Comparaison de modèles d'IA avec l'API Nvidia : Qwen, DeepSeek, Seed-OSS et Nemotron
Intermédiaire
Ceci est uncontenant 11 nœuds.Utilise principalement des nœuds comme Set, Merge, Switch, Webhook, HttpRequest. Comparer les modèles d'IA avec l'API Nvidia : Qwen, DeepSeek, Seed-OSS et Nemotron
Prérequis
- •Point de terminaison HTTP Webhook (généré automatiquement par n8n)
- •Peut nécessiter les informations d'identification d'authentification de l'API cible
Nœuds utilisés (11)
Catégorie
-
Aperçu du workflow
Visualisation des connexions entre les nœuds, avec support du zoom et du déplacement
Exporter le workflow
Copiez la configuration JSON suivante dans n8n pour importer et utiliser ce workflow
{
"id": "vwBMikFazJ8dTN7C",
"meta": {
"instanceId": "b91e510ebae4127f953fd2f5f8d40d58ca1e71c746d4500c12ae86aad04c1502",
"templateCredsSetupCompleted": true
},
"name": "Compare AI Models with Nvidia API: Qwen, DeepSeek, Seed-OSS & Nemotron",
"tags": [],
"nodes": [
{
"id": "2fd77eab-0817-4d39-a206-4506b5373765",
"name": "Webhook Trigger",
"type": "n8n-nodes-base.webhook",
"position": [
-144,
-528
],
"webhookId": "6737b4b1-3c2f-47b9-89ff-a012c1fa4f29",
"parameters": {
"path": "6737b4b1-3c2f-47b9-89ff-a012c1fa4f29",
"options": {},
"httpMethod": "POST",
"responseMode": "responseNode"
},
"typeVersion": 2.1
},
{
"id": "1f78059c-f7a8-493c-886e-05047d83a7b4",
"name": "Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1072,
-848
],
"parameters": {
"width": 864,
"height": 944,
"content": "# Compare AI Models with Nvidia API: Qwen, DeepSeek, Seed-OSS & Nemotron\n\n## Overview\n- Queries four AI models simultaneously via Nvidia's API in 2-3 seconds—4x faster than sequential processing. Perfect for ensemble intelligence, model comparison, or redundancy.\n\n\n## How It Works\n- Webhook Trigger receives queries\n- AI Router distributes to four parallel branches: Qwen2, SyncGenInstruct, DeepSeek-v3.1, and Nvidia Nemotron\n- Merge Node aggregates responses (continues with partial results on timeout)\n- Format Response structures output\n- Webhook Response returns JSON with all model outputs\n\n## Prerequisites\n\n- Nvidia API key from [build.nvidia.com](https://build.nvidia.com) (free tier available)\n- n8n v1.0.0+ with HTTP access\n- Model access in Nvidia dashboard\n\n## Setup\n\n1. Import workflow JSON\n2. Configure HTTP nodes: Authentication → Header Auth → `Authorization: Bearer YOUR_TOKEN_HERE`\n3. Activate workflow and test\n\n## Customization\n\nAdjust temperature/max_tokens in HTTP nodes, add/remove models by duplicating nodes, change primary response selection in Format node, or add Redis caching for frequent queries.\n\n## Use Cases\n\nMulti-model chatbots, A/B testing, code review, research assistance, and production systems with AI fallback.\n"
},
"typeVersion": 1
},
{
"id": "e7f74b77-470b-49e4-a191-577afda45296",
"name": "Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-192,
-848
],
"parameters": {
"color": 3,
"width": 1312,
"height": 784,
"content": ""
},
"typeVersion": 1
},
{
"id": "8a0ca7d2-f4c0-4a95-9a7a-63c9d40ef77e",
"name": "Formater la réponse",
"type": "n8n-nodes-base.set",
"position": [
720,
-544
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "bbfd9a05-0e6c-44cf-80e2-2a79ecb3f67a",
"name": "choices[0].message.content",
"type": "string",
"value": "={{ $json.choices[0].message.content }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "20e9c15e-cd3d-4624-8620-5e100081bab1",
