Swan 2.0: Inference Cloud

Decentralized AI Inference Marketplace — Swan Chain's Next Evolution

Overview

Swan 2.0 marks Swan Chain's evolution from a UBI-subsidized computing network into a market-driven AI inference marketplace. Built as the Inference Cloud, it connects AI model consumers with GPU providers through a decentralized coordination layer, enabling anyone to access AI models via a single API key — or earn stablecoin revenue by sharing their GPU resources.

Try Swan Inference: https://inference.swanchain.io

New here? See How to Use Swan Inference for a step-by-step guide, or jump to live pricing comparison against Anthropic, Google, and OpenRouter.

Swan 2.0 replaces UBI with inference revenue per SIP-003. UBI tapers to zero over 3 months. See also SIP-002 for the original transition proposal.

What Changes in Swan 2.0

Aspect	Swan 1.0 (UBI Model)	Swan 2.0 (Inference Cloud)
Provider Rewards	Flat UBI sampling	95% inference revenue (stablecoins)
Payment	SWAN tokens only	Stablecoins (USDC/USDT) + Pay-with-SWAN (20% discount)
Provider Roles	Separate ECP and FCP	Unified Computing Provider (CP)
Collateral	SWAN tokens only	SWAN tokens or Stripe (credit card)
Work Verification	Random sampling tasks	Periodic benchmarks (math, code, latency)
Workloads	Training, ZK proofs	AI inference (LLM, image, audio, embedding, multimodal)
Hardware Requirements	None (any GPU earned UBI)	Tiered: min 8GB VRAM, legacy GPUs rejected

Architecture

Swan Inference uses a hub-and-spoke architecture where the central platform coordinates between consumers and providers:

┌─────────────────────────────────────────────────────────────────┐
│                    External Consumers                            │
│              (Meganova AI, LiteLLM, Direct API)                 │
└─────────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────────┐
│                      SWAN INFERENCE                              │
│  ┌─────────────────┐          ┌─────────────────────────────┐   │
│  │  REST API        │          │  WebSocket Hub              │   │
│  │  (Port 8100)     │─────────▶│  (Port 8081)                │   │
│  │                  │          │  - Provider connections      │   │
│  │  /api/v1/*       │          │  - Inference dispatch        │   │
│  │  /v1/* (OpenAI)  │          │  - Load balancing            │   │
│  │                  │          │  - Health monitoring          │   │
│  └─────────────────┘          └─────────────────────────────┘   │
└─────────────────────────────────────────────────────────────────┘
                    │                         │
                    ▼ WebSocket               ▼ HTTP (fallback)
┌───────────────────────────────┐  ┌─────────────────────────────┐
│      GPU Providers            │  │   External Endpoints         │
│  (H100, A100, 4090, 3090)    │  │   (vLLM, TGI, OpenAI API)   │
└───────────────────────────────┘  └─────────────────────────────┘

Request Flow:

1. Consumer sends a request to the REST API

2. The Hub checks for available WebSocket providers

3. If WebSocket providers are available: route via WebSocket (primary path)

4. If no WebSocket providers: route to External Endpoints (fallback)

5. Response includes X-Swan-Connection-Mode header indicating which route was used

Key Components

Component	Role
REST API	OpenAI-compatible consumer-facing API
WebSocket Hub	Real-time provider connections, inference dispatch, load balancing
Marketplace Service	Model catalog, search, pricing
Payment Ledger	Off-chain usage tracking, invoicing
Benchmark Sampler	Periodic quality checks and scoring
Settlement Batcher	On-chain settlement via MerkleDistributor

OpenAI-Compatible API

Swan Inference provides a drop-in replacement for OpenAI's API. Any existing OpenAI SDK or integration works with Swan Inference by changing the base URL and API key.

Supported Endpoints

Endpoint	Description
/v1/chat/completions	Chat-based text generation (streaming supported)
/v1/embeddings	Text embeddings
/v1/images/generations	Image generation
/v1/audio/transcriptions	Audio-to-text transcription
/v1/models	List available models

Example Request

curl https://inference.swanchain.io/v1/chat/completions \
  -H "Authorization: Bearer sk-swan-YOUR-KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-r1-distill-llama-70b",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Model Catalog

Swan Inference serves two categories of models with different economics. The live catalog at inference.swanchain.io/models is the source of truth for current availability and pricing.

Frontier Gateway

Closed frontier models (Claude, Gemini) proxied at a consistent discount to direct API pricing. These run on the upstream provider's infrastructure — Swan acts as an aggregator, passing on cost savings through bulk agreements and SWAN token incentives.

Example	Direct pricing	Swan pricing	Savings
Claude Opus 4.6	$5.00 / $25.00 per 1M tokens	$4.00 / $20.00	~20%
Gemini 2.5 Flash	$0.30 / $2.50 per 1M tokens	$0.18 / $1.50	~40%

With Pay-with-SWAN, the discount stacks to 50–66% below going direct. See the pricing comparison for the live side-by-side.

