# Google Adk Models

> Use non-Gemini models with ADK agents via LiteLLM or Anthropic. Use when wiring Claude, GPT-4, Llama, Mistral, or any LiteLLM-supported provider into an ADK agent.

- Skill: `eagleisbatman/google-adk-models` (Agent Skill)
- Install (CLI): `npx skillmds@latest add eagleisbatman/google-adk-models`
- Raw SKILL.md: https://api.skillmd.com/api/skills/eagleisbatman/google-adk-models/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: eagleisbatman (https://skillmd.com/u/eagleisbatman)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/eagleisbatman/google-adk-models

---


# Google ADK — Models (Non-Gemini)

## Overview

ADK's `model` field accepts either a string (Gemini models) or a `BaseLlm` instance (any other provider via LiteLLM).

| Provider | Model String Pattern | Install |
|----------|---------------------|---------|
| Gemini (native) | `"gemini-2.5-flash"` | `pip install google-adk` |
| Any via LiteLLM | `LiteLlm(model="provider/model")` | `pip install google-adk[extensions]` |

## Install LiteLLM Support

```bash
pip install google-adk[extensions]
```

## Using LiteLLM (Any Provider)

```python
from google.adk.agents import Agent
from google.adk.models.lite_llm import LiteLlm

agent = Agent(
    name="claude_agent",
    model=LiteLlm(model="anthropic/claude-sonnet-4-20250514"),
    instruction="You are a helpful assistant.",
    tools=[my_tool],
)
```

## Provider-Specific Examples

### Anthropic (Claude)

```python
import os
os.environ["ANTHROPIC_API_KEY"] = "sk-..."

agent = Agent(
    name="claude_agent",
    model=LiteLlm(model="anthropic/claude-sonnet-4-20250514"),
    instruction="...",
)
```

### OpenAI (GPT)

```python
import os
os.environ["OPENAI_API_KEY"] = "sk-..."

agent = Agent(
    name="gpt_agent",
    model=LiteLlm(model="openai/gpt-4o"),
    instruction="...",
)
```

### Azure OpenAI

```python
import os
os.environ["AZURE_API_KEY"] = "..."
os.environ["AZURE_API_BASE"] = "https://your-resource.openai.azure.com/"
os.environ["AZURE_API_VERSION"] = "2024-02-01"

agent = Agent(
    name="azure_agent",
    model=LiteLlm(model="azure/gpt-4o-deployment-name"),
    instruction="...",
)
```

### Vertex AI (Claude via Google Cloud)

```python
import os
os.environ["VERTEXAI_PROJECT"] = "your-gcp-project-id"
os.environ["VERTEXAI_LOCATION"] = "us-east5"

agent = Agent(
    name="vertex_claude",
    model=LiteLlm(model="vertex_ai/claude-3-7-sonnet@20250219"),
    instruction="...",
)
```

### Ollama (Local Models)

```python
agent = Agent(
    name="local_agent",
    model=LiteLlm(model="ollama/llama3.1"),
    instruction="...",
)
```

## Additional LiteLLM Arguments

Pass extra kwargs to customize the LiteLLM completion call:

```python
agent = Agent(
    name="custom_agent",
    model=LiteLlm(
        model="anthropic/claude-sonnet-4-20250514",
        temperature=0.7,
        max_tokens=4096,
        drop_params=True,
    ),
    instruction="...",
)
```

## Default Model for All Agents

```python
from google.adk.agents import LlmAgent
from google.adk.models.lite_llm import LiteLlm

LlmAgent.set_default_model(LiteLlm(model="openai/gpt-4o"))
```

## Multi-Model Systems

```python
from google.adk.agents import Agent
from google.adk.models.lite_llm import LiteLlm

router = Agent(
    name="router",
    model="gemini-2.5-flash",
    instruction="Route requests to the appropriate specialist.",
    sub_agents=[fast_agent, smart_agent],
)

fast_agent = Agent(
    name="fast_worker",
    model="gemini-2.5-flash",
    instruction="Handle simple tasks quickly.",
)

smart_agent = Agent(
    name="smart_worker",
    model=LiteLlm(model="anthropic/claude-sonnet-4-20250514"),
    instruction="Handle complex reasoning tasks.",
)
```

## Gemini Models (Native — No LiteLlm Needed)

| Model | Use Case |
|-------|----------|
| `"gemini-2.5-flash"` | Fast, cost-effective (default) |
| `"gemini-2.5-pro"` | Complex reasoning |
| `"gemini-2.0-flash"` | Legacy |

## Key Rules

- Gemini models use plain strings: `model="gemini-2.5-flash"`
- All other providers use `LiteLlm(model="provider/model-name")`
- Environment variables for auth must be set BEFORE creating the agent
- LiteLLM model strings follow the `"provider/model"` convention
- Don't use LiteLLM for Gemini models — ADK warns against this (use native strings)
- `drop_params=True` silently ignores unsupported params (useful for cross-provider code)

## Related Skills

- `google-adk-llm-agent` — Agent configuration (where model is set)
- `google-adk-deploy` — Deploying with non-Gemini models (env vars in secrets)