Strengths
- 1.05M-token context and 128K output on every tier
- Function calling and structured outputs
- Reasoning effort up to max
- Text and image input
Best For
- Astra: demanding reasoning and research
- Sol: complex coding and professional work
- Luna: focused, high-volume tasks
Run It in EDDI
The fastest route is the Manager: open the agent wizard or the Platform Operator and pick the provider and model. To configure it yourself, follow these steps for the provider you want.
OpenAI · type: "openai"
Model ids: gpt-6.1-sol, gpt-6-astra, gpt-6-luna
1. Store the credential
Add the provider's API key to the Secrets Vault in the Manager, or with PUT /secretstore/secrets/default/openai-key, under the name used below. Configurations reference it as ${vault:…}, so the key never appears in plain text.
${vault:openai-key}2. Configure the LLM task
Use this as the langchain.json of the agent's workflow, or paste the parameters into the LLM editor in the Manager.
{
"tasks": [
{
"actions": [
"send_message"
],
"id": "chat",
"type": "openai",
"parameters": {
"apiKey": "${vault:openai-key}",
"modelName": "gpt-6.1-sol",
"systemMessage": "You are a helpful assistant",
"addToOutput": "true"
}
}
]
}Or create the whole agent in one call
setup_agent writes the rules, LLM configuration and workflow, then deploys the agent. Call it over MCP or POST /administration/agents/setup.
setup_agent(
agentName: "My gpt-6.1-sol agent",
systemPrompt: "You are a helpful assistant.",
provider: "openai",
model: "gpt-6.1-sol",
apiKey: "${vault:openai-key}"
)Azure OpenAI · type: "azure-openai"
Model ids: gpt-6-sol
1. Store the credential
Add the provider's API key to the Secrets Vault in the Manager, or with PUT /secretstore/secrets/default/azure-openai-key, under the name used below. Configurations reference it as ${vault:…}, so the key never appears in plain text.
${vault:azure-openai-key}2. Configure the LLM task
Use this as the langchain.json of the agent's workflow, or paste the parameters into the LLM editor in the Manager.
{
"tasks": [
{
"actions": [
"send_message"
],
"id": "chat",
"type": "azure-openai",
"parameters": {
"apiKey": "${vault:azure-openai-key}",
"deploymentName": "gpt-6-sol",
"endpoint": "https://your-resource.openai.azure.com",
"systemMessage": "You are a helpful assistant",
"addToOutput": "true"
}
}
]
}Notes for EDDI
- OpenAI documents the Responses API for tool calling on Astra and 6.1 Sol, while EDDI's
openaitype uses Chat Completions. Test tool-using agents on these models before production. - On Azure OpenAI,
deploymentNameis the name you gave the deployment in your Azure resource, not the model name. - A strong final tier for a model cascade, reached only by the requests a cheaper model is unsure about.
Related Models
Sources
The facts on this page come from the vendor's documentation, checked on 2026-09-30. Models change quickly, so confirm limits with the vendor before you rely on them. Prices are not listed here: see the vendor's pricing page.