Inference Marketplace

Decentralized AI Inference Marketplace for Real-Time Model Serving

The Inference Marketplace is Swan Chain's decentralized platform for AI model serving, introduced as part of Swan 2.0. Unlike the existing AI Computing Marketplace which handles training workloads through task auctions, the Inference Marketplace provides real-time, low-latency AI inference through persistent WebSocket connections and an OpenAI-compatible API.

How It Works

Request Lifecycle

Consumer                Swan Inference              Provider
   │                         │                         │
   │  POST /v1/chat/...      │                         │
   │────────────────────────▶│                         │
   │                         │  Select best provider   │
   │                         │  (load balancing)        │
   │                         │                         │
   │                         │  Forward via WebSocket   │
   │                         │────────────────────────▶│
   │                         │                         │  Run inference
   │                         │  Stream response         │
   │                         │◀────────────────────────│
   │  Stream response        │                         │
   │◀────────────────────────│                         │
   │                         │                         │
   │                         │  Record usage            │
   │                         │  (tokens, latency)       │

1. Consumer sends an inference request via the REST API with their API key

2. Swan Inference selects the best available provider using health-aware load balancing

3. The request is forwarded to the provider over a persistent WebSocket connection

4. The provider runs inference on their GPU and streams the response back

5. Swan Inference records usage metrics (tokens processed, latency, success/failure)

6. Usage is aggregated for billing and settlement

Provider Connection Modes

Mode	Description	Use Case
WebSocket Provider	GPU provider running computing-provider agent, connects via WebSocket	Primary path — no public IP required
External Endpoint	Existing OpenAI-compatible server (vLLM, TGI, OpenAI API) registered with Swan	Fallback — for providers with existing infrastructure

The response includes an X-Swan-Connection-Mode header indicating which path was used.

Provider Registration and Collateral

Registration Flow

1. Sign up at the Swan Inference dashboard

2. Upgrade to provider and receive a provider API key (sk-prov-*)

3. Deposit collateral — stablecoin (USDC/USDT on-chain) or USD (via payment gateway)

4. Connect via WebSocket using the computing-provider agent

5. Pass benchmark — initial verification (math, code, latency tests)

6. Begin serving — provider becomes active and receives inference requests

Collateral Options

Type	Method	Verification
Stablecoin (USDC/USDT)	On-chain deposit to ProviderCollateral contract	Automatic on-chain tx verification
USD	Stripe, PayPal, or bank transfer	Admin confirmation with payment reference

Collateral status follows the lifecycle: pending → confirmed → refund_requested → refunded

The refund waiting period is 7 days from the time of request, ensuring all pending settlements are cleared before funds are released.

See Computing Provider Collateral for detailed collateral amounts and slashing rules.

Request Routing and Load Balancing

Swan Inference routes requests using configurable load balancing strategies:

Strategy	Description
Health-Aware	Routes to the provider with the best health score (default)
Round-Robin	Distributes requests evenly across providers
Least-Connections	Routes to the provider with the fewest active requests

Additional routing features:

• Health monitoring with automatic circuit breaker for unhealthy providers

• Model warmup to pre-load models and reduce cold-start latency

• Retry and failover — up to 2 retries with exponential backoff if a provider fails

• Rate limiting per API key with tiered limits by model category

Rate Limits (Default)

Category	Requests/min
LLM	200
Image	60
Embedding	500
Other	200

Pricing Model

Consumer Pricing

Pricing varies by model category:

Category	Pricing Unit	Examples
LLM	Per input token + per output token	Chat completions, text generation
Embedding	Per token	Text embeddings
Image	Per request	Image generation
Audio	Per request	Transcription

Prices are listed transparently in the model catalog at inference.swanchain.io/models. The default marketplace currency is USDC.

Platform Fee

The platform charges a 5% fee on each transaction. This fee funds protocol operations, staking rewards, and SWAN token burns.

