List Models

List Models

curl --request GET \
  --url https://api.gravitex.ai/v1/models

import requests

url = "https://api.gravitex.ai/v1/models"

response = requests.get(url)

print(response.text)

const options = {method: 'GET'};

fetch('https://api.gravitex.ai/v1/models', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.gravitex.ai/v1/models",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "GET",
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://api.gravitex.ai/v1/models"

	req, _ := http.NewRequest("GET", url, nil)

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.get("https://api.gravitex.ai/v1/models")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.gravitex.ai/v1/models")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Get.new(url)

response = http.request(request)
puts response.read_body

GET

models

List Models

curl --request GET \
  --url https://api.gravitex.ai/v1/models

import requests

url = "https://api.gravitex.ai/v1/models"

response = requests.get(url)

print(response.text)

const options = {method: 'GET'};

fetch('https://api.gravitex.ai/v1/models', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.gravitex.ai/v1/models",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "GET",
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://api.gravitex.ai/v1/models"

	req, _ := http.NewRequest("GET", url, nil)

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.get("https://api.gravitex.ai/v1/models")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.gravitex.ai/v1/models")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Get.new(url)

response = http.request(request)
puts response.read_body

Introduction

Retrieve all models available to your API key. The same endpoint https://api.gravitex.ai/v1/models automatically returns the response in the appropriate platform’s native format based on request headers — no need to switch URLs or maintain multiple integrations.

Auto Format Detection

GravitexAI inspects the auth headers to detect the client type and returns the response using the official OpenAI / Anthropic / Gemini ListModels schema, so native SDKs work out of the box.

Format Detection Rules

Request signature	Response format
`x-api-key` + `anthropic-version` headers	Anthropic
`x-goog-api-key` header or `?key=xxx` query param	Gemini
`Authorization: Bearer ...` (default)	OpenAI

When multiple credentials are present, the priority is: Anthropic > Gemini > OpenAI.

Authentication

string

OpenAI-compatible authentication, format: Bearer sk-xxxxxxxxxx

string

Anthropic authentication — the raw API key (no Bearer prefix)

string

Anthropic API version, e.g. 2023-06-01

string

Gemini authentication — the raw API key

Request Examples

OpenAI format
Anthropic format
Gemini format

curl https://api.gravitex.ai/v1/models \
  -H "Authorization: Bearer sk-XyLy**************************mIqSt"

from openai import OpenAI

client = OpenAI(
    api_key="sk-XyLy**************************mIqSt",
    base_url="https://api.gravitex.ai/v1"
)

models = client.models.list()

for model in models.data:
    print(f"{model.id}  ({model.owned_by})")

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'sk-XyLy**************************mIqSt',
  baseURL: 'https://api.gravitex.ai/v1'
});

const models = await client.models.list();
models.data.forEach(m => console.log(`${m.id}  (${m.owned_by})`));

curl https://api.gravitex.ai/v1/models \
  -H "x-api-key: sk-XyLy**************************mIqSt" \
  -H "anthropic-version: 2023-06-01"

import anthropic

client = anthropic.Anthropic(
    api_key="sk-XyLy**************************mIqSt",
    base_url="https://api.gravitex.ai"
)

for model in client.models.list().data:
    print(f"{model.id}  ({model.display_name})")

curl "https://api.gravitex.ai/v1/models" \
  -H "x-goog-api-key: sk-XyLy**************************mIqSt"

import requests

resp = requests.get(
    "https://api.gravitex.ai/v1/models",
    headers={"x-goog-api-key": "sk-XyLy**************************mIqSt"}
)

for model in resp.json()["models"]:
    print(f"{model['name']}  ({model['displayName']})")

Response Examples

OpenAI format
Anthropic format
Gemini format

{
  "object": "list",
  "data": [
    {
      "id": "gpt-5.4",
      "object": "model",
      "created": 1715232000,
      "owned_by": "openai"
    },
    {
      "id": "claude-sonnet-4-5-20250929",
      "object": "model",
      "created": 1743465600,
      "owned_by": "anthropic"
    },
    {
      "id": "gemini-2.5-pro",
      "object": "model",
      "created": 1746057600,
      "owned_by": "google"
    }
  ]
}

