Cheng Siong Chin This workflow corresponds to n8n.io template #9283 — we link there as the canonical source.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"id": "vwBMikFazJ8dTN7C",
"meta": {
"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
],
"parameters": {
"path": "6737b4b1-3c2f-47b9-89ff-a012c1fa4f29",
"options": {},
"httpMethod": "POST",
"responseMode": "responseNode"
},
"typeVersion": 2.1
},
{
"id": "1f78059c-f7a8-493c-886e-05047d83a7b4",
"name": "Sticky 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\u20144x 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 \u2192 Header Auth \u2192 `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": "Sticky 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": "Format Response",
"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": "Send Aggregated AI Model Responses",
"type": "n8n-nodes-base.respondToWebhook",
"position": [
944,
-544
],
"parameters": {
"options": {}
},
"typeVersion": 1.4
},
{
"id": "0b86c542-74ce-4456-b025-07025e6f57a7",
"name": "Merge AI Model",
"type": "n8n-nodes-base.merge",
"position": [
528,
-576
],
"parameters": {
"numberInputs": 4
},
"typeVersion": 3.2
},
{
"id": "556f837e-5958-4121-9142-f3a05b560190",
"name": "AI Model Router",
"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": "Query 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": {
"name": "<your credential>"
}
},
"typeVersion": 4.2
},
{
"id": "0d948f27-f325-4776-88f5-17993c22f382",
"name": "Query 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": {
"name": "<your credential>"
}
},
"typeVersion": 4.2
},
{
"id": "8fb1c1df-6544-4275-af67-c7f85b9fed92",
"name": "Query 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": {
"name": "<your credential>"
}
},
"typeVersion": 4.2
},
{
"id": "d0e9668b-1c75-4e41-90ec-684abeae0d49",
"name": "Query 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": {
"name": "<your credential>"
}
},
"typeVersion": 4.2
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "34faee65-7df2-4012-93bf-50660415c2d2",
"connections": {
"Merge AI Model": {
"main": [
[
{
"node": "Format Response",
"type": "main",
"index": 0
}
]
]
},
"AI Model Router": {
"main": [
[
{
"node": "Query Qwen3-next-80b-a3b-thinking (Alibaba)",
"type": "main",
"index": 0
}
],
[
{
"node": "Query Bytedance/seed-oss-36b-instruct (Bytedance)",
"type": "main",
"index": 0
}
],
[
{
"node": "Query DeepSeekv3_1",
"type": "main",
"index": 0
}
],
[
{
"node": "Query Nvidia-nemotron-nano-9b-v2 (Nvidia)",
"type": "main",
"index": 0
}
],
[
{
"node": "Query Qwen3-next-80b-a3b-thinking (Alibaba)",
"type": "main",
"index": 0
},
{
"node": "Query Bytedance/seed-oss-36b-instruct (Bytedance)",
"type": "main",
"index": 0
},
{
"node": "Query Nvidia-nemotron-nano-9b-v2 (Nvidia)",
"type": "main",
"index": 0
}
]
]
},
"Format Response": {
"main": [
[
{
"node": "Send Aggregated AI Model Responses",
"type": "main",
"index": 0
}
]
]
},
"Webhook Trigger": {
"main": [
[
{
"node": "AI Model Router",
"type": "main",
"index": 0
}
]
]
},
"Query DeepSeekv3_1": {
"main": [
[
{
"node": "Merge AI Model",
"type": "main",
"index": 2
}
]
]
},
"Query Nvidia-nemotron-nano-9b-v2 (Nvidia)": {
"main": [
[
{
"node": "Merge AI Model",
"type": "main",
"index": 3
}
]
]
},
"Query Qwen3-next-80b-a3b-thinking (Alibaba)": {
"main": [
[
{
"node": "Merge AI Model",
"type": "main",
"index": 0
}
]
]
},
"Query Bytedance/seed-oss-36b-instruct (Bytedance)": {
"main": [
[
{
"node": "Merge AI Model",
"type": "main",
"index": 1
}
]
]
}
}
}
Credentials you'll need
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httpBearerAuth
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About this workflow
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. Webhook Trigger receives queries AI Router distributes to four parallel branches: Qwen2,…
Source: https://n8n.io/workflows/9283/ — original creator credit. Request a take-down →
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