Revenue Distribution

When a consumer pays for an inference request:

Recipient	Share	Description
Provider	70%	Paid in the request currency (USDC)
Protocol Treasury	20%	Funds ecosystem development
SWAN Buyback & Burn	10%	Deflationary mechanism

Settlement

Off-Chain Ledger

Usage is tracked in real time on an off-chain payment ledger:

• Every inference request records: tokens processed, latency, model used, provider, consumer

• Provider earnings accumulate in the ledger

• Consumers are billed based on aggregated usage

On-Chain Settlement

Settlement uses a MerkleDistributor smart contract for gas-efficient batch payouts:

1. Daily batches — Provider earnings are aggregated into settlement batches

2. Merkle tree — A Merkle tree is computed from all provider balances in the batch

3. On-chain submission — The Merkle root is submitted to the smart contract

4. Provider claims — Providers claim their earnings by submitting a Merkle proof

Settlement status follows: pending → submitted → confirmed

This approach settles many provider payments in a single on-chain transaction, minimizing gas costs.

Minimum Payout

Providers must accumulate a minimum balance (default: $50) before a payout is triggered. This prevents dust transactions and reduces gas costs.

Provider Earnings

Providers earn through two complementary streams:

1. Inference Revenue (Stablecoins)

Direct payment for serving inference requests, paid in the consumer's currency (typically USDC). This is the primary revenue stream and scales with the number of requests served.

2. Contribution Rewards (SWAN Tokens)

Daily SWAN token rewards allocated proportionally based on the provider's Contribution Score. This replaces the legacy UBI model and rewards providers for:

• Inference volume (requests processed)

• Token throughput (tokens generated)

• Uptime and availability

• Quality (success rate, latency)

• Model diversity (number of models served)

Earnings Dashboard

The provider dashboard provides:

• Daily/weekly/monthly earnings views with CSV export

• Per-model performance metrics (requests, success rate, tokens processed)

• Collateral status and on-chain deposit tracking

• Wallet verification via MetaMask for secure payouts

Subscription Plan

Swan Inference offers a Pro subscription alongside the existing pay-as-you-go credit model.

Pro Plan — $6/month

Feature	Pay-As-You-Go	Pro Subscription
Price	No fee, deposit credits	$6/month
Open-source models	Pay per token	Included (40M tokens/week, 1,500 req/day)
Premium models	Pay per token	Pay per token (from credit balance)
Images	Pay per image	75/day included
Payment	Stripe or crypto	Stripe (recurring) or crypto prepay

Subscriptions can be paid with stablecoins (USDC/USDT) or SWAN token. SWAN payments receive a 10% discount.

Provider Earnings Under Subscription

Providers earn the same per-token rate for subscription requests as pay-as-you-go. Total provider payouts from subscription requests are capped at the subscription revenue pool ($6 x subscriber count per month). If provider costs exceed the pool, payouts are pro-rated proportionally across providers based on their contribution.

Public Playground

The platform includes a public playground at inference.swanchain.io/playground that allows anyone to try AI inference without an API key. The playground is rate-limited to 5 requests per hour per IP, with a restricted model selection and limited token output. This provides a zero-friction entry point for new users to evaluate the platform before signing up.

Comparison with AI Computing Marketplace

Feature	AI Computing Marketplace	Inference Marketplace
Workload	Training, batch compute	Real-time inference
Latency	Minutes to hours	Milliseconds to seconds
Allocation	Task auction (bidding)	Real-time routing (WebSocket)
Payment	Per task	Per token / per request
Connection	Job-based	Persistent WebSocket
API	Swan SDK / Orchestrator	OpenAI-compatible REST API

Both marketplaces coexist within the Swan ecosystem, serving different use cases. The Inference Marketplace is optimized for interactive AI applications, while the AI Computing Marketplace handles batch training and compute-intensive tasks.

Learn More

• Swan 2.0: Inference Cloud — Overview of the Swan 2.0 platform

• Computing Provider Income — Contribution scoring and reward distribution

• Computing Provider Collateral — Collateral requirements and slashing