SCX.ai

Overview

Property	Details
Description	SCX.ai is an Australian sovereign AI platform serving open models over an OpenAI-compatible API, hosted on renewable-powered infrastructure.
Provider Route on LiteLLM	scx-ai/
Link to Provider Doc	SCX.ai Documentation ↗
Base URL	https://api.scx.ai/v1
Supported Operations	/chat/completions

We support ALL SCX.ai chat models, just set scx-ai/ as a prefix when sending completion requests

Available Models

Model	Description	Context Window	Max Output
scx-ai/GLM-5.2	Z.ai GLM-5.2, a 753B sparse MoE for long-horizon agentic coding	1,048,576 tokens	131,072 tokens
scx-ai/Qwen3.8-Max	Alibaba Qwen3.8 Max, a 2.4T sparse MoE taking text and image input	1,000,000 tokens	131,072 tokens

Both models support reasoning, function calling, JSON mode and JSON schema output. scx-ai/Qwen3.8-Max additionally accepts image input. Prompt caching is applied automatically on both, and cache hits are reported in usage.prompt_tokens_details.cached_tokens and billed at the cached input rate.

Required Variables

Environment Variables

os.environ["SCX_API_KEY"] = ""  # your SCX.ai API key

Usage - LiteLLM Python SDK

Non-streaming

SCX.ai Non-streaming Completion

import os
import litellm
from litellm import completion

os.environ["SCX_API_KEY"] = ""  # your SCX.ai API key

messages = [{"content": "Hello, how are you?", "role": "user"}]

# SCX.ai call
response = completion(
    model="scx-ai/GLM-5.2",
    messages=messages
)

print(response)

Streaming

SCX.ai Streaming Completion

import os
import litellm
from litellm import completion

os.environ["SCX_API_KEY"] = ""  # your SCX.ai API key

messages = [{"content": "Write a short story about AI", "role": "user"}]

# SCX.ai call with streaming
response = completion(
    model="scx-ai/GLM-5.2",
    messages=messages,
    stream=True
)

for chunk in response:
    print(chunk)

Function Calling

SCX.ai Function Calling

import os
import litellm
from litellm import completion

os.environ["SCX_API_KEY"] = ""  # your SCX.ai API key

tools = [{
    "type": "function",
    "function": {
        "name": "get_weather",
        "description": "Get the current weather in a location",
        "parameters": {
            "type": "object",
            "properties": {
                "city": {
                    "type": "string",
                    "description": "The city, e.g. Sydney"
                }
            },
            "required": ["city"]
        }
    }
}]

messages = [{"role": "user", "content": "What's the weather in Sydney?"}]

response = completion(
    model="scx-ai/GLM-5.2",
    messages=messages,
    tools=tools,
    tool_choice="auto"
)

print(response)

Structured Output

SCX.ai JSON Schema Output

import os
from litellm import completion

os.environ["SCX_API_KEY"] = ""  # your SCX.ai API key

response = completion(
    model="scx-ai/GLM-5.2",
    messages=[{"role": "user", "content": "The city is Sydney"}],
    response_format={
        "type": "json_schema",
        "json_schema": {
            "name": "city",
            "schema": {
                "type": "object",
                "properties": {"city": {"type": "string"}},
                "required": ["city"],
                "additionalProperties": False,
            },
        },
    },
)

print(response)

Vision

Image input is supported on scx-ai/Qwen3.8-Max. Images must be at least 10 pixels on each side.

SCX.ai Image Input

import os
from litellm import completion

os.environ["SCX_API_KEY"] = ""  # your SCX.ai API key

response = completion(
    model="scx-ai/Qwen3.8-Max",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "What colour fills this image?"},
            {"type": "image_url", "image_url": {"url": "https://example.com/image.png"}},
        ],
    }],
)

print(response)

Usage - LiteLLM Proxy Server

config.yaml

model_list:
  - model_name: glm-5.2
    litellm_params:
      model: scx-ai/GLM-5.2
      api_key: os.environ/SCX_API_KEY
  - model_name: qwen3.8-max
    litellm_params:
      model: scx-ai/Qwen3.8-Max
      api_key: os.environ/SCX_API_KEY

Custom API Base

Option 1: Environment variable

Custom API Base via env var

import os
from litellm import completion

os.environ["SCX_API_BASE"] = "https://custom.scx.ai/v1"
os.environ["SCX_API_KEY"] = ""  # your API key

response = completion(
    model="scx-ai/GLM-5.2",
    messages=[{"content": "Hello!", "role": "user"}],
)

Option 2: Pass directly

Custom API Base via parameter

from litellm import completion

response = completion(
    model="scx-ai/GLM-5.2",
    messages=[{"content": "Hello!", "role": "user"}],
    api_base="https://custom.scx.ai/v1",
    api_key="your-api-key",
)

Supported OpenAI Parameters

• temperature
• max_tokens
• max_completion_tokens
• top_p
• frequency_penalty
• presence_penalty
• stop
• n
• stream
• stream_options
• tools
• tool_choice
• response_format
• seed
• logit_bias
• logprobs
• top_logprobs

max_completion_tokens is sent upstream as max_tokens. SCX.ai accepts temperature in the range [0.0, 2.0) and rejects 2.0 itself, so LiteLLM clamps anything higher to 1.99.