免费 AI API
资源目录 2026

from openai import OpenAI
client = OpenAI(
    api_key="sk-你的硅基流动Key",
    base_url="https://api.siliconflow.cn/v1",
)
resp = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-V3",
    messages=[{"role":"user","content":"你好！"}],
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="你的火山引擎 API Key",
    base_url="https://ark.cn-beijing.volces.com/api/v3",
)
resp = client.chat.completions.create(
    model="ep-你的endpoint-id", # 控制台创建接入点
    messages=[{"role":"user","content":"你好！"}],
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="你的智谱 API Key",
    base_url="https://open.bigmodel.cn/api/paas/v4/",
)
resp = client.chat.completions.create(
    model="glm-4-flash", # 永久免费
    messages=[{"role":"user","content":"你好！"}],
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="sk-你的阿里云 API Key",
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
resp = client.chat.completions.create(
    model="qwen-long", # 100万 token/月免费配额
    messages=[{"role":"user","content":"你好！"}],
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="你的腾讯混元 API Key",
    base_url="https://api.hunyuan.cloud.tencent.com/v1",
)
resp = client.chat.completions.create(
    model="hunyuan-lite", # 永久免费
    messages=[{"role":"user","content":"你好！"}],
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="sk-你的 Kimi API Key",
    base_url="https://api.moonshot.cn/v1",
)
resp = client.chat.completions.create(
    model="moonshot-v1-8k",
    messages=[{"role":"user","content":"你好！"}],
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="你的千帆 API Key",
    base_url="https://qianfan.baidubce.com/v2",
)
resp = client.chat.completions.create(
    model="ernie-speed-8k", # 永久免费
    messages=[{"role":"user","content":"你好！"}],
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="你的 MiniMax API Key",
    base_url="https://api.minimaxi.com/v1",
)
resp = client.chat.completions.create(
    model="MiniMax-Text-01",
    messages=[{"role":"user","content":"你好！"}],
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="你的讯飞星火 API Key",
    base_url="https://spark-api-open.xf-yun.com/v1",
)
resp = client.chat.completions.create(
    model="lite", # 或 generalv3.5 / pro-128k
    messages=[{"role":"user","content":"你好！"}],
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="你的 ModelScope Token",
    base_url="https://api-inference.modelscope.cn/v1",
)
resp = client.chat.completions.create(
    model="Qwen/Qwen2.5-72B-Instruct",
    messages=[{"role":"user","content":"你好！"}],
)
print(resp.choices[0].message.content)

import time, random
from openai import OpenAI, RateLimitError
client = OpenAI(
    api_key="你的 OpenCode API Key",
    base_url="https://opencode.ai/zen/v1",
)
def chat(model, msgs, max_retry=4):
    for i in range(max_retry):
        try:
            return client.chat.completions.create(
                model=model, messages=msgs
            ).choices[0].message.content
        except RateLimitError:
            if i==max_retry-1: raise
            time.sleep(2**i + random.random())
# 最稳定: deepseek-v4-flash-free
# 备用:   big-pickle / nemotron-3-super-free
print(chat("deepseek-v4-flash-free",
          [{"role":"user","content":"Hello!"}]))

import requests, urllib.parse
prompt = "a cat on the moon, photorealistic"
url = ("https://image.pollinations.ai/prompt/"
      + urllib.parse.quote(prompt)
      + "?model=flux&width=1024&height=1024")
# 方式1: 直接当 img src 使用（最简单）
print("图片链接:", url)
# 方式2: 下载保存
img = requests.get(url)
with open("out.png","wb") as f: f.write(img.content)

