Skip to main content
Prerequisites:
  • A Valid Qubrid AI Account logged in the platform
  • Enough Credits in your Account should be present to make sure the requests get processed
  • A Valid API Ke to be replaced in YOUR_API_KEY section, generated using steps mentioned in How to generate an API Key

​
Mistral 7B Instruct v0.3 - View Model

  import requests, json, base64

url = "https://platform.qubrid.com/api/v1/qubridai/chat/completions"
headers = {"Authorization": "Bearer YOUR_API_KEY"}

headers["Content-Type"] = "application/json"
data = {
  "model": "mistralai/Mistral-7B-Instruct-v0.3",
  "messages": [
    {
      "role": "user",
      "content": "Explain quantum computing simply."
    }
  ],
  "temperature": 0.7,
  "max_tokens": 500
}
response = requests.post(url, headers=headers, json=data)
print(json.dumps(response.json(), indent=2))

# Expected Output:
# {"choices": [{"message": {"content": "Quantum computing uses qubits..."}}]}

​
GPT-OSS 20B - View Model

import requests, json, base64

url = "https://platform.qubrid.com/api/v1/qubridai/chat/completions"
headers = {"Authorization": "Bearer YOUR_API_KEY"}

headers["Content-Type"] = "application/json"
data = {
  "model": "openai/gpt-oss-20b",
  "messages": [
    {
      "role": "user",
      "content": "Explain quantum computing simply."
    }
  ],
  "temperature": 0.7,
  "max_tokens": 500
}
response = requests.post(url, headers=headers, json=data)
print(json.dumps(response.json(), indent=2))

# Expected Output:
# {"choices": [{"message": {"content": "Quantum computing uses qubits..."}}]}

​
IBM Granite 20B Code Instruct - View Model

import requests, json, base64

url = "https://platform.qubrid.com/api/v1/qubridai/chat/completions"
headers = {"Authorization": "Bearer YOUR_API_KEY"}

headers["Content-Type"] = "application/json"
data = {
  "model": "ibm-granite/granite-20b-code-instruct-8k",
  "messages": [
    {
      "role": "user",
      "content": "Explain quantum computing simply."
    }
  ],
  "temperature": 0.7,
  "max_tokens": 500
}
response = requests.post(url, headers=headers, json=data)
print(json.dumps(response.json(), indent=2))

# Expected Output:
# {}

​
Stable Code 3B - View Model

import requests, json, base64

url = "https://platform.qubrid.com/api/v1/qubridai/chat/completions"
headers = {"Authorization": "Bearer YOUR_API_KEY"}

headers["Content-Type"] = "application/json"
data = {
  "model": "stabilityai/stable-code-instruct-3b",
  "messages": [
    {
      "role": "user",
      "content": "Explain quantum computing simply."
    }
  ],
  "temperature": 0.7,
  "max_tokens": 500
}
response = requests.post(url, headers=headers, json=data)
print(json.dumps(response.json(), indent=2))

# Expected Output:
# {}

​
Qwen Image Edit - View Model

import requests, json, base64

url = "https://platform.qubrid.com/api/v1/qubridai/image/generation"
headers = {"Authorization": "Bearer YOUR_API_KEY"}

headers["Content-Type"] = "application/json"
data = {
  "model": "Qwen/Qwen-Image-Edit",
  "positive_prompt": "A futuristic city at sunset with flying cars",
  "width": 1024,
  "height": 1024,
  "steps": 30,
  "cfg": 7.5,
  "seed": 42
}
response = requests.post(url, headers=headers, json=data)
print(json.dumps(response.json(), indent=2))

# Expected Output:
# Binary PNG image stream (save with open('generated.png','wb').write(response.content))

​
Stable Diffusion - View Model

import requests, json, base64

url = "https://platform.qubrid.com/api/v1/qubridai/image/generation"
headers = {"Authorization": "Bearer YOUR_API_KEY"}

headers["Content-Type"] = "application/json"
data = {
  "model": "stabilityai/stable-diffusion-3.5-large",
  "positive_prompt": "A futuristic city at sunset with flying cars",
  "width": 1024,
  "height": 1024,
  "steps": 30,
  "cfg": 7.5,
  "seed": 42
}
response = requests.post(url, headers=headers, json=data)
print(json.dumps(response.json(), indent=2))

# Expected Output:
# Binary PNG image stream (save with open('generated.png','wb').write(response.content))

​
Whisper Large V3 - View Model

import requests, json, base64

url = "https://platform.qubrid.com/api/v1/qubridai/audio/transcribe"
headers = {"Authorization": "Bearer YOUR_API_KEY"}

files = {"file": open("audio.wav", "rb")}
data = {"model": "openai/whisper-large-v3"}
response = requests.post(url, headers=headers, files=files, data=data)
print(response.json())

# Expected Output:
# {"text": "Welcome to Qubrid AI", "language": "en"}

​
Qwen3-VL 8B Instruct - View Model

import requests, json, base64

url = "https://platform.qubrid.com/api/v1/qubridai/multimodal/chat"
headers = {"Authorization": "Bearer YOUR_API_KEY"}

headers["Content-Type"] = "application/json"
data = {
  "model": "Qwen/Qwen3-VL-8B-Instruct",
  "prompt": "Explain quantum computing simply.",
  "temperature": 0.7,
  "max_tokens": 500
}
response = requests.post(url, headers=headers, json=data)
print(json.dumps(response.json(), indent=2))

# Expected Output:
# {"choices": [{"message": {"content": "A brown cat sitting on a chair."}}]}

​
Qwen2.5-VL 7B instruct - View Model

import requests, json, base64

url = "https://platform.qubrid.com/api/v1/qubridai/multimodal/chat"
headers = {"Authorization": "Bearer YOUR_API_KEY"}

headers["Content-Type"] = "application/json"
data = {
  "model": "Qwen/Qwen2.5-VL-7B-Instruct",
  "prompt": "Explain quantum computing simply.",
  "temperature": 0.7,
  "max_tokens": 500
}
response = requests.post(url, headers=headers, json=data)
print(json.dumps(response.json(), indent=2))

# Expected Output:
# {"choices": [{"message": {"content": "A brown cat sitting on a chair."}}]}