AI模型选择指南2026：如何为你的项目选择最合适的AI模型

from openai import OpenAI

client = OpenAI(
    api_key="your-crazyrouter-key",
    base_url="https://api.crazyrouter.com/v1"
)

# 用 Claude Sonnet 4.5 做代码审查
response = client.chat.completions.create(
    model="claude-sonnet-4-5-20250929",
    messages=[
        {"role": "system", "content": "你是一位资深代码审查专家。请审查以下代码，指出bug、性能问题和改进建议。"},
        {"role": "user", "content": "```python\ndef process_data(items):\n    result = []\n    for i in range(len(items)):\n        if items[i] > 0:\n            result.append(items[i] * 2)\n    return result\n```"}
    ],
    max_tokens=2048
)

# 用 DeepSeek V3.2 写中文文章
response = client.chat.completions.create(
    model="deepseek-v3.2",
    messages=[
        {"role": "system", "content": "你是一位专业的科技博客作者，擅长用通俗易懂的语言解释复杂技术。"},
        {"role": "user", "content": "写一篇关于RAG（检索增强生成）技术的科普文章，1000字左右。"}
    ],
    max_tokens=4096
)

# 用 Gemini 3 Pro 分析长文档
with open("annual_report.txt") as f:
    document = f.read()  # 可能有几十万字

response = client.chat.completions.create(
    model="gemini-3-pro-preview",
    messages=[
        {"role": "system", "content": "分析以下年报，提取关键财务数据和风险因素。"},
        {"role": "user", "content": document}
    ],
    max_tokens=4096
)

def smart_model_router(task: dict) -> str:
    """根据任务类型和复杂度选择最合适的模型"""
    
    task_type = task.get("type", "general")
    complexity = task.get("complexity", "medium")
    language = task.get("language", "en")
    budget = task.get("budget", "normal")
    
    # 编程任务
    if task_type == "coding":
        if complexity == "high":
            return "claude-opus-4-6-20260120"      # 最强编程
        return "claude-sonnet-4-5-20250929"         # 性价比编程
    
    # 中文任务
    if language == "zh":
        if complexity == "high":
            return "gpt-5.2"                        # 高质量中文
        return "deepseek-v3.2"                      # 性价比中文
    
    # 长上下文
    if task.get("context_length", 0) > 128000:
        return "gemini-3-pro-preview"               # 2M 上下文
    
    # 推理任务
    if task_type == "reasoning":
        if budget == "low":
            return "deepseek-r2"                    # 便宜推理
        return "claude-opus-4-6-20260120"           # 最强推理
    
    # 简单任务
    if complexity == "low":
        return "gemini-2.5-flash"                   # 最便宜
    
    # 默认
    return "gpt-5-mini"                             # 综合性价比


# 使用示例
model = smart_model_router({
    "type": "coding",
    "complexity": "medium",
    "language": "en"
})
# 返回: "claude-sonnet-4-5-20250929"

from openai import OpenAI

# 一个 API Key，所有模型
client = OpenAI(
    api_key="your-crazyrouter-key",
    base_url="https://api.crazyrouter.com/v1"
)

# 随时切换模型，只需改 model 参数
models = {
    "编程": "claude-sonnet-4-5-20250929",
    "中文": "deepseek-v3.2",
    "推理": "deepseek-r2",
    "长文档": "gemini-3-pro-preview",
    "快速": "gemini-2.5-flash",
}

for task, model in models.items():
    response = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": f"测试 {task} 任务"}],
        max_tokens=100
    )
    print(f"{task}: {model} ✅")