Swan Inference API

Call 42+ AI Models via an OpenAI-Compatible API

Swan Inference provides an OpenAI-compatible REST API for accessing decentralized AI models. If you've used the OpenAI API or any OpenAI-compatible client, you already know how to use Swan Inference — just change the base URL and API key.

Base URL: https://inference.swanchain.io

Quick Start

1. Get an API Key

Sign up at inference.swanchain.io to get your API key. Keys use the sk-swan- prefix.

2. Make Your First Request

cURL

curl https://inference.swanchain.io/v1/chat/completions \
  -H "Authorization: Bearer sk-swan-YOUR-API-KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-r1-distill-llama-70b",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "What is Swan Chain?"}
    ]
  }'

Python

JavaScript

Go

That's it — any library or tool that supports the OpenAI API format works with Swan Inference.

---

Try Without an API Key

Swan Inference offers a public playground that lets you try AI inference without signing up.

curl https://inference.swanchain.io/v1/playground/chat \
  -H "Content-Type: application/json" \
  -d '{
    "model": "MadeAgents/Hammer2.1-0.5b",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

No Authorization header required. To list available playground models:

curl https://inference.swanchain.io/v1/playground/models

Limit	Value
Requests per hour	5 per IP
Max output tokens	100
Streaming	Not supported

For full access to all models with higher limits, sign up for a free account.

Subscription Plan

For heavy users, Swan Inference offers a Pro plan at $6/month with unlimited open-source model access:

Feature	Pay-As-You-Go	Pro ($6/month)
Open-source models	Pay per token	Included
Premium models	Pay per token	Pay per token
Requests/day	Unlimited	1,500
Tokens/week	Unlimited	40M
Payment	Credit balance	Stripe or crypto (USDC/USDT/SWAN)

---

Authentication

All API requests require an API key passed in the Authorization header:

Authorization: Bearer sk-swan-YOUR-API-KEY

Key Prefix	Purpose
sk-swan-*	Consumer API key — for making inference requests
sk-prov-*	Provider API key — for GPU providers connecting to the network

---

API Endpoints

List Models

Retrieve all available models and their current status.

GET /v1/models

curl https://inference.swanchain.io/v1/models \
  -H "Authorization: Bearer sk-swan-YOUR-API-KEY"

Response:

{
  "object": "list",
  "data": [
    {
      "id": "deepseek-r1-distill-llama-70b",
      "object": "model",
      "owned_by": "swan-inference"
    },
    {
      "id": "llama-3.2-3b",
      "object": "model",
      "owned_by": "swan-inference"
    }
  ]
}

You can also browse the full model catalog with pricing at inference.swanchain.io/models.

---

Chat Completions

Generate chat-based text responses. This is the primary endpoint for interacting with LLMs.

POST /v1/chat/completions

Request Body:

Parameter	Type	Required	Description
model	string	Yes	Model ID (e.g., deepseek-r1-distill-llama-70b)
messages	array	Yes	Array of message objects with role and content
temperature	float	No	Sampling temperature (0-2). Default: 1.0
max_tokens	integer	No	Maximum tokens to generate. Default: model-dependent
stream	boolean	No	Enable streaming responses. Default: false
top_p	float	No	Nucleus sampling threshold. Default: 1.0
stop	string/array	No	Stop sequence(s)
frequency_penalty	float	No	Frequency penalty (-2 to 2). Default: 0
presence_penalty	float	No	Presence penalty (-2 to 2). Default: 0

Example — Standard Request:

curl https://inference.swanchain.io/v1/chat/completions \
  -H "Authorization: Bearer sk-swan-YOUR-API-KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "llama-3.2-3b",
    "messages": [
      {"role": "user", "content": "Explain blockchain in one sentence."}
    ],
    "temperature": 0.7,
    "max_tokens": 100
  }'

Response:

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1709500000,
  "model": "llama-3.2-3b",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Blockchain is a decentralized, distributed digital ledger that records transactions across many computers so that no single record can be altered retroactively without the alteration of all subsequent blocks."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 12,
    "completion_tokens": 38,
    "total_tokens": 50
  }
}

---

Streaming

Enable real-time token-by-token responses by setting stream: true. The response uses Server-Sent Events (SSE).

cURL

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

Python

JavaScript

Stream Response Format:

Each SSE event contains a JSON chunk:

data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","choices":[{"delta":{"content":"Silicon"},"index":0}]}

data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","choices":[{"delta":{"content":" hearts"},"index":0}]}

data: [DONE]

---

Embeddings

Generate vector embeddings for text. Useful for search, similarity, and RAG applications.

POST /v1/embeddings

Request Body:

Parameter	Type	Required	Description
model	string	Yes	Embedding model ID
input	string/array	Yes	Text to embed (string or array of strings)

Example:

curl https://inference.swanchain.io/v1/embeddings \
  -H "Authorization: Bearer sk-swan-YOUR-API-KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "bge-large-en-v1.5",
    "input": "Swan Chain is a decentralized AI computing blockchain."
  }'

Response:

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [0.0023, -0.0091, 0.0152, ...]
    }
  ],
  "model": "bge-large-en-v1.5",
  "usage": {
    "prompt_tokens": 10,
    "total_tokens": 10
  }
}

---

Image Generation

Generate images from text prompts.

