Models

Models define the language models that power agent conversations. Evonic supports multiple model providers and local inference engines.

Supported Runners

Runner	Best For	Hardware Requirements
Ollama	Quick setup, multi-model support	Moderate (CPU/GPU)
llama.cpp	Maximum portability, edge devices	Low to Moderate
vLLM	High-throughput production workloads	High (GPU recommended)

Model Configuration

Models are managed via:

• CLI: evonic model list, evonic model add, evonic model rm
• API: REST endpoints for programmatic management
• Web UI: Manage models from the Models page (/system/models)

Each model has a provider (e.g., openai, anthropic, llama.cpp), a base URL, API key, and configuration options like max tokens, timeout, and temperature.

API Format Translation

Introduced in v0.7.0.

The LLM client now supports translating between OpenAI and Anthropic API formats, configurable per-model via an API Format dropdown in the model modal.

Format	Description
OpenAI	Standard chat completions format (default for most providers)
Anthropic	Anthropic’s native Messages API format

How It Works

When you set a model’s API format to Anthropic, the LLM client:

1. Takes the internal OpenAI-format request (messages, tools, system prompt)
2. Translates it to Anthropic’s Messages API format
3. Sends the translated request to the model’s base URL
4. Translates the Anthropic-format response back to the internal format

This means you can connect Claude and other Anthropic-compatible models natively without a proxy. Just set the base URL to an Anthropic-compatible endpoint and switch the API format to Anthropic.

Configuration

1. Go to System → Models (/system/models)
2. Create a new model or edit an existing one
3. Find the API Format dropdown in the model form
4. Select Anthropic for Anthropic-compatible models
5. Configure the provider, base URL, and API key as usual

The format is set per-model, so you can mix OpenAI-format and Anthropic-format models in the same deployment.

Duplicating a Model

Introduced in v0.2.6.

Instead of creating a new model from scratch, you can duplicate an existing model and tweak its settings. This is useful when you want to:

• Create a variant of a model with different parameters (e.g., higher temperature)
• Set up the same model with a different API key or base URL
• Copy a model from one provider setup to another

Via Web UI

1. Go to System → Models (/system/models)
2. Find the model you want to duplicate
3. Click the Duplicate button (copy icon)
4. A new model form opens pre-filled with the original’s settings
5. Adjust the settings as needed (name, provider, parameters, etc.)
6. Click Save

Via CLI

evonic model clone <source_model_id> --id <new_model_id> [--name "New Name"]

Example:

evonic model clone gpt-4 --id gpt-4-hightemp --name "GPT-4 High Temp" --temperature 0.9

This clones the gpt-4 model configuration and creates a new model called gpt-4-hightemp with a higher temperature setting.

Cloning vs Creating

Aspect	Clone	Create from scratch
Time	Instant — all fields pre-filled	Manual entry of every field
Error-prone	Low — settings are copied	High — easy to mistype config
Use case	Tweaking parameters	Adding completely new providers

New Model Providers

Introduced in v0.2.0.

Evonic supports the following additional model providers beyond the standard OpenAI-compatible endpoints:

Provider	Description	Configuration
OpenCode Zen	Optimized for code generation and analysis	Set provider to opencode-zen in model config
OpenCode Go	Lightweight code-focused model for edge devices	Set provider to opencode-go in model config
Ollama Cloud	Cloud-hosted Ollama models for remote inference	Set provider to ollama-cloud with your API key

These providers follow the same configuration structure as other models but may have provider-specific parameters available in the Advanced Settings section.

Learn More

• Local Models Overview: why local-first and model selection
• Ollama: setup and configuration
• llama.cpp: setup and configuration
• vLLM: setup and configuration
• Model Selection
• Quantization