"name": "Envoyer les réponses agrégées des modèles d'IA",
"type": "n8n-nodes-base.respondToWebhook",
"position": [
944,
-544
],
"parameters": {
"options": {}
},
"typeVersion": 1.4
},
{
"id": "0b86c542-74ce-4456-b025-07025e6f57a7",
"name": "Fusionner les modèles d'IA",
"type": "n8n-nodes-base.merge",
"position": [
528,
-576
],
"parameters": {
"numberInputs": 4
},
"typeVersion": 3.2
},
{
"id": "556f837e-5958-4121-9142-f3a05b560190",
"name": "Routeur de modèles d'IA",
"type": "n8n-nodes-base.switch",
"position": [
80,
-576
],
"parameters": {
"rules": {
"values": [
{
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "8c79834b-efde-4096-8a97-687dbaac1eaa",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json['AI Model'] }}",
"rightValue": "1"
}
]
}
},
{
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "6f423cc4-08e3-41aa-8c5a-40a2d37a248d",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json['AI Model'] }}",
"rightValue": "2"
}
]
}
},
{
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "b8ba2c94-78d3-4325-8dda-e139d2dad24d",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json['AI Model'] }}",
"rightValue": "3"
}
]
}
},
{
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "0d1a15d3-047f-4489-896e-af2c079de4ae",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json['AI Model'] }}",
"rightValue": "4"
}
]
}
},
{
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "634191cd-73c9-4335-987b-93e07ba7ab0f",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json['AI Model'] }}",
"rightValue": "5"
}
]
}
}
]
},
"options": {}
},
"typeVersion": 3.2
},
{
"id": "38a42944-835b-422c-b872-b20c8f899210",
"name": "Interroger Qwen3-next-80b-a3b-thinking (Alibaba)",
"type": "n8n-nodes-base.httpRequest",
"position": [
304,
-832
],
"parameters": {
"url": "https://integrate.api.nvidia.com/v1/chat/completions",
"method": "POST",
"options": {},
"jsonBody": "={\n \"model\": \"qwen/qwen3-next-80b-a3b-thinking\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"{{ $('On form submission').item.json['Insert your Query'] }}\"\n }\n ],\n \"temperature\": 0.7,\n \"max_tokens\": 1024\n} ",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"headerParameters": {
"parameters": [
{
"name": "accept",
"value": "application/json"
}
]
}
},
"credentials": {
"httpBearerAuth": {
"id": "AM38cMMgmt5pCa3J",
"name": "Bearer YOUR_TOKEN_HERE"
}
},
"typeVersion": 4.2
},
{
"id": "0d948f27-f325-4776-88f5-17993c22f382",
"name": "Interroger Bytedance/seed-oss-36b-instruct (Bytedance)",
"type": "n8n-nodes-base.httpRequest",
"position": [
304,
-640
],
"parameters": {
"url": "https://integrate.api.nvidia.com/v1/chat/completions",
"method": "POST",
"options": {},
"jsonBody": "={\n \"model\": \"bytedance/seed-oss-36b-instruct\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"{{ $json['Insert your Query'] }}\"\n }\n ],\n \"temperature\": 1.1,\n \"top_p\": 0.95,\n \"max_tokens\": 4096,\n \"thinking_budget\": -1,\n \"frequency_penalty\": 0,\n \"presence_penalty\": 0,\n \"stream\": false\n}",
"sendBody": true,
"specifyBody": "json",
"authentication": "genericCredentialType"
},
"credentials": {
"httpBearerAuth": {
"id": "81rXxn13x9fyoYSK",
"name": "Bearer YOUR_TOKEN_HERE Nvidia_bytedance/seed-oss-36b-instruct"
}
},
"typeVersion": 4.2
},
{
"id": "8fb1c1df-6544-4275-af67-c7f85b9fed92",
"name": "Interroger Nvidia-nemotron-nano-9b-v2 (Nvidia)",