Open-Source on Decentralized GPUs

Open-source models served by Swan's decentralized provider network. This is where Swan's economics structurally beat centralized providers — any qualifying GPU owner (datacenter to consumer hardware) can become a provider and share in inference revenue.

Example	Params	Swan pricing	Hardware tier
Qwen3 Coder 30B	30B MoE	$0.05 / $0.10 per 1M tokens	A (24GB)
GLM 4.7 Flash	—	$0.05 / $0.36 per 1M tokens	A (24GB)
Sapphira L3.3 70B	70B	$0.20 / $0.30 per 1M tokens	S (38GB+)
Whisper Large v3	—	$0.003 per minute	C (8GB+)

Open-source models are priced 50–66% below comparable centralized providers via the hardware tier system. See Hardware Tiers under Provider Onboarding for the full VRAM-to-model mapping.

Free Tier

Parameter	Specification
Available Models	Stheno 8B, Qwen3 8B (Tier B only)
Daily Token Limit	50,000 tokens (~25 conversations)
Rate Limit	5 requests per minute
Concurrency	1 simultaneous request
Registration	API key only (free, no KYC)
Upgrade Path	USDC top-up or Pay-with-SWAN

Payment & Revenue Split

Dual Deposit Options

Swan 2.0 accepts both stablecoins and SWAN as deposits into a single USD-denominated prepaid balance. SWAN deposits receive a 20% bonus in credits at deposit time, creating organic buy pressure for the token.

Deposit Method	Bonus	Example (depositing $100)
USDC/USDT (Stripe or crypto)	0%	$100 of credits
SWAN on Swan Mainnet	+20%	$120 of credits

Pay-with-SWAN flow:

1. Consumer deposits SWAN tokens to their per-user deposit address on Swan Mainnet

2. Balance is credited in USD at the current SWAN/USD rate plus a 20% bonus

3. Subsequent inference requests draw from this unified USD balance

4. Providers receive 95% of the per-request fee in their preferred payout currency (USDC or SWAN)

5. 5% goes to the Growth Fund

Provider-First Revenue Split (95/5)

During the bootstrap phase, Swan adopts an aggressive provider-first model to attract quality hardware:

Recipient	Share	Purpose
Computing Provider	95%	Direct payout in stablecoins (USDC/USDT)
Growth Fund	5%	Provider recruitment, integrations, dev tooling, liquidity
Protocol Treasury	0%	Deferred until network reaches sustainability threshold

The Growth Fund is reinvested into network expansion — provider onboarding bounties, DEX liquidity seeding, and integration grants. Spending is reported monthly with transaction hashes.

Dynamic Revenue Split Schedule

As network revenue grows, the split adjusts through governance votes:

Phase	Daily Revenue	Provider	Growth Fund	Treasury
Bootstrap	< $100	95%	5%	0%
Growth	$100 – $1,000	90%	5%	5%
Maturity	$1,000 – $10,000	85%	3% + 2% burn	10%
Scale	> $10,000	80%	2% + 3% burn	15%

Each phase transition requires a governance vote with a 7-day voting period. Revenue thresholds are measured as a 30-day rolling average.

Quality Assurance

Benchmarks

The benchmark worker runs periodically (default: every 24 hours) to verify provider quality. Benchmark results expire after 30 days — providers that miss benchmarks for 30+ days lose qualification and must re-benchmark to resume receiving traffic.

Test	Pass Threshold
Math Accuracy	≥ 50%
Code Generation	≥ 50%
Response Latency	≤ 5000ms

Slashing Conditions

Condition	Consequence
Benchmark failure (1st)	Warning + 24h suspension from task routing
Consecutive failure (2nd)	10% collateral slashed
Consecutive failure (3rd)	30% collateral slashed + network removal
Benchmark results expired (> 30 days)	Loses qualification until re-benchmarked
Inference success rate < 80%	Deprioritized in request routing
Uptime < 90% (30-day rolling)	Deprioritized in request routing

New Provider Grace Period: Providers registered within the last 7 days are exempt from uptime and success-rate deprioritization. This gives new providers time to build history without being penalized for insufficient data. Benchmark requirements and probation still apply during the grace period.

Health Monitoring

• Automatic health checks with configurable thresholds for WebSocket and external endpoints

• Circuit breaker to prevent cascading failures

• Load balancing with health-aware routing (round-robin, least-connections, or health-aware strategies)

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

Provider Leaderboard

Providers are ranked by a performance-based leaderboard using availability metrics, success rates, and latency.

