LLMs

LLM models are specified in settings via a string with format provider:model-id.

Examples

.aether/settings.json

{
  "agents": [
    {
      "model": "zai:glm-5.1",
      ...
    }
  ]
}

Form	Example	Meaning
Single model	zai:glm-5.1	Use one provider/model pair.
Alloy	zai:glm-5.1,openai:gpt-5.5	Round-robin between model specs each conversation turn.

Supported Providers

Anthropic

Credentials	ANTHROPIC_API_KEY
Model syntax	anthropic:<model-id>
Default provider model	claude-sonnet-4-5-20250929

OpenAI

Credentials	OPENAI_API_KEY
Model syntax	openai:<model-id>

Codex

Credentials	OAuth login stored in the configured credential store; OS keychain by default
Model syntax	codex:<model-id>
Common model	codex:gpt-5.5

Codex uses OpenAI’s Codex OAuth flow through the client. If no Codex credentials are available, Aether asks you to log in when the model is selected.

OpenRouter

Credentials	OPENROUTER_API_KEY
Model syntax	openrouter:<vendor>/<model-id>

Use the vendor/model format from the OpenRouter model list.

OpenAI-compatible providers

Aether has built-in OpenAI-compatible provider configs for:

Provider	Syntax	Env var
DeepSeek	deepseek:<model-id>	DEEPSEEK_API_KEY
Moonshot	moonshot:<model-id>	MOONSHOT_API_KEY
ZAI	zai:<model-id>	ZAI_API_KEY

Gemini

Credentials	GEMINI_API_KEY
Model syntax	gemini:<model-id>

AWS Bedrock

Credentials	AWS credential chain (environment, config file, IAM role, etc.)
Model syntax	bedrock:<model-id>

Use the Bedrock foundation model or system profile model ID as the Aether model identity. Aether uses this value for context windows, multimodal/reasoning capability checks, and Bedrock prompt caching decisions.

If you route traffic through an inference profile, configure the profile ARN as a provider override instead of putting the ARN in model:

.aether/settings.json

{
  "agents": [
    {
      "name": "BedrockProfile",
      "description": "Routes Bedrock requests through an application inference profile",
      "model": "bedrock:anthropic.claude-sonnet-4-5-20250929-v1:0",
      "providers": {
        "bedrock": {
          "inferenceProfileArn": "arn:aws:bedrock:us-west-2:000000000000:application-inference-profile/000000000000"
        }
      },
      "userInvocable": true
    }
  ]
}

Do not use bedrock:arn:aws:bedrock:... as the model. The ARN only identifies the request target; it does not tell Aether which model capabilities or context window to use.

Ollama

Credentials	None
Model syntax	ollama:<model-id>
Host override	OLLAMA_HOST

Aether discovers models you have pulled into Ollama.

llama.cpp

Credentials	None
Model syntax	llamacpp:<model-id>
Host override	LLAMA_CPP_HOST

Aether queries the server’s /v1/models endpoint for the currently loaded model.

Reasoning effort

Some providers support extended thinking. Set reasoningEffort on an agent to request a thinking budget:

Value	Meaning
"low"	Minimal thinking
"medium"	Moderate thinking
"high"	Extended thinking
"xhigh"	Maximum thinking budget for providers that expose a fourth level

.aether/settings.json

{
  "agents": [
    {
      "name": "Plan",
      "description": "Plans implementation strategy",
      "model": "codex:gpt-5.5",
      "reasoningEffort": "xhigh",
      "userInvocable": true,
      "prompts": [".aether/PLAN.md"]
    }
  ]
}

Providers that do not support the requested effort ignore it or map it to their closest available setting.

Alloying

An alloy spec is a comma-separated list of model specs. Each conversation turn uses the next provider in the list, cycling round-robin.

.aether/settings.json

{
  "agents": [
    {
      "name": "Alloy",
      "description": "Alternates between cloud and local models",
      "model": "zai:glm-5.1,ollama:llama3.2",
      "userInvocable": true,
      "prompts": [".aether/ALLOY.md"]
    }
  ]
}

Every model in the alloy must be usable in the current runtime environment: required credentials must be set, and local servers must be running.