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DecentralGPT

DecentralGPT (DGC) — 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).

DecentralGPT — an AI/Inference | Infra project on BNB Smart Chain: described in the whitepaper as a decentralized network for inference (LLM inference network) with distributed GPU nodes and the DGC token (Tier‑1 whitepaper + BscScan).

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/platform for running inference of large language models (LLM) on distributed GPU nodes (per the whitepaper).
  • Who it’s for: users/developers who need access to model inference; GPU node operators (mining/rewards).
  • What you can actually touch (Tier‑1): the DeGPT web product (the “Get Started” link on the official website).
  • Why onchain/token: in the whitepaper, the token is used in the network economy (mining/rewards, payments/burn); addresses of the protocol’s onchain contracts (other than the token) are not confirmed by Tier‑1 sources.

How it works (very briefly)

  1. The user does: sends a model inference request.
  2. The system does: a distributed coordinator selects GPU nodes, inference is performed; data may be stored in distributed storage (per the whitepaper).
  3. The user gets: the model’s response (text/code, etc. — per the whitepaper).
  4. Where the blockchain is: the whitepaper mentions onchain selection/reward mechanics; among verifiable onchain facts, the DGC token on the BNB Smart Chain network is confirmed.
  5. Token role (if any): economic incentives (rewards to GPU miners/developers) and payments with a burn mechanic (per the whitepaper).

Quick links: AI thesis fit

Project passport

Field Value
Project name DecentralGPT
Also known as (aliases) DGC; Decentral GPT
Logo (logo) —
Token symbol (ticker) DGC
Category AI/Inference | Infra
Primary chain (chain) BNB Smart Chain
Type EVM
Network status mainnet
Consensus (consensus) PoSA (BNB Smart Chain; 21 validators)
Launch date (launch_date) —
Project status (status) active
Token (standard) BEP-20
Token contract 0x9cfAE8067322394e34E6b734c4a3F72aCC4a7Fe5
Token model (token_type) utility (payments + staking + rewards)
Max supply 600,000,000,000 DGC (onchain max total supply)
Issuance fixed (per max total supply)
Tokenomics (tokenomics, brief) rewards to GPU nodes/developers; the user subscription is “100% automatically burned” (Tier‑1 Nodes)
Governance —
Admins/keys —
Audit —
Bug bounty —
Team (team) —
Funding (investors/funding) —
AI component (ai_component) positioning only (distributed LLM inference network)
Use‑case (use_case) LLM inference + distributed GPU nodes
DecAI Fit — AI thesis fit 3/6 — medium alignment with the Decentralized AI thesis
DecAI Fit component summary 3 / 1 / 2 / 0
Last verified 2026-02-11

General project overview

In the whitepaper, DecentralGPT is described as a “decentralized AI large language model inference network” that supports several open‑source LLMs, uses distributed GPU nodes, a P2P network and distributed storage (the text mentions IPFS). The roles “client node / distributed coordinator / distributed computing node” are described, as well as an economic model with rewards for the participation of GPU nodes.

Features/modules

  • Decentralized LLM inference on distributed GPU nodes (per the whitepaper).
  • Coordination/distribution of tasks and load balancing (per the whitepaper).
  • Economics: mining/rewards and a burn mechanic for payments (per the whitepaper).

Typical scenarios

  • Scenario 1: a user sends a request → the distributed network processes the inference → returns a response.
  • Scenario 2: a GPU node operator provides computation → receives rewards in the token (per the mining rewards description).

Getting started (wallet/network)

  • What you need: access to the website/documentation; for the token — an EVM wallet and BNB for gas.
  • Network/chain: BNB Smart Chain (the DGC token).
  • Fees: BSC fees for onchain operations.

Architecture/tech (non‑AI)

  • Components (per the whitepaper): UI/client, coordinator, GPU nodes, P2P network, distributed storage.
  • Where logic runs: inference runs on GPU nodes; the onchain part is described conceptually (selection/rewards), but addresses of the protocol contracts (other than the token) are not confirmed by Tier‑1 sources.

