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// Chapter 12 · Concepts

The Demand Side: ParalleliX AI

Where the network's work comes from.

2 min0 sectionsConcepts

Where the work comes from.

// 12.0 · ParalleliX AI · the demand side · open-source models on network compute

// Demand path

Sign up, fund credits, send a prompt, dispatch, receive. Five steps.

The live demand is ParalleliX AI, a consumer chat app (ChatGPT / Claude style) that runs open-source models on network compute. Deposits live in an on-chain vault (withdraw any time) and the operator share settles on-chain per request; spending is metered off-chain, so it is not trustless per message. Using it costs $PRLX, metered as credits. Each prompt is one inference request the coordinator dispatches whole to a single capable registered node; a single inference is autoregressive and is not split across nodes. The user sends a message and gets a response.

Open ParalleliX AITelegram botai.parallelix.io · t.me/ParalleliXAIbot
// Console · ParalleliX AI · chat
ParalleliX. AIcredits · off-chain
Summarize this paper's method in three bullets.
The method has three parts: first, it

Deposit $PRLX once on-chain, metered off-chain (no per-message gas). The request runs whole on a registered operator node and returns a Proof-of-Execution. Open-source models, custodial v1.

The chat surface. Deposit $PRLX into the on-chain vault; every prompt is metered off-chain against the credit balance with no per-message gas; withdraw any time.

// Console · Open-source model · running on the pool
parallelix ai // open-source model · running8 live
requests routed to capable nodesoss-models
node-11
99%rtx-4090
node-13
91%rtx-4090
node-15
88%a6000
node-04
87%rtx-4090
node-08
78%a6000
node-07
72%a6000
node-02
61%rtx-4090
node-09
··rtx-3090
answers streamingcredits · metered off-chain
1980 TFLOPS · fp168 streaming

Under the chat: each whole inference request streams on its own node across a heterogeneous GPU pool. Throughput scales with the number of online nodes, not by splitting one prompt.

The five steps

// 12.1 · deposit once on-chain · meter off-chain · no per-message gas

// ParalleliX AI flow · 5 stepson-chain vault · off-chain metering

  1. // step 01

    Sign up

    Create a ParalleliX AI account. No wallet signature is needed to use the app once credits are funded.

  2. // step 02

    Fund credits

    Deposit $PRLX into the on-chain ParalleliXAICredits vault. The coordinator mirrors it to a spendable balance; there is no per-message gas. Withdraw unspent credits any time. Sign in once with your wallet to authorize spending.

  3. // step 03

    Send a prompt

    The request is metered off-chain (message_cost = model_rate × tokens_processed) and debited from the credit balance.

  4. // step 04

    Dispatch

    The coordinator routes the inference to a registered operator node in the pool, or to project-operated fallback hardware (project GPUs / server CPU) when no network node is online.

  5. // step 05

    Receive

    The model response streams back. The $PRLX spent flows to the credit ledger, and a share settles to the operators whose nodes served the work.

How a prompt is metered

// 12.2 · message_cost = model_rate × tokens_processed · off-chain

Caveat·Illustrative

The figures below are illustrative. Exact model rates and the token-accounting surface are not finalised before v1. The shape is canonical: deposit once on-chain, meter off-chain per request.
// metering · illustrative
// ParalleliX AI · off-chain metering (illustrative)
deposit            on-chain vault → spendable credits (withdraw any time)
sign-in            wallet signature → session (authorizes spend)
prompt             "summarise this paper"
model_rate         0.0000040 PRLX / token
tokens_processed   1,420
message_cost       model_rate × tokens_processed = 0.00568 PRLX
debit              off-chain meter (no per-message gas)
dispatch           → online node  (fallback: project GPU / server CPU)
settle             operator share on-chain, per served request

What the credit buys

// 12.3 · metering, inference, settlement

// Credit covers · 3 stages

  • // 01Metering

    Off-chain debit of message_cost = model_rate × tokens_processed against the funded credit balance. No per-message gas.

  • // 02Inference

    Open-source models run on network compute. Each request is dispatched whole to one capable registered node (or to fallback hardware), since a single inference is not split across nodes.

  • // 03Settlement

    A share of the spent $PRLX settles to the operators whose nodes served the request. This is the steady-state operator funding source.

The pipeline is general enough to accept direct compute submissions paid in $PRLX, but a permissionless open compute marketplace for third-party submitters is planned, not live. Today the demand is ParalleliX AI, and its inference runs on the registered operator nodes.

// Where to go next · reading path