add-siliconflow-provider为 OpenClaw 配置硅基流动 (SiliconFlow) 作为模型源。SiliconFlow 是国内领先的 AI 模型推理平台，提供 98+ 个 chat 模型，包含多个免费模型（Qwen3-8B、DeepSeek-R1-8B 等）。使用标准 OpenAI 协议（openai-completions）。包含 provider 注册、模型定义、别名配置、fallback 链接入和验证的完整流程。当管理员说想"加硅基流动"、"配 SiliconFlow"、"接入 SF 模型"、"加 Kimi"、"加 Qwen3"、"加免费模型"、"接入 DeepSeek V3.2"时使用此 skill。
Install via ClawdBot CLI:
clawdbot install jooey/add-siliconflow-providerSiliconFlow（硅基流动）是国内领先的 AI 模型推理平台，提供 98+ 个 chat 模型，涵盖 Qwen、DeepSeek、Kimi、GLM、MiniMax 等主流系列。
核心优势：
openai-completions 协议，即插即用如果还没有 SiliconFlow 账号，请通过邀请链接注册（双方均获赠额度）：
👉 https://cloud.siliconflow.cn/i/ihj5inat
| 项目 | 值 |
|------|------|
| Provider 名称 | siliconflow |
| API 协议 | openai-completions |
| Base URL | https://api.siliconflow.cn/v1 |
| 认证方式 | Bearer Token (API Key) |
| 项目 | 说明 |
|------|------|
| API Key | 在 控制台 创建，格式 sk-xxx |
| 余额 | 免费模型无需余额；付费模型需充值（新用户注册送 ¥14） |
sk-xxx 格式的密钥curl -s 'https://api.siliconflow.cn/v1/user/info' \
-H 'Authorization: Bearer <YOUR_API_KEY>' | python3 -m json.tool期望返回 "status": "normal" 和余额信息。
| 模型 ID | 说明 | 推荐别名 |
|---------|------|----------|
| Qwen/Qwen3-8B | 通义千问 3 代 8B，综合能力强 | sf-qwen3-8b |
| deepseek-ai/DeepSeek-R1-0528-Qwen3-8B | DeepSeek R1 推理蒸馏版 | sf-r1-8b |
| THUDM/glm-4-9b-chat | 智谱 GLM-4 9B | sf-glm4 |
| Qwen/Qwen2.5-7B-Instruct | Qwen 2.5 7B | sf-qwen25-7b |
| Qwen/Qwen2.5-Coder-7B-Instruct | Qwen 2.5 编码专用 | sf-qwen-coder-7b |
| 模型 ID | 输入/输出 (¥/M tokens) | 说明 | 推荐别名 |
|---------|----------------------|------|----------|
| Qwen/Qwen3-30B-A3B | 0.7 / 2.8 | MoE 架构，性价比极高 | sf-qwen3-30b |
| Qwen/Qwen3-Coder-30B-A3B-Instruct | 0.7 / 2.8 | 编码专用 30B | sf-coder-30b |
| deepseek-ai/DeepSeek-V3.2 | 2.0 / 3.0 | DeepSeek 最新版 | sf-dsv3 |
| Pro/deepseek-ai/DeepSeek-V3.2 | 2.0 / 3.0 | Pro 加速版 | sf-dsv3-pro |
| 模型 ID | 输入/输出 (¥/M tokens) | 说明 | 推荐别名 |
|---------|----------------------|------|----------|
| deepseek-ai/DeepSeek-R1 | 4.0 / 16.0 | 推理模型 | sf-r1 |
| Pro/moonshotai/Kimi-K2.5 | 4.0 / 21.0 | 月之暗面最强模型 | sf-kimi |
| Qwen/Qwen3-Coder-480B-A35B-Instruct | 8.0 / 16.0 | 编码旗舰 480B MoE | sf-coder-480b |
cp ~/.openclaw/openclaw.json ~/.openclaw/openclaw.json.backup.$(date +%Y%m%d_%H%M%S)通过 gateway config.patch 添加 SiliconFlow provider。以下为推荐配置（8 个精选模型）：
{
"models": {
"providers": {
"siliconflow": {
"baseUrl": "https://api.siliconflow.cn/v1",
"apiKey": "<YOUR_API_KEY>",
"api": "openai-completions",
"models": [
{
"id": "Qwen/Qwen3-8B",
"name": "Qwen3 8B (Free)",
"reasoning": false,
"input": ["text"],
"cost": {"input": 0, "output": 0, "cacheRead": 0, "cacheWrite": 0},
"contextWindow": 32768,
"maxTokens": 8192
},
{
"id": "deepseek-ai/DeepSeek-R1-0528-Qwen3-8B",
"name": "DeepSeek R1 Qwen3 8B (Free)",
"reasoning": true,
"input": ["text"],
"cost": {"input": 0, "output": 0, "cacheRead": 0, "cacheWrite": 0},
"contextWindow": 32768,
"maxTokens": 8192
},
{
"id": "Qwen/Qwen3-30B-A3B",
"name": "Qwen3 30B MoE",
"reasoning": false,
"input": ["text"],
"cost": {"input": 0.7, "output": 2.8, "cacheRead": 0, "cacheWrite": 0},
"contextWindow": 32768,
"maxTokens": 8192
},
{
"id": "Qwen/Qwen3-Coder-30B-A3B-Instruct",
"name": "Qwen3 Coder 30B",
"reasoning": false,
"input": ["text"],
"cost": {"input": 0.7, "output": 2.8, "cacheRead": 0, "cacheWrite": 0},
"contextWindow": 32768,
"maxTokens": 8192
},
{
"id": "deepseek-ai/DeepSeek-V3.2",
"name": "DeepSeek V3.2",
