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Baseten

LiteLLM supports both Baseten Model APIs and dedicated deployments with automatic routing.

API Types​

Model API (Default)​

  • URL: https://inference.baseten.co/v1
  • Format: baseten/<model-name> (e.g., baseten/openai/gpt-oss-120b)
  • Best for: Quick access to popular models

Dedicated Deployments​

  • URL: https://model-{id}.api.baseten.co/environments/production/sync/v1
  • Format: baseten/{8-digit-alphanumeric-code} (e.g., baseten/abcd1234)
  • Best for: Custom models, latency SLAs
tip

Automatic Routing: LiteLLM detects the type based on model format:

  • 8-digit alphanumeric codes → Dedicated deployment
  • All other formats → Model API

Quick Start​

import os
from litellm import completion

os.environ['BASETEN_API_KEY'] = "your-api-key"

# Model API (default)
response = completion(
    model="baseten/openai/gpt-oss-120b",
    messages=[{"role": "user", "content": "Hello!"}]
)

# Dedicated deployment (8-digit ID)
response = completion(
    model="baseten/abcd1234",
    messages=[{"role": "user", "content": "Hello!"}]
)

Examples​

Basic Usage​

# Model API
response = completion(
    model="baseten/openai/gpt-oss-120b",
    messages=[{"role": "user", "content": "Explain quantum computing"}],
    max_tokens=500,
    temperature=0.7
)

# Dedicated deployment
response = completion(
    model="baseten/abcd1234",
    messages=[{"role": "user", "content": "Explain quantum computing"}],
    max_tokens=500,
    temperature=0.7
)

Streaming (Model API only)​

response = completion(
    model="baseten/openai/gpt-oss-120b",
    messages=[{"role": "user", "content": "Write a poem"}],
    stream=True,
    stream_options={"include_usage": True}
)

for chunk in response:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

Usage with LiteLLM Proxy​

  1. Config:
model_list:
  - model_name: baseten-model
    litellm_params:
      model: baseten/openai/gpt-oss-120b
      api_key: your-baseten-api-key
  1. Request:
import openai
client = openai.OpenAI(
    api_key="sk-1234",
    base_url="http://0.0.0.0:4000"
)

response = client.chat.completions.create(
    model="baseten-model",
    messages=[{"role": "user", "content": "Hello!"}]
)