> ## Documentation Index
> Fetch the complete documentation index at: https://docs.skaro.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Supported Providers

> Overview of all LLM providers supported by Skaro.

Skaro supports four LLM providers out of the box. You can use one provider for everything, or mix them using [role-based routing](/providers/role-based-routing).

## Provider Comparison

| Provider      | API Key Required | Default Model             | Console URL                                                          |
| ------------- | ---------------- | ------------------------- | -------------------------------------------------------------------- |
| **Anthropic** | Yes              | `claude-sonnet-4-6`       | [console.anthropic.com](https://console.anthropic.com/settings/keys) |
| **OpenAI**    | Yes              | `gpt-5.2`                 | [platform.openai.com](https://platform.openai.com/api-keys)          |
| **Groq**      | Yes              | `llama-3.3-70b-versatile` | [console.groq.com](https://console.groq.com/keys)                    |
| **Ollama**    | No               | `qwen3:32b`               | Local — [ollama.com](https://ollama.com)                             |

## Available Models

### Anthropic

| Model                                            | Context Window | Max Output |
| ------------------------------------------------ | -------------- | ---------- |
| Claude Opus 4.6 (`claude-opus-4-6`)              | 200K           | 128K       |
| Claude Sonnet 4.6 (`claude-sonnet-4-6`)          | 200K           | 64K        |
| Claude Sonnet 4.5 (`claude-sonnet-4-5-20250929`) | 200K           | 64K        |
| Claude Haiku 4.5 (`claude-haiku-4-5-20251001`)   | 200K           | 64K        |

### OpenAI

| Model                           | Context Window | Max Output |
| ------------------------------- | -------------- | ---------- |
| GPT-5.2 (`gpt-5.2`)             | 256K           | 128K       |
| GPT-5.1 (`gpt-5.1`)             | 256K           | 128K       |
| GPT-5 (`gpt-5`)                 | 256K           | 65K        |
| GPT-5 Mini (`gpt-5-mini`)       | 256K           | 65K        |
| GPT-5.2 Codex (`gpt-5.2-codex`) | 256K           | 128K       |
| GPT-4.1 (`gpt-4.1`)             | 1M             | 32K        |
| GPT-4.1 Mini (`gpt-4.1-mini`)   | 1M             | 32K        |

### Groq

| Model                                                           | Context Window | Max Output |
| --------------------------------------------------------------- | -------------- | ---------- |
| Llama 3.3 70B (`llama-3.3-70b-versatile`)                       | 131K           | 32K        |
| Llama 3.1 8B Instant (`llama-3.1-8b-instant`)                   | 131K           | 131K       |
| GPT-OSS 120B (`openai/gpt-oss-120b`)                            | 131K           | 65K        |
| Llama 4 Scout 17B (`meta-llama/llama-4-scout-17b-16e-instruct`) | 131K           | 8K         |
| Kimi K2 (`moonshotai/kimi-k2-instruct-0905`)                    | 262K           | 16K        |
| Qwen3 32B (`qwen/qwen3-32b`)                                    | 131K           | 40K        |

### Ollama (Local)

| Model                               | Context Window | Max Output |
| ----------------------------------- | -------------- | ---------- |
| Qwen3 32B (`qwen3:32b`)             | 131K           | 40K        |
| Qwen 3.5 35B (`qwen3.5:35b`)        | 131K           | 40K        |
| Llama 3.3 70B (`llama3.3:70b`)      | 131K           | 32K        |
| DeepSeek R1 70B (`deepseek-r1:70b`) | 131K           | 65K        |
| Gemma 3 27B (`gemma3:27b`)          | 131K           | 8K         |
| Phi-4 14B (`phi4:14b`)              | 16K            | 16K        |
| CodeLlama 34B (`codellama:34b`)     | 16K            | 16K        |

<Tip>
  You can also enter any custom model ID during `skaro init` or via `skaro config --model your-model-id`. The lists above are suggestions, not hard limits.
</Tip>

## Choosing a Provider

**Best quality** — Anthropic or OpenAI. Larger models produce better architecture reviews and more consistent code. Best for the `architect` role.

**Fastest inference** — Groq. Hardware-accelerated inference makes it excellent for code generation. Good for the `coder` role.

**Full privacy** — Ollama. Code never leaves your machine. No API costs. Trade-off: requires local hardware (16GB+ RAM for 30B+ models) and may produce lower quality output than cloud providers.

**Cost-effective start** — Groq offers a generous free tier. Good for trying Skaro without spending money.

## Quick Setup

```bash theme={null}
# Pick one:
skaro config --provider anthropic --api-key sk-ant-...
skaro config --provider openai --api-key sk-...
skaro config --provider groq --api-key gsk_...
skaro config --provider ollama --model qwen3:32b
```

See [Role-Based Routing](/providers/role-based-routing) to use different providers for different phases.