使用Nvidia API比较AI模型
中级
这是一个自动化工作流，包含 11 个节点。主要使用 Set, Merge, Switch, Webhook, HttpRequest 等节点。 使用Nvidia API比较AI模型：Qwen、DeepSeek、Seed-OSS和Nemotron
前置要求
- •HTTP Webhook 端点（n8n 会自动生成）
- •可能需要目标 API 的认证凭证
分类
-
工作流预览
可视化展示节点连接关系，支持缩放和平移
导出工作流
复制以下 JSON 配置到 n8n 导入，即可使用此工作流
{
"id": "vwBMikFazJ8dTN7C",
"meta": {
"instanceId": "b91e510ebae4127f953fd2f5f8d40d58ca1e71c746d4500c12ae86aad04c1502",
"templateCredsSetupCompleted": true
},
"name": "使用 Nvidia API 比较 AI 模型：Qwen、DeepSeek、Seed-OSS 和 Nemotron",
"tags": [],
"nodes": [
{
"id": "2fd77eab-0817-4d39-a206-4506b5373765",
"name": "Webhook触发器",
"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": "便签",
"type": "n8n-nodes-base.stickyNote",
"position": [
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],
"parameters": {
"width": 864,
"height": 944,
"content": "# 使用 Nvidia API 比较 AI 模型：Qwen、DeepSeek、Seed-OSS 和 Nemotron"
},
"typeVersion": 1
},
{
"id": "e7f74b77-470b-49e4-a191-577afda45296",
"name": "便签说明4",
"type": "n8n-nodes-base.stickyNote",
"position": [
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],
"parameters": {
"color": 3,
"width": 1312,
"height": 784,
"content": "Emelia 触发器"
},
"typeVersion": 1
},
{
"id": "8a0ca7d2-f4c0-4a95-9a7a-63c9d40ef77e",
"name": "格式化响应",
"type": "n8n-nodes-base.set",
"position": [
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-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": "发送聚合的 AI 模型响应",
"type": "n8n-nodes-base.respondToWebhook",
"position": [
944,
-544
],
"parameters": {
"options": {}
},
"typeVersion": 1.4
},
{
"id": "0b86c542-74ce-4456-b025-07025e6f57a7",
"name": "合并 AI 模型",
"type": "n8n-nodes-base.merge",
"position": [
528,
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],
"parameters": {
"numberInputs": 4
},
"typeVersion": 3.2
},
{
"id": "556f837e-5958-4121-9142-f3a05b560190",
"name": "AI 模型路由器",
"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": "查询 Qwen3-next-80b-a3b-thinking（阿里巴巴）",
"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": "查询 Bytedance/seed-oss-36b-instruct（字节跳动）",
"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": "查询 Nvidia-nemotron-nano-9b-v2（英伟达）",
"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": "查询 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
}
]
]
}
}
}常见问题
如何使用这个工作流？
复制上方的 JSON 配置代码，在您的 n8n 实例中创建新工作流并选择「从 JSON 导入」，粘贴配置后根据需要修改凭证设置即可。
这个工作流适合什么场景？
中级
需要付费吗？
本工作流完全免费，您可以直接导入使用。但请注意，工作流中使用的第三方服务（如 OpenAI API）可能需要您自行付费。
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难度等级
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节点数量11
分类-
节点类型7
作者
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.
外部链接
在 n8n.io 查看 →
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