Provider Onboarding

Hardware Tiers

To receive inference traffic and earn revenue, providers must meet minimum hardware requirements:

Tier	Min VRAM	Example Hardware	Models	Status
S	38GB+	L40S, A100, H100	70B premium models	Recruiting new providers
A	24GB	RTX 4090, 3090, A6000	24B–32B agent models	Activate idle inventory
B	12GB	RTX 4070 Ti, 3080 Ti	8B–12B free tier	Some current providers
C	8GB	RTX 3070, 4060	Embedding, Whisper	Lowest qualifying tier
macOS	16GB+ unified	Apple Silicon M1/M2/M3/M4	8B–12B via Ollama	Entry-level providers
Rejected	< 8GB or legacy	TESLA P4, GTX 1050 Ti	None	No rewards

Legacy GPUs (TESLA P4, GTX 1050 Ti) served the network well during the ZK-task era but cannot serve AI inference workloads at acceptable quality.

macOS Support: Apple Silicon Macs can serve as providers using Ollama as the inference backend. While datacenter GPUs offer higher throughput, Macs are a low-friction entry point for new providers — no Docker, NVIDIA drivers, or Linux required.

Requirements

Linux (NVIDIA GPU):

• GPU meeting at least Tier C requirements (≥ 8GB VRAM)

• Docker 24.0+ with NVIDIA Container Toolkit

• Inference server: SGLang (recommended), vLLM, or Ollama

macOS (Apple Silicon):

• Apple Silicon Mac (M1/M2/M3/M4) with 16GB+ unified memory

• Ollama installed (brew install ollama)

Both platforms:

• Swan's computing-provider agent installed

• No public IP, domain, or SSL setup required — providers connect via WebSocket behind NAT/firewall

• Pass initial inference benchmark (math, code, latency)

• Maintain > 50% uptime over a trailing 7-day window

Registration Flow

1. Sign up at the Swan Inference dashboard and get a provider API key (sk-prov-*)

2. Start a model server — SGLang/vLLM (Linux) or Ollama (macOS)

3. Install and run the computing-provider agent — the setup wizard auto-discovers your models

4. Pass benchmarks — automated quality verification runs within minutes of connecting

5. Admin approval — most providers are approved within 24 hours

6. Deposit collateral via Stripe (credit card) or SWAN tokens on-chain

7. Start earning — receive inference requests with a 7-day grace period for full traffic priority

Collateral

Providers must deposit collateral to become active on the network. Two deposit methods are available:

Method	Currency	Processing	Refund
Stripe	Credit/debit card (USD)	Instant	Refunded to original card (7-day waiting period)
On-chain	SWAN tokens	Requires gas (SwanETH)	Returned to wallet (7-day waiting period)

See Computing Provider Collateral for details on collateral amounts and the refund waiting period.

On-Chain Settlement

Swan Inference uses a MerkleDistributor smart contract for gas-efficient batch settlement:

1. The platform aggregates provider earnings into daily settlement batches

2. A Merkle tree is computed from all provider balances

3. The Merkle root is submitted on-chain

4. Providers claim their earnings by submitting a Merkle proof

This approach minimizes gas costs by settling many provider payments in a single on-chain transaction.

Smart Contracts

Contract	Address (Swan Chain Mainnet)
ProviderCollateral	0x557f306f917009cf83c32b8b32a79202e79948e5
SWAN Token	0xAF90ac6428775E1Be06BAFA932c2d80119a7bd02

Swan Chain Mainnet operates on Chain ID 254 with RPC at https://mainnet-rpc01.swanchain.io. See Network Info for full details.

UBI Sunset (SIP-003)

Swan 2.0 eliminates UBI entirely per SIP-003. Providers earn solely from inference revenue (95% of fees). The taper schedule:

Period	UBI Level	SWAN/day	Notes
Swan 2.0 Launch (Mar 16 – Apr 9)	100%	58,369	Platform goes live, governance vote Apr 1–7
Month 1 post-vote (Apr 10 – May 9)	50%	29,185	Contribution-weighted; legacy hardware earns zero
Month 2 post-vote (May 10 – Jun 9)	20%	11,674	Providers earn primarily from inference
Month 3+ (Jun 10 onwards)	0%	0	UBI permanently off. Inference revenue only.

Why Stop UBI

Under Swan 1.0, 75% of daily UBI went to providers with 0% uptime. SIP-003 redirects all incentives toward GPUs that actually serve inference. The breakeven where inference revenue matches the best current UBI payout is just $25/day total network revenue.

Safety Valve

If the network cannot sustain minimum viable provider economics ($50/day revenue) by Month 3, governance can vote to extend UBI at 25% (contribution-weighted only) for 3 additional months.

SWAN Token Utility

After UBI stops, SWAN token utility is:

Utility	Description
Pay-with-SWAN	20% inference discount for consumers — creates organic buy pressure
Provider Collateral	Required deposit to join the network
Governance	Vote on protocol parameters, revenue splits, and phase transitions

Learn More

• Inference Marketplace — How the marketplace works: pricing, routing, and settlement

• Computing Provider Income — Contribution score formula and reward distribution

• Computing Provider Collateral — Collateral requirements and slashing

• SIP-001: FCP Subsidy Program — Stage 1 funding for computing providers

• SIP-002: Unified CP & Contribution Rewards — Original transition proposal

• SIP-003: Inference Cloud Economics — Full model catalog, 95/5 revenue split, UBI sunset, Pay-with-SWAN