"reasoning": false,
"input": ["text"],
"cost": {"input": 2.0, "output": 3.0, "cacheRead": 0, "cacheWrite": 0},
"contextWindow": 128000,
"maxTokens": 8192
},
{
"id": "deepseek-ai/DeepSeek-R1",
"name": "DeepSeek R1",
"reasoning": true,
"input": ["text"],
"cost": {"input": 4.0, "output": 16.0, "cacheRead": 0, "cacheWrite": 0},
"contextWindow": 128000,
"maxTokens": 8192
},
{
"id": "Pro/moonshotai/Kimi-K2.5",
"name": "Kimi K2.5",
"reasoning": false,
"input": ["text"],
"cost": {"input": 4.0, "output": 21.0, "cacheRead": 0, "cacheWrite": 0},
"contextWindow": 128000,
"maxTokens": 8192
},
{
"id": "Qwen/Qwen3-Coder-480B-A35B-Instruct",
"name": "Qwen3 Coder 480B",
"reasoning": false,
"input": ["text"],
"cost": {"input": 8.0, "output": 16.0, "cacheRead": 0, "cacheWrite": 0},
"contextWindow": 32768,
"maxTokens": 8192
}
]
}
}
}
}在同一个 patch 中添加别名映射：
{
"agents": {
"defaults": {
"models": {
"siliconflow/Qwen/Qwen3-8B": {"alias": "sf-qwen3-8b"},
"siliconflow/deepseek-ai/DeepSeek-R1-0528-Qwen3-8B": {"alias": "sf-r1-8b"},
"siliconflow/Qwen/Qwen3-30B-A3B": {"alias": "sf-qwen3-30b"},
"siliconflow/Qwen/Qwen3-Coder-30B-A3B-Instruct": {"alias": "sf-coder-30b"},
"siliconflow/deepseek-ai/DeepSeek-V3.2": {"alias": "sf-dsv3"},
"siliconflow/deepseek-ai/DeepSeek-R1": {"alias": "sf-r1"},
"siliconflow/Pro/moonshotai/Kimi-K2.5": {"alias": "sf-kimi"},
"siliconflow/Qwen/Qwen3-Coder-480B-A35B-Instruct": {"alias": "sf-coder-480b"}
}
}
}
}⚠️ agents.defaults.models. 只允许 alias 字段！ 其他字段会导致 Gateway 崩溃。
将免费模型加入 fallback 链作为兜底：
{
"agents": {
"defaults": {
"model": {
"fallbacks": [
"...(现有 fallbacks)...",
"siliconflow/Qwen/Qwen3-8B",
"siliconflow/Qwen/Qwen3-30B-A3B"
]
}
}
}
}推荐 fallback 策略：优先放免费模型 (Qwen3-8B)，然后放便宜模型 (Qwen3-30B)。
# 1. 配置校验
openclaw doctor
# 2. 重启生效
openclaw gateway restart
# 3. 确认状态
openclaw gateway status
# 4. 测试模型切换
# 在聊天中输入: /model sf-kimicurl -s 'https://api.siliconflow.cn/v1/user/info' \
-H 'Authorization: Bearer <API_KEY>' | python3 -c "
import json,sys; d=json.load(sys.stdin)['data']
print(f'充值余额: ¥{d[\"chargeBalance\"]}')
print(f'赠送余额: ¥{d[\"balance\"]}')
print(f'总余额: ¥{d[\"totalBalance\"]}')
"# 所有 chat 模型
curl -s 'https://api.siliconflow.cn/v1/models?sub_type=chat' \
-H 'Authorization: Bearer <API_KEY>' | python3 -c "
import json,sys
models = json.load(sys.stdin)['data']
print(f'共 {len(models)} 个 chat 模型')
for m in sorted(models, key=lambda x: x['id']):
print(f' {m[\"id\"]}')
"curl -s 'https://api.siliconflow.cn/v1/chat/completions' \
-H 'Authorization: Bearer <API_KEY>' \
-H 'Content-Type: application/json' \
-d '{
"model": "Qwen/Qwen3-8B",
"messages": [{"role":"user","content":"说OK"}],
"max_tokens": 5
}'SiliconFlow 有 98+ 个 chat 模型。如需添加更多，先用模型列表 API 查询可用模型，然后按 Step 2 的格式添加到 provider 的 models 数组中。
| 模型 | 输入/输出 (¥/M tokens) | 特点 |
|------|----------------------|------|
| zai-org/GLM-4.6 | 3.5 / 14.0 | 智谱最新旗舰 |
| Pro/deepseek-ai/DeepSeek-R1 | 4.0 / 16.0 | Pro 加速推理 |
| moonshotai/Kimi-K2-Thinking | 4.0 / 16.0 | Kimi 思考模型 |
| Qwen/Qwen3-235B-A22B-Instruct-2507 | 2.5 / 10.0 | Qwen3 指令模型 |
| baidu/ERNIE-4.5-300B-A47B | 2.0 / 8.0 | 百度文心 |
| stepfun-ai/step3 | 4.0 / 10.0 | 阶跃星辰 Step3 |
Pro/ 前缀的模型使用专用推理集群，速度更快但价格略高Qwen/Qwen3-8B 不能写成 qwen/qwen3-8b注册链接：https://cloud.siliconflow.cn/i/ihj5inat （邀请注册双方均获赠额度）
Generated Mar 1, 2026