"type": "n8n-nodes-base.httpRequest",
"position": [
304,
-256
],
"parameters": {
"url": "https://integrate.api.nvidia.com/v1/chat/completions",
"method": "POST",
"options": {},
"jsonBody": "{\n \"model\": \"nvidia/nvidia-nemotron-nano-9b-v2\",\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"/think\"\n }\n ],\n \"temperature\": 0.6,\n \"top_p\": 0.95,\n \"max_tokens\": 2048,\n \"min_thinking_tokens\": 1024,\n \"max_thinking_tokens\": 2048,\n \"frequency_penalty\": 0,\n \"presence_penalty\": 0,\n \"stream\": true\n}",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"headerParameters": {
"parameters": [
{}
]
}
},
"credentials": {
"httpBearerAuth": {
"id": "De0YbIT8HKmoZ2QW",
"name": "Bearer YOUR_TOKEN_HERE"
}
},
"typeVersion": 4.2
},
{
"id": "d0e9668b-1c75-4e41-90ec-684abeae0d49",
"name": "Interroger DeepSeekv3_1",
"type": "n8n-nodes-base.httpRequest",
"position": [
304,
-432
],
"parameters": {
"url": "https://integrate.api.nvidia.com/v1/chat/completions",
"method": "POST",
"options": {},
"jsonBody": "={\n \"model\": \"deepseek-ai/deepseek-r1\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"{{ $('On form submission').item.json['Insert your Query'] }}\"\n }\n ],\n \"temperature\": 0.6,\n \"top_p\": 0.7,\n \"frequency_penalty\": 0,\n \"presence_penalty\": 0,\n \"max_tokens\": 4096,\n \"stream\": true\n} ",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"headerParameters": {
"parameters": [
{
"name": "Accept",
"value": "application/json"
}
]
}
},
"credentials": {
"httpBearerAuth": {
"id": "C39RW210A9LPDPUu",
"name": "Bearer YOUR_TOKEN_HERE Nvidia_Deepseekv31"
}
},
"typeVersion": 4.2
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "34faee65-7df2-4012-93bf-50660415c2d2",
"connections": {
"0b86c542-74ce-4456-b025-07025e6f57a7": {
"main": [
[
{
"node": "8a0ca7d2-f4c0-4a95-9a7a-63c9d40ef77e",
"type": "main",
"index": 0
}
]
]
},
"556f837e-5958-4121-9142-f3a05b560190": {
"main": [
[
{
"node": "38a42944-835b-422c-b872-b20c8f899210",
"type": "main",
"index": 0
}
],
[
{
"node": "0d948f27-f325-4776-88f5-17993c22f382",
"type": "main",
"index": 0
}
],
[
{
"node": "d0e9668b-1c75-4e41-90ec-684abeae0d49",
"type": "main",
"index": 0
}
],
[
{
"node": "8fb1c1df-6544-4275-af67-c7f85b9fed92",
"type": "main",
"index": 0
}
],
[
{
"node": "38a42944-835b-422c-b872-b20c8f899210",
"type": "main",
"index": 0
},
{
"node": "0d948f27-f325-4776-88f5-17993c22f382",
"type": "main",
"index": 0
},
{
"node": "8fb1c1df-6544-4275-af67-c7f85b9fed92",
"type": "main",
"index": 0
}
]
]
},
"8a0ca7d2-f4c0-4a95-9a7a-63c9d40ef77e": {
"main": [
[
{
"node": "20e9c15e-cd3d-4624-8620-5e100081bab1",
"type": "main",
"index": 0
}
]
]
},
"2fd77eab-0817-4d39-a206-4506b5373765": {
"main": [
[
{
"node": "556f837e-5958-4121-9142-f3a05b560190",
"type": "main",
"index": 0
}
]
]
},
"d0e9668b-1c75-4e41-90ec-684abeae0d49": {
"main": [
[
{
"node": "0b86c542-74ce-4456-b025-07025e6f57a7",
"type": "main",
"index": 2
}
]
]
},
"8fb1c1df-6544-4275-af67-c7f85b9fed92": {
"main": [
[
{
"node": "0b86c542-74ce-4456-b025-07025e6f57a7",
"type": "main",
"index": 3
}
]
]
},
"38a42944-835b-422c-b872-b20c8f899210": {
"main": [
[
{
"node": "0b86c542-74ce-4456-b025-07025e6f57a7",
"type": "main",
"index": 0
}
]
]
},
"0d948f27-f325-4776-88f5-17993c22f382": {
"main": [
[
{
"node": "0b86c542-74ce-4456-b025-07025e6f57a7",
"type": "main",
"index": 1
}
]
]
}
}
}Foire aux questions
Comment utiliser ce workflow ?