from openai import OpenAI
# 1. 注册 agnes-ai.com 获取免费 API Key
# 2. 在控制台创建 API Key
client = OpenAI(
    api_key="你的 Agnes AI API Key",
    base_url="https://api.agnes-ai.com/v1",
)
resp = client.chat.completions.create(
    model="agnes-2.0-flash", # 文字 / Agentic 旗舰模型
    messages=[{"role":"user","content":"Hello!"}],
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="AIza-你的 Google AI Key",
    base_url="https://generativelanguage.googleapis.com/v1beta/openai/",
)
resp = client.chat.completions.create(
    model="gemini-2.5-flash-lite", # 1500次/天，最高吞吐
    messages=[{"role":"user","content":"Hello!"}],
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="gsk_-你的 Groq Key",
    base_url="https://api.groq.com/openai/v1",
)
resp = client.chat.completions.create(
    model="llama-3.1-8b-instant", # 14400次/天，最大 RPD
    messages=[{"role":"user","content":"Hello!"}],
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="csk-你的 Cerebras Key",
    base_url="https://api.cerebras.ai/v1",
)
resp = client.chat.completions.create(
    model="llama-4-scout-17b-16e-instruct",
    messages=[{"role":"user","content":"Hello!"}],
    max_tokens=1024, # 免费层 context ≤ 8192 tokens
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="sk-or-你的Key",
    base_url="https://openrouter.ai/api/v1",
)
resp = client.chat.completions.create(
    model="meta-llama/llama-3.3-70b-instruct:free",
    messages=[{"role":"user","content":"Hello!"}],
)
# 其他免费: deepseek/deepseek-r1:free
#          qwen/qwen3-coder-480b-a35b-instruct:free
#          google/gemma-3-27b-it:free
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="nvapi-你的Key",
    base_url="https://integrate.api.nvidia.com/v1",
)
resp = client.chat.completions.create(
    model="meta/llama-3.3-70b-instruct",
    messages=[{"role":"user","content":"Hello!"}],
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="你的 SambaNova Key",
    base_url="https://api.sambanova.ai/v1",
)
resp = client.chat.completions.create(
    model="Meta-Llama-3.3-70B-Instruct", # ✅ 免费
    # ❌ 别用 MiniMax-M2.7 → 402 Error
    messages=[{"role":"user","content":"Hello!"}],
)
print(resp.choices[0].message.content)

from openai import OpenAI
client = OpenAI(
    api_key="token.llm7.io 免费领取",
    base_url="https://api.llm7.io/v1",
)
resp = client.chat.completions.create(
    model="deepseek-r1",
    messages=[{"role":"user","content":"Hello!"}],
)
print(resp.choices[0].message.content)

import requests
acct = "你的 Cloudflare Account ID"
tok  = "你的 Cloudflare API Token"
resp = requests.post(
    f"https://api.cloudflare.com/client/v4/accounts/{acct}"
    "/ai/run/@cf/black-forest-labs/flux-1-schnell",
    headers={"Authorization":f"Bearer {tok}"},
    json={"prompt":"a cat on the moon"},
)
if resp.status_code==200:
    with open("out.png","wb") as f: f.write(resp.content)
else: print(resp.json()) # 429=神经元用完

import requests
resp = requests.post(
    "https://api.together.xyz/v1/images/generations",
    headers={"Authorization":"Bearer 你的Key"},
    json={"model":"black-forest-labs/FLUX.1-schnell-Free",
          "prompt":"a cat on the moon",
          "n":1,"width":1024,"height":1024},
)
print(resp.json()["data"][0]["url"])

# pip install fal-client
import fal_client as fal, os
os.environ["FAL_KEY"] = "你的 fal.ai API Key"
result = fal.subscribe(
    "fal-ai/flux/schnell",
    arguments={"prompt":"a cat on the moon"},
)
print(result["images"][0]["url"])

# pip install runware
import asyncio
from runware import Runware, IImageInference
async def main():
    client = Runware(api_key="你的 Runware Key")
    await client.connect()
    images = await client.imageInference(
        IImageInference(
            positivePrompt="a cat on the moon",
            model="runware:100@1",
            numberResults=1,
        )
    )
    print(images[0].imageURL)
asyncio.run(main())