Modelle
Modelle auflisten
Returns a list of available models supported by the Venice.ai API across text, image, audio, video, and related inference types.
GET
/
models
/api/v1/models
curl --request GET \
--url https://api.venice.ai/api/v1/models \
--header 'Authorization: Bearer <token>'import requests
url = "https://api.venice.ai/api/v1/models"
headers = {"Authorization": "Bearer <token>"}
response = requests.get(url, headers=headers)
print(response.text)const options = {method: 'GET', headers: {Authorization: 'Bearer <token>'}};
fetch('https://api.venice.ai/api/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.venice.ai/api/v1/models",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "GET",
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>"
],
]);
$response = curl_exec($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.venice.ai/api/v1/models"
req, _ := http.NewRequest("GET", url, nil)
req.Header.Add("Authorization", "Bearer <token>")
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.venice.ai/api/v1/models")
.header("Authorization", "Bearer <token>")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.venice.ai/api/v1/models")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Get.new(url)
request["Authorization"] = 'Bearer <token>'
response = http.request(request)
puts response.read_body{
"data": [
{
"created": 1727966436,
"id": "llama-3.2-3b",
"model_spec": {
"availableContextTokens": 131072,
"capabilities": {
"optimizedForCode": false,
"quantization": "fp16",
"supportsAudioInput": false,
"supportsFunctionCalling": true,
"supportsLogProbs": true,
"supportsMultipleImages": false,
"supportsReasoning": false,
"supportsReasoningEffort": false,
"supportsResponseSchema": true,
"supportsTeeAttestation": false,
"supportsE2EE": false,
"supportsVision": false,
"supportsVideoInput": false,
"supportsWebSearch": true,
"supportsXSearch": false
},
"constraints": {
"temperature": {
"default": 0.8
},
"top_p": {
"default": 0.9
}
},
"description": "Compact and efficient model for quick responses and lighter workloads.",
"name": "Llama 3.2 3B",
"modelSource": "https://huggingface.co/meta-llama/Llama-3.2-3B",
"offline": false,
"privacy": "private",
"pricing": {
"input": {
"usd": 0.15,
"diem": 0.15
},
"output": {
"usd": 0.6,
"diem": 0.6
}
},
"traits": [
"fastest"
]
},
"object": "model",
"owned_by": "venice.ai",
"type": "text"
}
],
"object": "list",
"type": "text"
}{
"error": "<string>"
}Preise nach Qualitätsstufe
Für Bildmodelle, die den optionalen Parameterquality akzeptieren (derzeit gpt-image-2 und gpt-image-2-edit), enthält die Antwort eine Preismatrix pro Qualitätsstufe unter model_spec.pricing.quality. Jeder Top-Level-Schlüssel ist eine Auflösungsstufe (1K, 2K, 4K), und jeder verschachtelte Schlüssel ist eine Qualitätsstufe (low, medium, high) mit ihrem eigenen Preis in usd und diem:
"pricing": {
"resolutions": {
"1K": { "usd": 0.27, "diem": 0.27 },
"2K": { "usd": 0.51, "diem": 0.51 },
"4K": { "usd": 0.84, "diem": 0.84 }
},
"quality": {
"1K": {
"low": { "usd": 0.02, "diem": 0.02 },
"medium": { "usd": 0.07, "diem": 0.07 },
"high": { "usd": 0.26, "diem": 0.26 }
},
"2K": {
"low": { "usd": 0.03, "diem": 0.03 },
"medium": { "usd": 0.13, "diem": 0.13 },
"high": { "usd": 0.50, "diem": 0.50 }
},
"4K": {
"low": { "usd": 0.05, "diem": 0.05 },
"medium": { "usd": 0.21, "diem": 0.21 },
"high": { "usd": 0.83, "diem": 0.83 }
}
}
}
pricing.resolutions ist der ältere Preisplan pro Bild, der aus Gründen der Abwärtskompatibilität beibehalten wird. pricing.quality ist die Matrix pro (Auflösung, Qualität), die immer dann angewendet wird, wenn der Parameter quality unterstützt wird. Beide Felder sind in der Antwort enthalten, damit Clients die Qualitätsunterstützung erkennen und die Matrix in ihren eigenen UIs anzeigen können.
Postman-Collection
Weitere Beispiele finden Sie in dieser Postman-Collection.Autorisierungen
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Abfrageparameter
Filter models by type. Use "all" to get all model types.
Verfügbare Optionen:
asr, decision, embedding, image, music, text, tts, upscale, inpaint, video Beispiel:
"text"
Antwort
OK
List of available models
Show child attributes
Show child attributes
Verfügbare Optionen:
list Type of models returned.
Verfügbare Optionen:
asr, decision, embedding, image, music, text, tts, upscale, inpaint, video Beispiel:
"text"
War diese Seite hilfreich?
⌘I
/api/v1/models
curl --request GET \
--url https://api.venice.ai/api/v1/models \
--header 'Authorization: Bearer <token>'import requests
url = "https://api.venice.ai/api/v1/models"
headers = {"Authorization": "Bearer <token>"}
response = requests.get(url, headers=headers)
print(response.text)const options = {method: 'GET', headers: {Authorization: 'Bearer <token>'}};
fetch('https://api.venice.ai/api/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.venice.ai/api/v1/models",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "GET",
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>"
],
]);
$response = curl_exec($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.venice.ai/api/v1/models"
req, _ := http.NewRequest("GET", url, nil)
req.Header.Add("Authorization", "Bearer <token>")
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.venice.ai/api/v1/models")
.header("Authorization", "Bearer <token>")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.venice.ai/api/v1/models")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Get.new(url)
request["Authorization"] = 'Bearer <token>'
response = http.request(request)
puts response.read_body{
"data": [
{
"created": 1727966436,
"id": "llama-3.2-3b",
"model_spec": {
"availableContextTokens": 131072,
"capabilities": {
"optimizedForCode": false,
"quantization": "fp16",
"supportsAudioInput": false,
"supportsFunctionCalling": true,
"supportsLogProbs": true,
"supportsMultipleImages": false,
"supportsReasoning": false,
"supportsReasoningEffort": false,
"supportsResponseSchema": true,
"supportsTeeAttestation": false,
"supportsE2EE": false,
"supportsVision": false,
"supportsVideoInput": false,
"supportsWebSearch": true,
"supportsXSearch": false
},
"constraints": {
"temperature": {
"default": 0.8
},
"top_p": {
"default": 0.9
}
},
"description": "Compact and efficient model for quick responses and lighter workloads.",
"name": "Llama 3.2 3B",
"modelSource": "https://huggingface.co/meta-llama/Llama-3.2-3B",
"offline": false,
"privacy": "private",
"pricing": {
"input": {
"usd": 0.15,
"diem": 0.15
},
"output": {
"usd": 0.6,
"diem": 0.6
}
},
"traits": [
"fastest"
]
},
"object": "model",
"owned_by": "venice.ai",
"type": "text"
}
],
"object": "list",
"type": "text"
}{
"error": "<string>"
}