# Models > List available models and their metadata using GET /v1/models. Canonical: https://ai-gateway.sassmaker.com/docs/models ## Endpoint ``` GET /v1/models ``` Returns the list of models currently registered in the gateway in OpenAI-compatible format. Each model entry includes gateway-specific metadata such as provider, model type, reasoning tier, streaming support, and embedding dimensions where relevant. ## Response ```json { "object": "list", "data": [ { "id": "llama-3.3-70b-versatile", "object": "model", "created": 1714000000, "owned_by": "groq", "type": "chat", "provider": "groq", "reasoning_tier": null, "supports_streaming": true }, { "id": "gemini-2.0-flash", "object": "model", "created": 1714000000, "owned_by": "gemini", "provider": "gemini", "reasoning_tier": null, "supports_streaming": true }, { "id": "gemini-2.0-flash-thinking-exp", "object": "model", "created": 1714000000, "owned_by": "gemini", "provider": "gemini", "reasoning_tier": "high", "supports_streaming": true }, { "id": "@cf/meta/llama-3.3-70b-instruct-fp8-fast", "object": "model", "created": 1714000000, "owned_by": "workers_ai", "provider": "workers_ai", "reasoning_tier": null, "supports_streaming": true }, { "id": "voyage-3", "object": "model", "created": 1714000000, "owned_by": "voyage_ai", "type": "embedding", "provider": "voyage_ai", "reasoning_tier": null, "supports_streaming": false, "dimensions": 1024, "enabled": true } ] } ``` ## Response Fields | Field | Type | Description | |---|---|---| | `id` | string | Model identifier to use in request bodies. | | `object` | string | Always `"model"`. | | `created` | number | Unix timestamp when the model was registered. | | `owned_by` | string | The provider that owns/hosts the model. | | `type` | string | `"chat"` or `"embedding"`. | | `provider` | string | Gateway provider key. One of `groq`, `gemini`, `workers_ai`, `openrouter`, `cerebras`, `sambanova`, `nvidia`, `voyage_ai`. | | `reasoning_tier` | string \| null | Reasoning capability tier (`"low"`, `"medium"`, `"high"`), or `null` for standard models. | | `supports_streaming` | boolean | Whether the model supports SSE streaming. | | `evaluation_weight` | number | Continuous eval routing multiplier derived from `MODEL_EVALUATIONS_JSON`; `1` means no eval nudge. | | `evaluation_sample_count` | number | Number of recent eval samples behind the current weight. | | `evaluated_at` | string \| null | Timestamp for the current eval snapshot, when supplied. | | `dimensions` | number | Embedding vector dimensions. Present on `type: "embedding"` rows. | | `supports_dimensions` | boolean | Whether the embedding model can accept a requested output dimension. Present on embedding rows. | | `aliases` | string[] | Compatible model aliases, such as OpenAI embedding names mapped to gateway providers. Present on embedding rows. | | `enabled` | boolean | Whether the provider credential/binding needed for the row is currently configured. | Continuous evals are optional and never bypass hard filters. The router still excludes unhealthy, rate-limited, incompatible, or capability-mismatched models before applying eval weights. Embedding rows are included so RAG services can choose vector models from the live gateway catalog. Embedding vector spaces are not interchangeable; persist the selected model with each index. ## Model Capabilities Each model has capability metadata used for automatic routing: | Capability | Description | Auto-detected from | |---|---|---| | **Tool calling** | Function/tool use support | `tools` array in request | | **JSON mode** | Structured output (`response_format: { type: "json_object" }`) | `response_format` field | | **Vision** | Image input via `image_url` content parts | Image content in messages | | **Context window** | Maximum input tokens the model can handle | Estimated from prompt size | When your request requires a capability, the gateway automatically filters to models that support it. If no capable model is available, a `503` is returned. ### Capability Summary by Provider | Provider | Tool Calling | JSON Mode | Vision | Context Window | |---|:---:|:---:|:---:|---| | **Gemini** | All models | All models | All models | 1M tokens | | **Groq** | All models | All models | Llama 4 models | 32K–131K | | **SambaNova** | All models | All models | — | 32K–131K | | **NVIDIA NIM** | Most models | All models | — | 32K–131K | | **Cerebras** | All models | All models | — | 32K–131K | | **OpenRouter** | Select models | Most models | Select models | 32K–131K | | **Workers AI** | — | — | — | 2K–131K | ## Examples ### curl ```bash curl https://your-gateway.workers.dev/v1/models \ -H "Authorization: Bearer " ``` ### JavaScript ```js const response = await fetch('https://your-gateway.workers.dev/v1/models', { headers: { 'Authorization': 'Bearer ', }, }); const { data: models } = await response.json(); // Print all model IDs grouped by provider const byProvider = models.reduce((acc, model) => { (acc[model.provider] ??= []).push(model.id); return acc; }, {}); for (const [provider, ids] of Object.entries(byProvider)) { console.log(`\n${provider}:`); ids.forEach((id) => console.log(` - ${id}`)); } ``` ### OpenAI SDK ```js const client = new OpenAI({ baseURL: 'https://your-gateway.workers.dev/v1', apiKey: '', }); const models = await client.models.list(); // Filter to only streaming-capable chat models const chatModels = models.data.filter( (m) => m.type === 'chat' && m.supports_streaming, ); console.log('Available chat models:'); chatModels.forEach((m) => console.log(` ${m.id} (${m.provider})`)); ``` ## Filtering by Provider You can filter client-side after fetching the full list: ```js const response = await fetch('https://your-gateway.workers.dev/v1/models', { headers: { 'Authorization': 'Bearer ' }, }); const { data: models } = await response.json(); const groqModels = models.filter((m) => m.provider === 'groq'); const reasoningModels = models.filter((m) => m.reasoning_tier !== null); const embeddingModels = models.filter((m) => !m.supports_streaming); ``` ## Using a Specific Model Pass any `id` value directly as the `model` field in a chat or embeddings request: ```bash curl https://your-gateway.workers.dev/v1/chat/completions \ -H "Authorization: Bearer " \ -H "Content-Type: application/json" \ -d '{ "model": "llama-3.3-70b-versatile", "messages": [{ "role": "user", "content": "Hello from Groq!" }] }' ``` Or use `"auto"` to let the gateway pick the healthiest available provider automatically.