> For the complete documentation index, see [llms.txt](https://docs.swanchain.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.swanchain.io/core-concepts/swan-2.0-inference-cloud/become-a-provider.md). # Become a Provider This guide walks through turning your GPU into an AI inference endpoint on Swan Chain — from starting a local model server, to installing the `computing-provider` agent, to earning stablecoin revenue from real inference traffic. {% hint style="info" %} Looking to **consume** models instead of provide? See [How to Use Swan Inference](/core-concepts/swan-2.0-inference-cloud/how-to-use.md). For hardware tiers, collateral economics, revenue splits, and slashing rules, see the [Provider Onboarding](/core-concepts/swan-2.0-inference-cloud.md#provider-onboarding) section of the Swan 2.0 overview. This page focuses on the hands-on setup. {% endhint %} ## 0. Check prerequisites Providers connect **outbound** to Swan Inference over WebSocket — **no public IP, domain, or SSL setup is required**. You just need a capable GPU and one of two supported OS/inference-engine stacks: | Platform | Minimum hardware | Inference engine | | ------------------------- | ---------------------------------------------------------- | ------------------------------------------------------------------------------ | | **Linux (NVIDIA)** | GPU with ≥ 8 GB VRAM (Tier C); 24 GB+ recommended (Tier A) | [SGLang](https://github.com/sgl-project/sglang) (recommended), vLLM, or Ollama | | **macOS (Apple Silicon)** | M1/M2/M3/M4 with ≥ 16 GB unified memory | [Ollama](https://ollama.com) | Legacy GPUs (TESLA P4, GTX 1050 Ti, anything < 8 GB VRAM) cannot serve modern inference workloads and will not receive traffic. Full tier-to-model mapping is in [Hardware Tiers](/core-concepts/swan-2.0-inference-cloud.md#hardware-tiers). You'll also need: * **Go 1.22+** to build the `computing-provider` agent * **Docker 24.0+ with the NVIDIA Container Toolkit** (Linux only) * A funded wallet or credit card for collateral (step 5) ## 1. Start a model server Your GPU needs an OpenAI-compatible inference server running locally. Swan Inference will route requests to it via the `computing-provider` agent. ### Linux (NVIDIA) — SGLang ```bash # Download model weights from HuggingFace computing-provider models download Qwen/Qwen2.5-7B-Instruct # Start SGLang serving the model on port 30000 docker run -d --gpus all -p 30000:30000 --ipc=host --name sglang \ -v ~/.swan/models/Qwen/Qwen2.5-7B-Instruct:/models \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server --model-path /models \ --host 0.0.0.0 --port 30000 \ --served-model-name Qwen/Qwen2.5-7B-Instruct ``` Verify it's healthy: `curl http://localhost:30000/v1/models`. ### macOS (Apple Silicon) — Ollama ```bash brew install ollama ollama serve & ollama pull qwen2.5:7b ``` Verify it's healthy: `curl http://localhost:11434/api/tags`. {% hint style="info" %} The quickstart uses Qwen 2.5 7B as an example, but earnings scale with real token traffic. Browse the [model catalog](https://inference.swanchain.io/models) to find in-demand models with less provider competition. {% endhint %} ## 2. Install the computing-provider agent Clone and build from source (mainnet): ```bash git clone https://github.com/swanchain/computing-provider.git cd computing-provider make clean && make mainnet && sudo make install # Verify computing-provider --version ``` Full install details including the NVIDIA Container Toolkit setup are in the [`computing-provider` README](https://github.com/swanchain/computing-provider#readme). ## 3. Run the setup wizard The wizard creates your provider account (or logs you into an existing one), auto-discovers your running model server, and writes `config.toml` and `models.json`: ```bash computing-provider setup ``` A typical run looks like this (macOS + Ollama): ``` ============================================================ Computing Provider Setup Wizard ============================================================ Step 1/5: Checking Prerequisites ------------------------------------------------------------ [ok] Ollama: ollama version is 0.14.1 (running) [!] Docker: Docker not running. Please start Docker daemon. (optional - Ollama available) [ok] GPU: Apple Silicon (Apple M1) Step 2/5: Initializing Configuration ------------------------------------------------------------ Node Name [demo-provider]: demo-provider Initialized CP repo at '/Users/swanchain/.swan/computing'. [ok] Configuration initialized Step 3/5: Authentication ------------------------------------------------------------ A Swan Inference account is needed to connect your provider to the network. Do you already have a Swan Inference account [y/N]: n Create a new Swan Inference account Email: demo-provider@example.com Password: Creating account... [ok] Account