Token/economics (expanded, no forecasts)

  • Rewards: a model of rewards to GPU miners and a share for model developers is described (per the whitepaper).
  • Payments + burn: it is stated that user payments (for example monthly fees) are “100% automatically destroyed” (per the whitepaper).
  • Supply conflict: the whitepaper contains a wording about a “1 trillion” total supply, but the onchain max total supply on BscScan shows 600B DGC — this requires re‑checking.

Governance

Not established per Tier‑1 sources.

Security and incidents

  • Audits / bug bounty / advisories: no confirmation found in Tier‑1 sources.

Project status and timeline

  • Roadmap: present in the whitepaper.

AI component of the project

  • What is real AI here? The Tier‑1 whitepaper explicitly describes an LLM inference network and the processing of requests on distributed nodes.
  • What is truly onchain? The DGC token on BNB Smart Chain; the rest of the onchain logic is described conceptually and requires addresses/contracts for strict verification.
  • Why is a token needed? In the whitepaper, the token is used for rewards/incentives and payments with a burn mechanic.
  • Red flags (based on the information found): onchain‑washing — if “onchain” remains at the level of words without addresses/contracts; what to double‑check — where exactly the protocol logic is implemented onchain and which contracts/networks are used (including the “DBC EVM chain” from the whitepaper).

DecAI Fit component summary

  • DecAI Fit: 3/6 — medium alignment with the Decentralized AI thesis
Component Level Score
AI reality medium 3
Onchain necessity low 1
Token necessity medium 2
Evidence Tier‑1 present 0
Details

AI reality

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

  • AI_0 (decision): 0
  • Claim (one line): AI is described as a functional product (LLM inference network), not just intent.
  • Evidence: Tier‑1 — https://www.decentralgpt.org/wp-content/uploads/2025/07/DecentralGPT-WhitePapper.pdf
  • Why sufficient / why not (one line): we use AI_0 only when there is intent without evidence; here there is a Tier‑1 description of the AI feature.
  • Conflict note (if any): —

AI_1 — what the AI does (1/0)

  • AI_1 (decision): 1
  • Claim (one line): the system processes requests and performs inference of large language models (LLM).
  • Evidence: Tier‑1 — https://www.decentralgpt.org/wp-content/uploads/2025/07/DecentralGPT-WhitePapper.pdf
  • Why sufficient / why not (one line): the whitepaper explicitly describes the “model inference network” function.
  • Conflict note (if any): —

AI_2 — demos/examples (1/0)

  • AI_2 (decision): 1
  • Claim (one line): the official website has a “Get Started” link to the DeGPT web product.
  • Evidence: Tier‑1 — https://www.decentralgpt.org/ ; https://www.degpt.ai
  • Why sufficient / why not (one line): there is a Tier‑1 “what you can touch” artifact (a web product).
  • Conflict note (if any): —

AI_3 — metrics/quality (1/0)

  • AI_3 (decision): 0
  • Metrics: —
  • Context (version/date/how measured): —
  • Evidence: Tier‑1 — —
  • Why sufficient / why not (one line): the whitepaper has no sufficient reproducible metrics of model/inference quality.
  • Conflict note (if any): —

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

  • AI_4 (decision): 1
  • Claim (one line): the system architecture is described (UI/coordinator/GPU nodes/P2P/storage).
  • Evidence: Tier‑1 — https://www.decentralgpt.org/wp-content/uploads/2025/07/DecentralGPT-WhitePapper.pdf
  • Why sufficient / why not (one line): the whitepaper includes an architectural description (system components and flow).
  • Conflict note (if any): —

