Nscale (EU Sovereign)

https://docs.nscale.com/docs/inference/chat

:::tip

We support ALL Nscale models, just set model=nscale/<any-model-on-nscale> as a prefix when sending litellm requests

:::

Required Variables

os.environ["NSCALE_API_KEY"] = ""  # your Nscale API key

Explore Available Models

Explore our full list of text and multimodal AI models — all available at highly competitive pricing: 📚 Full List of Models

Key Features

• EU Sovereign: Full data sovereignty and compliance with European regulations
• Ultra-Low Cost (starting at $0.01 / M tokens): Extremely competitive pricing for both text and image generation models
• Production Grade: Reliable serverless deployments with full isolation
• No Setup Required: Instant access to compute without infrastructure management
• Full Control: Your data remains private and isolated

Usage - LiteLLM Python SDK

Text Generation

from litellm import completion

os.environ["NSCALE_API_KEY"] = ""  # your Nscale API key
response = completion(
    model="nscale/meta-llama/Llama-4-Scout-17B-16E-Instruct",
    messages=[{"role": "user", "content": "What is LiteLLM?"}]
)
print(response)

from litellm import completion

os.environ["NSCALE_API_KEY"] = ""  # your Nscale API key
stream = completion(
    model="nscale/meta-llama/Llama-4-Scout-17B-16E-Instruct",
    messages=[{"role": "user", "content": "What is LiteLLM?"}],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content is not None:
        print(chunk.choices[0].delta.content, end="")

Image Generation

from litellm import image_generation

os.environ["NSCALE_API_KEY"] = ""  # your Nscale API key
response = image_generation(
    model="nscale/stabilityai/stable-diffusion-xl-base-1.0",
    prompt="A beautiful sunset over mountains",
    n=1,
    size="1024x1024"
)
print(response)

Usage - LiteLLM Proxy

Add the following to your LiteLLM Proxy configuration file:

model_list:
  - model_name: nscale/meta-llama/Llama-4-Scout-17B-16E-Instruct
    litellm_params:
      model: nscale/meta-llama/Llama-4-Scout-17B-16E-Instruct
      api_key: os.environ/NSCALE_API_KEY
  - model_name: nscale/meta-llama/Llama-3.3-70B-Instruct
    litellm_params:
      model: nscale/meta-llama/Llama-3.3-70B-Instruct
      api_key: os.environ/NSCALE_API_KEY
  - model_name: nscale/stabilityai/stable-diffusion-xl-base-1.0
    litellm_params:
      model: nscale/stabilityai/stable-diffusion-xl-base-1.0
      api_key: os.environ/NSCALE_API_KEY

Start your LiteLLM Proxy server:

litellm --config config.yaml

# RUNNING on http://0.0.0.0:4000

from openai import OpenAI

# Initialize client with your proxy URL
client = OpenAI(
    base_url="http://localhost:4000",  # Your proxy URL
    api_key="your-proxy-api-key"       # Your proxy API key
)

# Non-streaming response
response = client.chat.completions.create(
    model="nscale/meta-llama/Llama-4-Scout-17B-16E-Instruct",
    messages=[{"role": "user", "content": "What is LiteLLM?"}]
)

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

# Configure LiteLLM to use your proxy
response = litellm.completion(
    model="litellm_proxy/nscale/meta-llama/Llama-4-Scout-17B-16E-Instruct",
    messages=[{"role": "user", "content": "What is LiteLLM?"}],
    api_base="http://localhost:4000",
    api_key="your-proxy-api-key"
)

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

curl http://localhost:4000/v1/chat/completions \\
  -H "Content-Type: application/json" \\
  -H "Authorization: Bearer your-proxy-api-key" \\
  -d '{
    "model": "nscale/meta-llama/Llama-4-Scout-17B-16E-Instruct",
    "messages": [{"role": "user", "content": "What is LiteLLM?"}]
  }'

Getting Started

1. Create an account at console.nscale.com
2. Claim free credit
3. Create an API key in settings
4. Start making API calls using LiteLLM

Additional Resources

• Nscale Documentation
• Blog: Sovereign Serverless