Small businesses can use SiliconFlow's free models like Qwen3-8B to build cost-effective customer support chatbots. This enables handling FAQs and basic inquiries without upfront costs, leveraging OpenAI compatibility for easy integration into existing systems.
Educational platforms can deploy SiliconFlow's reasoning models like DeepSeek-R1-8B for interactive tutoring and homework help. The free tier allows scalable deployment to students, providing personalized learning experiences with minimal operational expenses.
Marketing agencies can use SiliconFlow's affordable models such as Qwen3-30B to generate blog posts, social media content, and ad copy. The low-cost pricing enables high-volume content production while maintaining quality, ideal for campaigns with tight budgets.
Development teams can integrate SiliconFlow's coding-specific models like Qwen3-Coder-30B into IDEs for real-time code suggestions and debugging. This enhances productivity by providing instant feedback, with free options for startups and paid models for complex projects.
Research institutions can leverage SiliconFlow's high-context models like DeepSeek-V3.2 for summarizing papers, analyzing datasets, and generating reports. The platform's diverse model range supports various academic tasks, from literature reviews to experimental design.
Offer basic AI features using SiliconFlow's free models to attract users, then upsell premium features powered by paid models like DeepSeek-R1 or Kimi-K2.5. This model drives user acquisition with no-cost entry and monetizes through tiered subscriptions.
Develop custom AI applications using SiliconFlow's models and resell them as branded solutions to large corporations. This leverages the platform's low costs and model variety to deliver tailored tools for industries like finance or healthcare.
Create an intermediary service that aggregates SiliconFlow's API with other providers, offering clients a unified interface for multiple AI models. This adds value through simplified billing, model selection, and support, capitalizing on SiliconFlow's competitive pricing.
💬 Integration Tip
Start by testing with free models to validate functionality before scaling to paid models, ensuring API key security and monitoring usage costs.
Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Now with WAL Protocol, Working Buffer, Autonomous Crons, and battle-tested patterns. Part of the Hal Stack 🦞
Use the ClawdHub CLI to search, install, update, and publish agent skills from clawdhub.com. Use when you need to fetch new skills on the fly, sync installed skills to latest or a specific version, or publish new/updated skill folders with the npm-installed clawdhub CLI.
Clawdbot documentation expert with decision tree navigation, search scripts, doc fetching, version tracking, and config snippets for all Clawdbot features
Interact with Moltbook social network for AI agents. Post, reply, browse, and analyze engagement. Use when the user wants to engage with Moltbook, check their feed, reply to posts, or track their activity on the agent social network.
OpenClaw CLI wrapper — gateway, channels, models, agents, nodes, browser, memory, security, automation.
MoltGuard — runtime security plugin for OpenClaw agents by OpenGuardrails. Helps users install, register, activate, and check the status of MoltGuard. Use wh...