{
  "data": [
    {
      "type": "model",
      "id": "claude-opus-4-5-20251101",
      "display_name": "Claude Opus 4.5",
      "created_at": "2025-11-01T00:00:00Z"
    },
    {
      "type": "model",
      "id": "claude-sonnet-4-5-20250929",
      "display_name": "Claude Sonnet 4.5",
      "created_at": "2025-09-29T00:00:00Z"
    }
  ],
  "has_more": false,
  "first_id": "claude-opus-4-5-20251101",
  "last_id": "claude-sonnet-4-5-20250929"
}

{
  "models": [
    {
      "name": "models/gemini-2.5-pro",
      "version": "001",
      "displayName": "Gemini 2.5 Pro",
      "description": "Google's flagship multimodal reasoning model",
      "inputTokenLimit": 1048576,
      "outputTokenLimit": 8192,
      "supportedGenerationMethods": ["generateContent", "countTokens"]
    },
    {
      "name": "models/gemini-3.1-pro-preview",
      "version": "preview",
      "displayName": "Gemini 3.1 Pro Preview",
      "inputTokenLimit": 1048576,
      "outputTokenLimit": 8192,
      "supportedGenerationMethods": ["generateContent", "countTokens"]
    }
  ]
}

Response Fields

OpenAI format

Field	Type	Description
`object`	string	Always `list`
`data`	array	Model list
`data[].id`	string	Model identifier; use this as the `model` parameter in requests
`data[].object`	string	Always `model`
`data[].created`	integer	Release timestamp (Unix seconds)
`data[].owned_by`	string	Provider, e.g. `openai`, `anthropic`, `google`

Anthropic format

Field	Type	Description
`data`	array	Model list
`data[].type`	string	Always `model`
`data[].id`	string	Model identifier
`data[].display_name`	string	Human-friendly name
`data[].created_at`	string	Release time (ISO 8601 string)
`has_more`	boolean	Whether more pages exist
`first_id` / `last_id`	string	Pagination cursors

Gemini format

Field	Type	Description
`models`	array	Model list
`models[].name`	string	Resource name, format `models/{id}`
`models[].displayName`	string	Human-friendly name
`models[].description`	string	Model description
`models[].inputTokenLimit`	integer	Maximum input tokens
`models[].outputTokenLimit`	integer	Maximum output tokens
`models[].supportedGenerationMethods`	array	Methods supported by this model

Error Handling

Status	Meaning	Suggested action
`200`	Success	—
`401`	API key invalid or expired	Verify the key; ensure it has not been disabled
`429`	Too many requests	Back off and retry; contact BD to raise your quota
`500`	Internal server error	Retry briefly; contact support if it persists

Error response example (OpenAI format):

{
  "error": {
    "message": "Invalid API key",
    "type": "invalid_request_error",
    "code": "invalid_api_key"
  }
}

Best Practices

Cache the result — the model list changes infrequently; caching for 1+ hour avoids unnecessary requests.
Validate at startup — call this endpoint once at boot to confirm the key works and the target model is available.
Permission-aware — the returned list varies with the API key’s entitlements; different keys may see different models.
Drop-in SDKs — when using the official OpenAI / Anthropic / Google SDKs, simply point the base URL to https://api.gravitex.ai; no extra adapters required.

Python example dependencies:

OpenAI format: pip install openai
Anthropic format: pip install anthropic
Gemini format: pip install requests

OpenAI SDK Usage Native Claude Format

API documentation

Chat & text

Safety & audio

Image Series

Video Series

Completions & Embeddings

Interface module

Introduction

Auto Format Detection

Format Detection Rules

Authentication

Request Examples

Response Examples

Response Fields

OpenAI format

Anthropic format

Gemini format

Error Handling

Best Practices

​Introduction

Auto Format Detection

​Format Detection Rules

​Authentication

​Request Examples

​Response Examples

​Response Fields

​OpenAI format

​Anthropic format

​Gemini format

​Error Handling

​Best Practices

Introduction

Format Detection Rules

Authentication

Request Examples

Response Examples

Response Fields

OpenAI format

Anthropic format

Gemini format

Error Handling

Best Practices