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Atlas Cloud — LLM Provider Guide

Atlas Cloud is a full-modal AI inference platform providing an OpenAI-compatible API for 59+ LLM models, image generation, and video generation.

Configuration

Set the following environment variables to use Atlas Cloud as your LLM backend:

ATLAS_API_KEY=<your-atlascloud-api-key>
ATLAS_BASE_URL=https://api.atlascloud.ai/v1

Or copy from .env.example:

cp .env.example .env
# Then fill in ATLAS_API_KEY

Install

ECC can install its managed surfaces into any OpenAI-compatible backend. To use Atlas Cloud with Claude Code (or any ECC-managed harness), set the base URL and API key:

export ATLAS_API_KEY=your-key-here
export ATLAS_BASE_URL=https://api.atlascloud.ai/v1

Available Models

All Atlas Cloud LLM models (59+)
  • Anthropic: anthropic/claude-haiku-4.5-20251001, anthropic/claude-opus-4.8, anthropic/claude-sonnet-4.6
  • OpenAI: openai/gpt-5.4, openai/gpt-5.5
  • Google Gemini: google/gemini-3.1-flash-lite, google/gemini-3.1-pro-preview, google/gemini-3.5-flash
  • Qwen: qwen/qwen2.5-7b-instruct, Qwen/Qwen3-235B-A22B-Instruct-2507, qwen/qwen3-235b-a22b-thinking-2507, qwen/qwen3-30b-a3b, Qwen/Qwen3-30B-A3B-Instruct-2507, qwen/qwen3-30b-a3b-thinking-2507, qwen/qwen3-32b, qwen/qwen3-8b, Qwen/Qwen3-Coder, qwen/qwen3-coder-next, qwen/qwen3-max-2026-01-23, Qwen/Qwen3-Next-80B-A3B-Instruct, Qwen/Qwen3-Next-80B-A3B-Thinking, Qwen/Qwen3-VL-235B-A22B-Instruct, qwen/qwen3-vl-235b-a22b-thinking, qwen/qwen3-vl-30b-a3b-instruct, qwen/qwen3-vl-30b-a3b-thinking, qwen/qwen3-vl-8b-instruct, qwen/qwen3.5-122b-a10b, qwen/qwen3.5-27b, qwen/qwen3.5-35b-a3b, qwen/qwen3.5-397b-a17b, qwen/qwen3.6-35b-a3b, qwen/qwen3.6-plus
  • DeepSeek: deepseek-ai/deepseek-ocr, deepseek-ai/deepseek-r1-0528, deepseek-ai/DeepSeek-V3-0324, deepseek-ai/DeepSeek-V3.1, deepseek-ai/DeepSeek-V3.1-Terminus, deepseek-ai/deepseek-v3.2, deepseek-ai/DeepSeek-V3.2-Exp, deepseek-ai/deepseek-v4-flash, deepseek-ai/deepseek-v4-pro
  • Kimi: moonshotai/Kimi-K2-Instruct, moonshotai/Kimi-K2-Instruct-0905, moonshotai/Kimi-K2-Thinking, moonshotai/kimi-k2.5, moonshotai/kimi-k2.6
  • GLM: zai-org/GLM-4.6, zai-org/glm-4.7, zai-org/glm-5, zai-org/glm-5-turbo, zai-org/glm-5.1, zai-org/glm-5v-turbo
  • MiniMax: MiniMaxAI/MiniMax-M2, minimaxai/minimax-m2.1, minimaxai/minimax-m2.5, minimaxai/minimax-m2.7
  • xAI: xai/grok-4.3
  • KAT: kwaipilot/kat-coder-pro-v2
  • Other: owl

Usage Example

from openai import OpenAI
import os

client = OpenAI(
    api_key=os.environ["ATLAS_API_KEY"],
    base_url=os.environ.get("ATLAS_BASE_URL", "https://api.atlascloud.ai/v1"),
)

response = client.chat.completions.create(
    model="anthropic/claude-sonnet-4.6",
    messages=[{"role": "user", "content": "Hello from ECC + Atlas Cloud!"}],
)
print(response.choices[0].message.content)

Get API Credits

Visit Atlas Cloud Coding Plan for API credits.