mistralai/mistral-nemo
發布時間: 2024-07-19
131,072 context · $0.03/M input tokens · $0.06/M output tokens
A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...
按用量付費
無需預付費用,僅按實際使用量付費
使用以下程式碼範例整合我們的 API:
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["WAVESPEED_API_KEY"],
base_url="https://llm.wavespeed.ai/v1",
timeout=120.0,
max_retries=2,
)
try:
response = client.chat.completions.create(
model="mistralai/mistral-nemo",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content or "")
except Exception as exc:
raise SystemExit(f"LLM request failed: {exc}") from excmistralai mistral-nemo
| Specification | Value |
|---|---|
| Provider | Mistralai |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 131072 tokens |
| Max Output | 16384 tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.0 |
| Output | $0.0 |
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: mistralai/mistral-nemo
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="mistralai/mistral-nemo",
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": "mistralai/mistral-nemo",
"messages": [{"role": "user", "content": "Hello!"}]
}'
mistralai/mistral-nemo
A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...
輸入
$0.025 /M
輸出
$0.055 /M
上下文
131K
最大輸出
16K
工具調用
支援
WaveSpeedAI 定價:輸入每百萬 token $0.03,輸出每百萬 token $0.06。Prompt 快取與批次處理分別計費,可顯著降低長上下文、高重複任務的實際成本。
Mistral Nemo 每次請求最多支援 131K 上下文 token,輸出最多 16K token。
WaveSpeedAI 透過 https://llm.wavespeed.ai/v1 的 OpenAI 相容 Chat Completions 介面提供 Mistral Nemo。大多數 OpenAI SDK 用戶端只需更換 base URL 和 API Key;選用欄位取決於具體模型。
登入 WaveSpeedAI,在 Access Keys 中建立 API Key,然後使用上方顯示的 model id 向 https://llm.wavespeed.ai/v1/chat/completions 發送請求。模型可用性、能力和價格請以目前模型目錄為準。