cohere/command-a
256,000 context · $2.50/M input tokens · $10.00/M output tokens
Command A is an open-weights 111B parameter model with a 256k context window focused on delivering great performance across agentic, multilingual, and coding use cases. Compared to other leading proprietary...
按量付费
无需预付费用，仅按实际使用量付费
使用以下代码示例接入我们的 API：
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="cohere/command-a",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)cohere command-a
| Specification | Value |
|---|---|
| Provider | Cohere |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 256000 tokens |
| Max Output | 8192 tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $2.7 |
| Output | $11.0 |
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: cohere/command-a
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="cohere/command-a",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "cohere/command-a",
"messages": [{"role": "user", "content": "Hello!"}]
}'cohere/command-a
Command A is an open-weights 111B parameter model with a 256k context window focused on delivering great performance across agentic, multilingual, and coding use cases. Compared to other leading proprietary...
输入
$2.5 /M
输出
$10 /M
上下文
256K
最大输出
8K
WaveSpeedAI 定价:输入每百万 token $2.50,输出每百万 token $10.00。Prompt 缓存和批处理单独计费,可显著降低长上下文、高重复任务的实际成本。
Command A 单次请求最多支持 256K 上下文 token,输出最多 8K token。
是的。WaveSpeedAI 通过 https://llm.wavespeed.ai/v1 的 OpenAI 兼容端点提供 Command A。把官方 OpenAI SDK 的 base URL 指向该地址,使用 WaveSpeedAI 的 API Key 即可,无需任何其他代码改动。
登录 WaveSpeedAI,在 Access Keys 中生成 API Key,使用上方显示的 model id 向 https://llm.wavespeed.ai/v1/chat/completions 发送请求。新账户可获得免费额度,用于试用 Command A。