created! Set up your provider profile Provider Name [demo-provider]: Wallet Address (optional, press Enter to skip): -> Skipped - you can add a wallet later to start earning rewards Registering your provider... [ok] Provider registered! -> Provider ID: 84bca13d-d056-4826-a1ca-ac4d43597a9c -> Status: pending (your provider will be reviewed before it can earn rewards) [!] SAVE THIS API KEY - it connects your machine to Swan Inference and is only shown once. API Key: sk-prov-535a****fb47 Step 4/5: Discovering Model Servers ------------------------------------------------------------ [ok] Found ollama at localhost:11434 * qwen3:8b Matching with Swan Inference models... [ok] qwen3:8b -> Qwen/Qwen3-8B (100%) Step 5/5: Finalizing Setup ------------------------------------------------------------ Select models to enable: 1) Qwen/Qwen3-8B - ollama @ http://localhost:11434 ~16GB (local: qwen3:8b) Enter selections (e.g., 1,3,4) or press Enter for all [all]: [ok] Updated config.toml [ok] Created models.json ============================================================ Setup Complete! ============================================================ What to do next: * Start your provider: computing-provider run * Monitor in browser: computing-provider dashboard * Check connection: computing-provider inference status ``` **Save the `sk-prov-*` key** — it's shown once and authenticates this provider to the network. If you already have a `sk-prov-*` key (for example, from the web signup at [inference.swanchain.io/provider-signup](https://inference.swanchain.io/provider-signup)), pass it directly: ```bash computing-provider setup --api-key=sk-prov-xxxxxxxxxxxx ``` Config files land in `~/.swan/computing/`: * `config.toml` — WebSocket URL, API key, node name * `models.json` — mapping from Swan Inference model IDs to your local endpoints {% hint style="info" %} Consumer keys (`sk-swan-*`) and provider keys (`sk-prov-*`) are different. The `computing-provider` agent only accepts `sk-prov-*` keys. {% endhint %} ### Configuration reference The wizard writes sensible defaults, but if it failed to discover your model server, you run a non-standard port, or you want to serve multiple models, edit these files directly. **Provider config (`~/.swan/computing/config.toml`)** ```toml # ~/.swan/computing/config.toml [API] Port = 8085 MultiAddress = "/ip4//tcp/" NodeName = "" [RPC] SWAN_CHAIN_RPC = "https://rpc-proxima.swanchain.io" [Inference] Enable = true WebSocketURL = "wss://api-ws-dev.swanchain.io" ApiKey = "sk-prov-YOUR_API_KEY" Models = ["Qwen/Qwen2.5-7B-Instruct"] ``` **Model endpoints (`~/.swan/computing/models.json`)** ```json { "Qwen/Qwen2.5-7B-Instruct": { "endpoint": "http://localhost:30000", "gpu_memory": 16000, "category": "text-generation" }, "meta-llama/Llama-3.2-3B-Instruct": { "endpoint": "http://localhost:11434", "gpu_memory": 14000, "category": "text-generation", "local_model": "llama3.2:3b" } } ``` | Field | Required | Description | | ------------- | -------- | ------------------------------------------------------------------------ | | `endpoint` | Yes | URL of your local inference server (SGLang, vLLM, Ollama) | | `gpu_memory` | Yes | GPU VRAM used by this model in MB | | `category` | Yes | Model type: `text-generation`, `image`, `embedding`, `audio` | | `local_model` | No | Local model name if different from the key (e.g., Ollama's `qwen2.5:7b`) | | `api_key` | No | API key if your model server requires authentication | The keys in `models.json` must match valid Swan Inference model IDs. Run `computing-provider models catalog` or check the [model catalog](https://inference.swanchain.io/models) for the full list. The agent watches `models.json` and hot-reloads on change — no restart needed. You can also force a reload: ```bash curl -X POST http://localhost:8085/api/v1/computing/inference/models/reload ``` ## 4. Start the provider and pass benchmarks Run the agent: ```bash nohup computing-provider run >> cp.log 2>&1 & ``` Then check your status: ```bash computing-provider inference status ``` You'll move through these stages automatically: ``` Connect ──▶ Collateral ──▶ Approval ──▶ Active (instant) (see step 5) (< 24 hrs) (earning) ``` | Stage | What happens | Typical duration | | -------------- | ---------------------------------------------------------------------------------------------------------------- | ---------------- | | **Connect** | Agent opens a WebSocket to Swan Inference, registers your models, and auto-runs math / code / latency benchmarks | Instant | | **Collateral** | Deposit via Stripe or on-chain SWAN (step 5) | Instant | | **Approval** | Admin reviews your benchmark results and collateral | < 24 hours | | **Active** | Traffic starts flowing — you earn per-request revenue | Ongoing |
Provider activation stages shown in the dashboard