Copiez le code de configuration JSON ci-dessus, créez un nouveau workflow dans votre instance n8n et sélectionnez "Importer depuis le JSON", collez la configuration et modifiez les paramètres d'authentification selon vos besoins.
Dans quelles scénarios ce workflow est-il adapté ?
Intermédiaire
Est-ce payant ?
Ce workflow est entièrement gratuit et peut être utilisé directement. Veuillez noter que les services tiers utilisés dans le workflow (comme l'API OpenAI) peuvent nécessiter un paiement de votre part.
Workflows recommandés
Qwen3-VL-8B-Thinking旅行规划器
基于Skyscanner、Booking.cometGmaildeAI优化旅行行程générateur
Set
Code
Gmail
+
Set
Code
Gmail
18 NœudsCheng Siong Chin
Productivité personnelle
Système d'évaluation par les pairs piloté par l'IA avec génération automatique de critères d'évaluation
Utiliser GPT-4-nano, Slack et les notifications par e-mail pour automatiser l'attribution des relecture par les pairs
Set
Code
Slack
+
Set
Code
Slack
22 NœudsCheng Siong Chin
Extraction de documents
Système d'alerte de santé Grok-3 piloté par l'IA (avec notification des membres de la famille)
Système de surveillance de la santé basé sur l'analyse Grok-3 AI, avec alertes par e-mail pour la famille/les médecins
If
Set
Merge
+
If
Set
Merge
17 NœudsCheng Siong Chin
Productivité personnelle
Analyse automatisée des réunions Microsoft Teams avec GPT-4.1, Outlook et Mem.ai
Utiliser GPT-4.1, Outlook et Mem.ai pour automatiser l'analyse des réunions Microsoft Teams
If
Set
Code
+
If
Set
Code
61 NœudsWayne Simpson
Ressources Humaines
Exemple de workflow d'application de chatbot RAG pour les chaînes ouvertes Bitrix24
Chatbot RAG pour canaux ouverts de Bitrix24, alimenté par l'IA
If
Set
Merge
+
If
Set
Merge
34 NœudsFerenc Erb
Autres
n8n Placeholdarr pour Plex
Bibliothèque média dynamique avec téléchargement à la demande pour Radarr/Sonarr et Plex
If
Set
Ssh
+
If
Set
Ssh
87 NœudsArjan ter Heegde
Gestion de fichiers
Informations sur le workflow
Niveau de difficulté
Intermédiaire
Nombre de nœuds11
Catégorie-
Types de nœuds7
Description de la difficulté
Auteur
Cheng Siong Chin
@cschinProf. Cheng Siong CHIN serves as Chair Professor in Intelligent Systems Modelling and Simulation in Newcastle University, Singapore. His academic credentials include an M.Sc. in Advanced Control and Systems Engineering from The University of Manchester and a Ph.D. in Robotics from Nanyang Technological University.
Liens externes
Voir sur n8n.io →
Partager ce workflow