Onchain necessity

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

  • OC_1 (decision): 1
  • Chain: BNB Smart Chain
  • Addresses/identifiers: token DGC: 0x9cfAE8067322394e34E6b734c4a3F72aCC4a7Fe5
  • Evidence: Tier‑1 — https://bscscan.com/token/0x9cfAE8067322394e34E6b734c4a3F72aCC4a7Fe5
  • Why sufficient / why not (one line): the onchain fact of the token is confirmed by the explorer.
  • Conflict note (if any): —

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

  • OC_2 (decision): 0
  • What useful logic is onchain: the whitepaper mentions onchain mechanics, but without addresses/contracts for strict verification.
  • Evidence: Tier‑1 — https://www.decentralgpt.org/wp-content/uploads/2025/07/DecentralGPT-WhitePapper.pdf
  • Why sufficient / why not (one line): without specific addresses/contracts we do not consider “onchain beyond just a token” proven.
  • Conflict note (if any): —

OC_3 — onchain is critical (1/0)

  • OC_3 (decision): 0
  • “Replace the blockchain” test: not proven per Tier‑1; the documents contain no strict argument that a key property of the product breaks down without the blockchain.
  • Evidence: Tier‑1 — —
  • Why sufficient / why not (one line): there is no sufficient Tier‑1 justification for OC_3.
  • Conflict note (if any): —

Token necessity

TK_0 — no token (1/0)

  • TK_0 (decision): 0
  • Claim (one line): the project has a token, DGC, on BNB Smart Chain.
  • Evidence: Tier‑1 — https://bscscan.com/token/0x9cfAE8067322394e34E6b734c4a3F72aCC4a7Fe5
  • Why sufficient / why not (one line): the token is confirmed by the explorer.
  • 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): the whitepaper describes user payments/fees that are “100% burned”.
  • Evidence: Tier‑1 — https://www.decentralgpt.org/wp-content/uploads/2025/07/DecentralGPT-WhitePapper.pdf
  • Why sufficient / why not (one line): the existence of a payment function of the token is claimed in the Tier‑1 documentation.
  • Conflict note (if any): —

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

  • TK_2 (decision): 1
  • Claim (one line): the token is used for rewards to GPU miners and model developers.
  • Evidence: Tier‑1 — https://www.decentralgpt.org/wp-content/uploads/2025/07/DecentralGPT-WhitePapper.pdf
  • Why sufficient / why not (one line): the whitepaper describes mining rewards and the distribution of shares.
  • Conflict note (if any): —

TK_3 — governance (1/0)

  • TK_3 (decision): 0
  • Claim (one line): the governance role of the token is not established per Tier‑1 sources.
  • Evidence: Tier‑1 — —
  • Why sufficient / why not (one line): in the whitepaper, governance via the token is not singled out as a verifiable mechanic.
  • Conflict note (if any): —

TK_4 — token is replaceable (1/0)

  • TK_4 (decision): 0
  • Claim (one line): no conclusion about the replaceability of the token has been drawn.
  • Evidence: Tier‑1 — —
  • Why sufficient / why not (one line): there is no Tier‑1 comparison “with the token/without the token”.
  • Conflict note (if any): CONFLICT: supply of 1T in the whitepaper vs 600B max total supply on BscScan.

Evidence (table)

Tier Source What it proves
Tier‑1 https://www.decentralgpt.org/wp-content/uploads/2025/07/DecentralGPT-WhitePapper.pdf LLM inference network, architecture, mining rewards, burn of user payments
Tier‑1 https://www.decentralgpt.org/ Links to the DeGPT web product (“Get Started”) and the project’s mobile apps.
Tier‑1 https://www.decentralgpt.org/nodes/ The claim that the subscription price is “100% automatically and immediately destroyed (burn)”; description of GPU mining.
Tier‑1 https://bscscan.com/token/0x9cfAE8067322394e34E6b734c4a3F72aCC4a7Fe5 token DGC: network, contract, onchain max total supply
Tier‑1 — No Tier‑1 source for claim “there are addresses of the protocol’s onchain contracts (other than the token)” was found.

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