The My Provider tab visualizes the activation flow: Start → Connect → Deposit Collateral → Approved → Active & Earning.

## 5. Deposit collateral Once approved, deposit collateral to unlock full traffic routing. Two options: | Method | Currency | Processing | Refund | | ------------ | --------------------------- | -------------------- | ------------------------------------------- | | **Stripe** | Credit/debit card (USD) | Instant | 7-day waiting period, back to original card | | **On-chain** | SWAN tokens on Swan Mainnet | Requires SwanETH gas | 7-day waiting period, back to your wallet | ```bash # Show instructions for your account (deposit address, minimum amount) computing-provider inference deposit # Verify deposit was seen on-chain computing-provider inference deposit --check ```
Provider collateral deposit panel

Provider dashboard's Collateral Deposit panel — verify your wallet, then pay the required amount via Stripe or on-chain crypto.

Collateral amounts scale with hardware tier and earning multiplier. See [Computing Provider Collateral](/core-concepts/token/computing-provider-collateral.md) for the full table. ## 6. Monitor earnings and uptime The Provider dashboard at [inference.swanchain.io/dashboard](https://inference.swanchain.io/dashboard) shows live earnings, request counts, and benchmark history.
Provider earnings dashboard

Earnings dashboard with live request volume, per-model breakdown, and payout history.

For a local view, the agent ships its own web dashboard: ```bash computing-provider dashboard # → http://localhost:3005 ``` Set where payouts go: ```bash computing-provider inference set-beneficiary 0xYourWalletAddress ``` {% hint style="info" %} **New Provider Grace Period:** For the first 7 days after activation, uptime and success-rate deprioritization are waived. Use this window to stabilize your setup before full routing weight kicks in. {% endhint %} ## Switching or adding models Edit `~/.swan/computing/models.json` — the agent watches this file and hot-reloads without restarting. Start additional model servers on different ports and add them all to the JSON. Full walkthrough with multi-GPU pinning is in the [`computing-provider` README](https://github.com/swanchain/computing-provider#switching-models). ## Troubleshooting | Symptom | Fix | | ----------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `invalid provider API key` | Verify key starts with `sk-prov-` and check `ApiKey` in `~/.swan/computing/config.toml` | | `WebSocket connection failed` | Confirm outbound port 443 is open; URL must be `wss://` not `http://` | | Provider online but no requests | Model name mismatch — `--served-model-name` must exactly match the key in `models.json` and a model ID in the [catalog](https://inference.swanchain.io/models) | | `could not select device driver "nvidia"` | Install the NVIDIA Container Toolkit; see [`computing-provider` README](https://github.com/swanchain/computing-provider#install-nvidia-container-toolkit) | | Stuck in `pending` | Provider needs collateral + passing benchmark + hardware check. Run `computing-provider inference status` to see which condition is missing | Full troubleshooting catalog: [`computing-provider` README — FAQ](https://github.com/swanchain/computing-provider#faq). ## Next steps * [**Provider Onboarding**](/core-concepts/swan-2.0-inference-cloud.md#provider-onboarding) — hardware tiers, revenue split, slashing rules * [**Computing Provider Income**](/core-concepts/token/swan-provider-income.md) — contribution score formula and reward distribution * [**Computing Provider Collateral**](/core-concepts/token/computing-provider-collateral.md) — required amounts and refund process * [**Inference Marketplace**](/core-concepts/market-provider/inference-marketplace.md) — how pricing, routing, and settlement work under the hood Questions? Reach the team on [Discord](https://discord.gg/swanchain) or open an issue on the [`computing-provider` repo](https://github.com/swanchain/computing-provider/issues).