Token Station

One API key, one format — access every model across 12 AI providers.

OpenAI 1.2B tkns Anthropic 980M tkns Gemini 870M tkns Groq 650M tkns xAI 420M tkns Bailian 380M tkns ALL SYSTEMS OK 4.5B TOKENS MAIN DISPLAY 99%
Get Started Available Models
OpenAI
Anthropic
Google Gemini
xAI Grok
Groq
Alibaba Bailian
Moonshot Kimi
MiniMax
Zhipu GLM
Kling AI
BytePlus
ElevenLabs
OpenAI
Anthropic
Google Gemini
xAI Grok
Groq
Alibaba Bailian
Moonshot Kimi
MiniMax
Zhipu GLM
Kling AI
BytePlus
ElevenLabs
🔌
OpenAI Compatible API
🧪
12 Model Labs
🤖
100+ Models
💬
Chat & Reasoning
👨‍💻
Coding
🛠️
Agentic Tools & Skills
🔗
MCPs
👁️
Image Understanding
🎨
Image Creation
🎬
Video Creation
🎤
Speech to Text
🔊
Text to Speech

Supported APIs

Chat Completions — Stateless LLM with Images /v1/chat/completions

Send messages to any LLM provider. Supports text, images, streaming, and tool use. The gateway automatically translates between OpenAI, Anthropic, and Gemini formats.

curl -X POST http://GATEWAY/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer gw-YOUR_KEY" \
  -d '{
    "model": "openai/gpt-5.4",
    "messages": [
      {"role": "system", "content": "You are helpful."},
      {"role": "user", "content": [
        {"type": "text", "text": "What is in this image?"},
        {"type": "image_url", "image_url": {"url": "https://example.com/photo.jpg"}}
      ]}
    ],
    "max_completion_tokens": 1024,
    "stream": true
  }'
from openai import OpenAI

client = OpenAI(
    base_url="http://GATEWAY/v1",
    api_key="gw-YOUR_KEY"
)

response = client.chat.completions.create(
    model="openai/gpt-5.4",
    messages=[
        {"role": "system", "content": "You are helpful."},
        {"role": "user", "content": [
            {"type": "text", "text": "What is in this image?"},
            {"type": "image_url", "image_url": {"url": "https://example.com/photo.jpg"}}
        ]}
    ],
    max_completion_tokens=1024,
    stream=True
)

for chunk in response:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")
Responses API — Stateful LLM with Images /v1/responses

Stateful conversation API with built-in context management. Supports OpenAI, Anthropic, Groq, xAI, and Bailian providers.

curl -X POST http://GATEWAY/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer gw-YOUR_KEY" \
  -d '{
    "model": "anthropic/claude-sonnet-4-6",
    "input": [
      {
        "role": "user",
        "content": [
          {"type": "input_text", "text": "Describe this image in detail."},
          {"type": "input_image", "image_url": "https://example.com/photo.jpg"}
        ]
      }
    ]
  }'
from openai import OpenAI

client = OpenAI(
    base_url="http://GATEWAY/v1",
    api_key="gw-YOUR_KEY"
)

response = client.responses.create(
    model="anthropic/claude-sonnet-4-6",
    input=[
        {
            "role": "user",
            "content": [
                {"type": "input_text", "text": "Describe this image in detail."},
                {"type": "input_image", "image_url": "https://example.com/photo.jpg"}
            ]
        }
    ]
)

print(response.output_text)
Speech to Text /v1/audio/transcriptions

Transcribe audio files using OpenAI Whisper models. Supports mp3, mp4, mpeg, mpga, m4a, wav, and webm.

curl -X POST http://GATEWAY/v1/audio/transcriptions \
  -H "Authorization: Bearer gw-YOUR_KEY" \
  -F file=@audio.mp3 \
  -F model=openai/gpt-4o-transcribe
from openai import OpenAI

client = OpenAI(
    base_url="http://GATEWAY/v1",
    api_key="gw-YOUR_KEY"
)

with open("audio.mp3", "rb") as f:
    transcript = client.audio.transcriptions.create(
        model="openai/gpt-4o-transcribe",
        file=f
    )

print(transcript.text)
Text to Speech /v1/audio/speech

Convert text to natural-sounding speech using OpenAI TTS models. Voices: alloy, echo, fable, onyx, nova, shimmer.

curl -X POST http://GATEWAY/v1/audio/speech \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer gw-YOUR_KEY" \
  -d '{
    "model": "openai/tts-1",
    "input": "Hello, world! Welcome to Token Station.",
    "voice": "alloy"
  }' --output speech.mp3
from openai import OpenAI

client = OpenAI(
    base_url="http://GATEWAY/v1",
    api_key="gw-YOUR_KEY"
)

response = client.audio.speech.create(
    model="openai/tts-1",
    input="Hello, world! Welcome to Token Station.",
    voice="alloy"
)

response.stream_to_file("speech.mp3")
Image Generation /v1/images/generations

Generate images from text prompts. Supports OpenAI DALL-E / GPT Image, Google Imagen, and xAI Grok.

curl -X POST http://GATEWAY/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer gw-YOUR_KEY" \
  -d '{
    "model": "openai/gpt-image-1.5",
    "prompt": "A sunset over mountains, oil painting style",
    "n": 1,
    "size": "1024x1024"
  }'
from openai import OpenAI

client = OpenAI(
    base_url="http://GATEWAY/v1",
    api_key="gw-YOUR_KEY"
)

response = client.images.generate(
    model="openai/gpt-image-1.5",
    prompt="A sunset over mountains, oil painting style",
    n=1,
    size="1024x1024"
)

print(response.data[0].url)
Video Generation /v1/video/generations

Generate videos from text or images. Supports Gemini Veo, Kling, Bailian Wan, BytePlus Seedance, xAI Grok, and OpenAI Sora. The gateway handles async polling internally.

# Text-to-video
curl -X POST http://GATEWAY/v1/video/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer gw-YOUR_KEY" \
  -d '{
    "model": "gemini/veo-3.1-generate-preview",
    "prompt": "A timelapse of a flower blooming in a garden",
    "aspect_ratio": "16:9"
  }'

# Image-to-video
curl -X POST http://GATEWAY/v1/video/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer gw-YOUR_KEY" \
  -d '{
    "model": "kling/kling-v3-0",
    "prompt": "The character turns and walks away",
    "image": "https://example.com/photo.jpg",
    "duration": 5,
    "aspect_ratio": "16:9"
  }'
import openai

client = openai.OpenAI(
    base_url="http://GATEWAY/v1",
    api_key="gw-YOUR_KEY"
)

# Text-to-video (custom endpoint)
response = client.post(
    "/v1/video/generations",
    body={
        "model": "gemini/veo-3.1-generate-preview",
        "prompt": "A timelapse of a flower blooming in a garden",
        "aspect_ratio": "16:9"
    },
    cast_to=object
)

print(response)