> ## Documentation Index > Fetch the complete documentation index at: https://docs.weflayr.com/llms.txt > Use this file to discover all available pages before exploring further. # Models > List every model the gateway serves, with its providers, regions, capabilities and prices, in the OpenAI model list format. The answer is an [OpenAI model list](https://platform.openai.com/docs/api-reference/models/list), so `client.models.list()` of any OpenAI client reads it. Each model also lists every provider serving it, and each provider every region it serves the model in, with the field names of the [Vercel AI Gateway model list](https://vercel.com/docs/ai-gateway). Each level is a request field: | Level | Request field | Example | | - | - | - | | `id` | `model` | `claude-sonnet-4-5` | | `providers[].provider` | `provider` | `bedrock` | | `providers[].deployments[].region` | `region` | `eu-west-1` | The provider and the region are fields of their own: do not prefix `model` with `/`. No API key is needed. The list holds only the models the gateway has checked it can call, in the regions where it checked them. ## Query parameters **output\_modalities** `string` (default: text) Which models to list: `text` for the models that answer [Chat Completions](https://docs.weflayr.com/api/gateway/chat-completions.md) and [Responses](https://docs.weflayr.com/api/gateway/responses.md), `embeddings` for the models that answer [Embeddings](https://docs.weflayr.com/api/gateway/embeddings.md). Any other value returns a 400 `invalid_query_parameter`. ## Response **object** `string` Always `list`. **data** `object[]` The models, by `id`. **properties** **id** `string` The model name to send as `model`. **object** `string` Always `model`. **created** `integer | null` The model's release date, in Unix seconds. `null` when unknown. **owned\_by** `string | null` Who makes the model, e.g. `anthropic`, whichever provider serves it. `null` when unknown. **type** `string` `language` or `embedding`. **providers** `object[]` The providers serving the model, by name. **properties** **provider** `string` The provider name to send as `provider`. **tags** `string[]` What the provider serves the model with: `vision`, `text`, `image-gen`, `video-gen`, `speech`, `tool-use`, `reasoning`, `web-search`, `implicit-caching`, `explicit-caching`, `structured-output`, `file-input`. A capability that differs per region is listed when one of the provider's regions has it. **modalities** `object` What the model reads (`input`: `text`, `image`, `pdf`, `video`, `audio`) and answers with (`output`: `text`, `image`, `video`, `audio`). `pdf` is listed as the tags are, when one of the provider's regions reads PDFs. **context\_window** `integer | null` The longest input the model takes, in tokens. **max\_tokens** `integer | null` The most tokens the model writes in one answer. **deployments** `object[]` The regions the provider serves the model in, `GLOBAL` first, then `US`, then `EU`. **properties** **region** `string` The region name to send as `region`: `GLOBAL`, `US`, `EU`, or the provider's own region (e.g. `eu-west-1` on Bedrock). **macro\_region** `string` `GLOBAL`, `US` or `EU`: the region holding `region`. **pricing** `object | null` The standard prices, in USD per token, as decimal strings: `input`, `output`, `input_cache_read`, `input_cache_write` (the default cache lifetime) and `input_cache_write_extended_ttl` (the longer lifetime: one hour for Claude, 12 hours on OpenAI). A price is left out when the deployment does not bill that kind of token. A price that depends on the input length also has `_tiers`, one `{cost, min, max}` per range of text input tokens: `min` is the first token count billed at that price, `max` the first one billed at the next (excluded, absent for the last range). A price set only from a longer input on has `_tiers` and no top-level value: below its first range, Weflayr has no price for that kind of token. `service_tiers` holds the same prices for `flex` and `priority`, where the deployment serves them. `null` when Weflayr has no standard price for the deployment yet. ## Errors An `output_modalities` value other than `text` or `embeddings` returns a 400 `invalid_query_parameter`. A 503 `model_catalog_unavailable` means the gateway could not read its model catalog: retry later. The errors are in OpenAI's format, see [Errors](https://docs.weflayr.com/api/introduction.md#errors). ```python Python theme={null} from openai import OpenAI client = OpenAI(base_url="https://gateway.weflayr.com/v1", api_key="") for model in client.models.list(): print(model.id, [provider["provider"] for provider in model.providers]) ``` ```js Node.js theme={null} const OpenAI = require('openai'); const client = new OpenAI({ baseURL: 'https://gateway.weflayr.com/v1', apiKey: '' }); for await (const model of client.models.list()) { console.log(model.id, model.providers.map((provider) => provider.provider)); } ``` ```bash cURL theme={null} curl "https://gateway.weflayr.com/v1/models?output_modalities=text" ``` ```json 200 theme={null} { "object": "list", "data": [ { "id": "claude-sonnet-4-5", "object": "model", "created": 1759104000, "owned_by": "anthropic", "type": "language", "providers": [ { "provider": "bedrock", "tags": ["vision", "text", "tool-use", "reasoning", "explicit-caching", "file-input"], "modalities": {"input": ["text", "image", "pdf"], "output": ["text"]}, "context_window": 200000, "max_tokens": 64000, "deployments": [ { "region": "eu-west-1", "macro_region": "EU", "pricing": { "input": "0.0000033", "input_tiers": [ {"cost": "0.0000033", "min": 0, "max": 200001}, {"cost": "0.0000066", "min": 200001} ], "output": "0.0000165", "output_tiers": [ {"cost": "0.0000165", "min": 0, "max": 200001}, {"cost": "0.00002475", "min": 200001} ], "input_cache_read": "0.00000033", "input_cache_write": "0.000004125", "input_cache_write_extended_ttl": "0.0000066", "service_tiers": { "flex": {"input": "0.00000165", "output": "0.00000825"} } } } ] } ] } ] } ``` This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.