SiliconFlow AI Infra

SiliconFlow

模型 & 价格


deepseek-ai/deepseek-v2-chat	¥1.33/1M tokens
deepseek-ai/deepseek-llm-67b-chat	¥1/1M tokens
alibaba/Qwen2-7B-Instruct	¥0.35/1M tokens
alibaba/Qwen1.5-110B-Chat	¥4.13/1M tokens
alibaba/Qwen1.5-32B-Chat	¥1.26/1M tokens
alibaba/Qwen1.5-14B-Chat	¥0.7/1M tokens
alibaba/Qwen1.5-7B-Chat	¥0.35/1M tokens
01-ai/Yi-1.5-34B-Chat	¥1.26/1M tokens
01-ai/Yi-1.5-9B-Chat	¥0.42/1M tokens
01-ai/Yi-1.5-6B-Chat	¥0.35/1M tokens
zhipuai/glm4-9B-chat	¥0.6/1M tokens
zhipuai/chatglm3-6B	¥0.35/1M tokens
meta/llama3-70B-chat	¥4.13/1M tokens
meta/llama3-8B-chat	¥0.42/1M tokens
mixtralai/Mixtral-8x22B-Instruct-v0.1	¥4.13/1M tokens
mixtralai/Mixtral-8x7B-Instruct-v0.1	¥1.26/1M tokens
mixtralai/Mistral-7B-Instruct-v0.2	¥0.35/1M tokens
google/gemma-7b-it	¥0.35/1M tokens
google/gemma-2b-it	¥0.14/1M tokens
microsoft/Phi-3-mini-4k-instruct

价格

OpenAI API

from openai import OpenAI


client = OpenAI(
    api_key="sk-xxxxxx", 
    base_url="https://api.siliconflow.cn/v1"
)

response = client.chat.completions.create(
    model='deepseek-ai/deepseek-v2-chat',
    messages=[
        {'role': 'user', 'content': "你好！"}
    ]
)

print(response.choices[0].message.content)

流式输出

from openai import OpenAI


client = OpenAI(
    api_key="sk-xxxxxx", 
    base_url="https://api.siliconflow.cn/v1"
)

response = client.chat.completions.create(
    model='deepseek-ai/deepseek-v2-chat',
    messages=[
        {'role': 'user', 'content': "介绍一下你自己吧。"}
    ],
    stream=True
)

for chunk in response:
    print(chunk.choices[0].delta.content)

CURL

curl --request POST \
     --url https://api.siliconflow.cn/v1/chat/completions \
     --header 'Authorization: Bearer sk-xxxxxx' \
     --header 'accept: application/json' \
     --header 'content-type: application/json' \
     --data '{
  "model": "deepseek-ai/deepseek-v2-chat",
  "messages": [
    {
      "role": "user",
      "content": "你好"
    }
  ],
  "stream": false,
  "max_tokens": 512,
  "temperature": 0.7
}'

目录

SiliconFlow

模型 & 价格

OpenAI API

CURL