Documentation Index
Fetch the complete documentation index at: https://docs.gourmand.dev/llms.txt
Use this file to discover all available pages before exploring further.
Popular Model Providers
These are the most commonly used model providers that offer a wide range of capabilities:
| Provider | Description | Capabilities |
|---|
| Anthropic | Providers of Claude models, known for long context windows and strong reasoning | Chat, Edit, Apply, Embeddings |
| OpenAI | Creators of GPT models with strong coding capabilities | Chat, Edit, Apply, Embeddings |
| Azure | Microsoft’s cloud platform offering OpenAI models | Chat, Edit, Apply, Embeddings |
| Amazon Bedrock | AWS service offering access to various foundation models | Chat, Edit, Apply, Embeddings |
| Ollama | Run open-source models locally with a simple interface | Chat, Edit, Apply, Embeddings, Autocomplete |
| Google Gemini | Google’s multimodal AI models | Chat, Edit, Apply, Embeddings |
| DeepSeek | Specialized code models with strong performance | Chat, Edit, Apply |
| Mistral | High-performance open models with commercial offerings | Chat, Edit, Apply, Embeddings |
| xAI | Grok models from xAI | Chat, Edit, Apply |
| Vertex AI | Google Cloud’s machine learning platform | Chat, Edit, Apply, Embeddings |
| Inception | On-premises open-source model runners | Chat, Edit, Apply |
Additional Model Providers
Beyond the top-level providers, Gobi supports many other options:
Hosted Services
| Provider | Description |
|---|
| Groq | Ultra-fast inference for various open models |
| Together AI | Platform for running a variety of open models |
| DeepInfra | Hosting for various open source models |
| OpenRouter | Gateway to multiple model providers |
| Tetrate Agent Router Service | Gateway with intelligent routing across multiple model providers |
| Cohere | Models specialized for semantic search and text generation |
| NVIDIA | GPU-accelerated model hosting |
| Cloudflare | Edge-based AI inference services |
| HuggingFace | Platform for open source models |
Local Model Options
| Provider | Description |
|---|
| LM Studio | Desktop app for running models locally |
| llama.cpp | Optimized C++ implementation for running LLMs |
| LlamaStack | Stack for running Llama models locally |
| llamafile | Self-contained executable model files |
Enterprise Solutions
| Provider | Description |
|---|
| SambaNova | Enterprise AI platform |
| Watson x | IBM’s enterprise AI platform |
| Sagemaker | AWS machine learning platform |
| Nebius | Cloud-based machine learning platform |
How to Choose a Model Provider
When selecting a model provider, consider:
- Hosting preference: Do you need local models for offline use or privacy, or are you comfortable with cloud services?
- Performance requirements: Different providers offer varying levels of speed, quality, and context length.
- Specific capabilities: Some models excel at code generation, others at embeddings or reasoning tasks.
- Pricing: Costs vary significantly between providers, from free local options to premium cloud services.
- API key requirements: Most cloud providers require API keys that you’ll need to configure.
You can add models to your config.yaml file like this:
models:
- name: Claude 4 Sonnet
provider: anthropic # Choose provider from the lists above
model: claude-sonnet-4-20250514 # Specific model name
apiKey: ${{ secrets.OPENAI_API_KEY }}
roles:
- chat
- edit
- apply