POST /v1/images/generations

Request Body:

Parameter	Type	Required	Description
model	string	Yes	Image model ID (e.g., flux-1-schnell)
prompt	string	Yes	Text description of the image to generate
n	integer	No	Number of images to generate. Default: 1
size	string	No	Image size (e.g., 1024x1024)

Example:

curl https://inference.swanchain.io/v1/images/generations \
  -H "Authorization: Bearer sk-swan-YOUR-API-KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "flux-1-schnell",
    "prompt": "A futuristic data center powered by blockchain, digital art style",
    "n": 1,
    "size": "1024x1024"
  }'

Response:

{
  "created": 1709500000,
  "data": [
    {
      "url": "https://inference.swanchain.io/images/generated/abc123.png"
    }
  ]
}

---

Audio Transcription

Transcribe audio files to text.

POST /v1/audio/transcriptions

Request Body (multipart/form-data):

Parameter	Type	Required	Description
file	file	Yes	Audio file (mp3, mp4, wav, webm, etc.)
model	string	Yes	Audio model ID (e.g., whisper-large-v3)
language	string	No	Language code (e.g., en)

Example:

curl https://inference.swanchain.io/v1/audio/transcriptions \
  -H "Authorization: Bearer sk-swan-YOUR-API-KEY" \
  -F file="@audio.mp3" \
  -F model="whisper-large-v3"

Response:

{
  "text": "Hello, welcome to Swan Chain's decentralized AI inference platform."
}

---

Supported Models

Swan Inference hosts 42+ models across five categories:

Category	Models	Pricing
LLM	DeepSeek R1 (70B), Llama 3 (3B, 8B, 70B), Qwen 2.5, Mistral, Phi-3	Per input/output token
Image	FLUX.1 Schnell, Stable Diffusion XL	Per request
Audio	Whisper Large V3	Per request
Embedding	BGE Large, E5 Large	Per token
Multimodal	Llama 3.2 Vision, Qwen-VL	Per token

Model availability depends on online providers. Check real-time status at inference.swanchain.io/models or call GET /v1/models.

---

Rate Limits

Requests are rate-limited per API key:

Model Category	Requests per Minute
LLM	200
Image	60
Embedding	500
Other	200

Maximum concurrent requests: 100 per API key.

When rate-limited, the API returns HTTP 429 Too Many Requests with a Retry-After header.

---

Request Limits

Parameter	Limit
Max input tokens (LLM)	128,000
Max output tokens (LLM)	16,384
Max input tokens (Embedding)	8,192
Max request body size	10 MB
Max messages per request	100
Max message length	100,000 characters
Request timeout	120 seconds

---

Error Handling

The API returns standard HTTP error codes with JSON error bodies:

{
  "error": {
    "message": "Invalid API key provided",
    "type": "authentication_error",
    "code": "invalid_api_key"
  }
}

Status Code	Meaning
400	Bad request — check your request body
401	Unauthorized — invalid or missing API key
404	Model not found or no providers available
429	Rate limit exceeded — slow down
500	Internal server error
503	Service unavailable — all providers busy

The platform automatically retries failed requests (up to 2 retries with exponential backoff) when a provider is temporarily unavailable, so most transient errors are handled transparently.

---

Response Headers

Swan Inference includes helpful headers in every response:

Header	Description
X-Request-ID	Unique request correlation ID for tracing
X-Swan-Connection-Mode	How the request was routed: websocket or external

Use X-Request-ID when contacting support or debugging request issues.

---

Using with LLM Frameworks

Swan Inference works with any framework that supports OpenAI-compatible APIs.

LangChain (Python)

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    base_url="https://inference.swanchain.io/v1",
    api_key="sk-swan-YOUR-API-KEY",
    model="deepseek-r1-distill-llama-70b",
)

response = llm.invoke("What is decentralized AI?")
print(response.content)

LlamaIndex

from llama_index.llms.openai_like import OpenAILike

llm = OpenAILike(
    api_base="https://inference.swanchain.io/v1",
    api_key="sk-swan-YOUR-API-KEY",
    model="deepseek-r1-distill-llama-70b",
)

response = llm.complete("Explain DePIN in simple terms.")
print(response.text)

LiteLLM

import litellm

response = litellm.completion(
    model="openai/deepseek-r1-distill-llama-70b",
    messages=[{"role": "user", "content": "Hello!"}],
    api_base="https://inference.swanchain.io/v1",
    api_key="sk-swan-YOUR-API-KEY",
)

print(response.choices[0].message.content)

Vercel AI SDK (TypeScript)

import { createOpenAI } from "@ai-sdk/openai";
import { generateText } from "ai";

const swan = createOpenAI({
  baseURL: "https://inference.swanchain.io/v1",
  apiKey: "sk-swan-YOUR-API-KEY",
});

const { text } = await generateText({
  model: swan("deepseek-r1-distill-llama-70b"),
  prompt: "What is Swan Chain?",
});

console.log(text);

---

Pricing

Category	Pricing Unit	Billed In
LLM	Per input token + per output token	USDC
Embedding	Per token	USDC
Image	Per request	USDC
Audio	Per request	USDC

View current pricing for each model at inference.swanchain.io/models.

Token usage is included in every response under the usage field.

---

Network Stats

Public endpoints are available for monitoring network health:

Endpoint	Description
GET /api/v1/stats/network	Aggregate network stats (providers, requests, capacity)
GET /api/v1/stats/leaderboard	Provider leaderboard ranked by performance
GET /api/v1/stats/gpu	GPU distribution and VRAM capacity across the network
GET /api/v1/stats/utilization	Network utilization metrics
GET /api/v1/stats/model-demand	Model demand data (useful for providers choosing which models to serve)
GET /api/v1/dashboard/summary	Dashboard summary with request and capacity metrics

These endpoints do not require authentication.

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Learn More

• Swan 2.0: Inference Cloud — Architecture and platform overview

• Inference Marketplace — How the marketplace works (routing, pricing, settlement)

• Model Catalog — Browse all available models with real-time availability and pricing