepnode.ai/
  • Why sufficient / why not (one line): this is an interactive Tier‑1 artifact (app) that can be opened and used right away.
  • Conflict note (if any): —

AI_3 — metrics/quality (1/0)

  • AI_3 (decision): 0
  • Metrics: —
  • Context (version/date/how measured): —
  • Evidence: Tier‑1 — https://deepnode.ai/
  • Why sufficient / why not (one line): Tier‑1 contains marketing percentages (for example, success rate), but without a methodology/context and without reference to a specific model/version.
  • Conflict note (if any): —

AI_4 — tech description/architecture/versions (1/0)

  • AI_4 (decision): 1
  • Claim (one line): the platform architecture is described (execution/validation/reputation/governance, redundancy).
  • Evidence: Tier‑1 — https://deepnode.gitbook.io/docs/platform ; https://cdn.deepnode.ai/Whitepaper.pdf
  • Why sufficient / why not (one line): there is a Tier‑1 description of the components, roles and basic logic of the network.
  • Conflict note (if any): —

Onchain necessity

OC_1 — contracts/addresses/chain (1/0)

  • OC_1 (decision): 1
  • Chain: Ethereum
  • Addresses/identifiers: DN token 0x9B6a1d4fa5d90E5f2D34130053978D14Cd301d58
  • Evidence: Tier‑1 — https://etherscan.io/token/0x9B6a1d4fa5d90E5f2D34130053978D14Cd301d58
  • Why sufficient / why not (one line): there is a verifiable onchain token address.
  • Conflict note (if any): —

OC_2 — onchain beyond just a token (1/0)

  • OC_2 (decision): 1
  • What useful logic is onchain: the docs claim onchain accounting of registration/reputation/rewards and “automation of rewards via smart contracts”.
  • Evidence: Tier‑1 — https://deepnode.gitbook.io/docs/platform ; https://deepnode.gitbook.io/docs/platform/rewards-and-incentives
  • Why sufficient / why not (one line): Tier‑1 explicitly states that rewards are automated by smart contracts and protocol actions are recorded onchain.
  • Conflict note (if any): specific addresses of protocol contracts (other than the token) are not listed on these pages.

OC_3 — onchain is critical (1/0)

  • OC_3 (decision): 0
  • “Replace the blockchain” test: per Tier‑1 sources, no strict statement was found that a key property of the product breaks down without the blockchain (in operational form).
  • Evidence: Tier‑1 — https://deepnode.gitbook.io/docs/platform
  • Why sufficient / why not (one line): the benefits of onchain are described, but criticality is not proven by the OC_3 standard.
  • Conflict note (if any): —

Token necessity

TK_0 — no token (1/0)

  • TK_0 (decision): 0
  • Claim (one line): the protocol has a token, DN.
  • Evidence: Tier‑1 — https://etherscan.io/token/0x9B6a1d4fa5d90E5f2D34130053978D14Cd301d58
  • Why sufficient / why not (one line): the onchain token page confirms the existence of DN.
  • Conflict note (if any): —

TK_1..TK_4 (1/0)

TK_1 — payment for the service (1/0)

  • TK_1 (decision): 1
  • Claim (one line): running a model (model inference) is paid for with a fee in DN.
  • Evidence: Tier‑1 — https://deepnode.gitbook.io/docs/platform/rewards-and-incentives
  • Why sufficient / why not (one line): the docs directly state “fee (paid in DN)” when running a model.
  • Conflict note (if any): —

TK_2 — incentives/collateral/penalties (1/0)

  • TK_2 (decision): 1
  • Claim (one line): there are “Protocol Emissions” distributed via incentive pools to active participants.
  • Evidence: Tier‑1 — https://deepnode.gitbook.io/docs/platform/rewards-and-incentives
  • Why sufficient / why not (one line): the source of rewards via protocol emissions is explicitly described.
  • Conflict note (if any): —

TK_3 — governance (1/0)

  • TK_3 (decision): 1
  • Claim (one line): stakers receive voting power in governance.
  • Evidence: Tier‑1 — https://deepnode.gitbook.io/docs/platform/roles
  • Why sufficient / why not (one line): Tier‑1 links DN staking to governance rights.
  • Conflict note (if any): the governance section in the docs is marked “Coming soon”.

TK_4 — token is replaceable (1/0)

  • TK_4 (decision): 1
  • Claim (one line): no Tier‑1 proof was found that DN cannot be replaced with another payment unit without loss of meaning.
  • Evidence: Tier‑1 — https://deepnode.gitbook.io/docs/platform/rewards-and-incentives
  • Why sufficient / why not (one line): the role of the token is described, but a strict argument for irreplaceability (why the native token specifically and not USDC) is not presented.
  • Conflict note (if any): —

Evidence (table)

Tier Source What it proves
Tier‑1 https://cdn.deepnode.ai/Whitepaper.pdf the concept of an inference/validation marketplace and the economy of the roles
Tier‑1 https://deepnode.gitbook.io/docs/platform the platform architecture (execution/validation/reputation/governance)
Tier‑1 https://deepnode.gitbook.io/docs/platform/roles the roles (miners/validators/stakers/backers/creators) and their link to staking/voting
Tier‑1 https://deepnode.gitbook.io/docs/platform/rewards-and-incentives the fee in DN for running models and the distribution of fees/emissions
Tier‑1 https://dive.deepnode.ai/ an interactive dApp artifact (wallet connect)
Tier‑1 https://etherscan.io/token/0x9B6a1d4fa5d90E5f2D34130053978D14Cd301d58 the onchain parameters of the DN token (max supply, decimals, address)
Tier‑2 https://www.coingecko.com/en/coins/deepnode reference profile

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