meta-llama/llama-3.2-3b-instruct
发布时间: 2024-09-25
80,000 context · $0.05/M input tokens · $0.34/M output tokens
Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it...
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:
import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 2,
});
try {
const response = await client.chat.completions.create({
model: 'meta-llama/llama-3.2-3b-instruct',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 2,
});
try {
const response = await client.chat.completions.create({
model: 'meta-llama/llama-3.2-3b-instruct',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}meta-llama llama-3.2-3b-instruct
| Specification | Value |
|---|---|
| Provider | Meta-Llama |
| 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: meta-llama/llama-3.2-3b-instruct
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="meta-llama/llama-3.2-3b-instruct",
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": "meta-llama/llama-3.2-3b-instruct",
"messages": [{"role": "user", "content": "Hello!"}]
}'
meta-llama/llama-3.2-3b-instruct
Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it...
输入
$0.051 /M
输出
$0.34 /M
上下文
80K
最大输出
16K
通过我们的统一 API 接入 Llama 3.2 3b Instruct — 兼容 OpenAI、无冷启动、透明计费。
WaveSpeedAI 定价:输入每百万 token $0.05,输出每百万 token $0.34。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。
Llama 3.2 3b Instruct 单次请求最多支持 80K 上下文 token,输出最多 16K token。
WaveSpeedAI 通过 https://llm.wavespeed.ai/v1 的 OpenAI 兼容 Chat Completions 接口提供 Llama 3.2 3b Instruct。大多数 OpenAI SDK 客户端只需更换 base URL 和 API Key;可选字段取决于具体模型。
登录 WaveSpeedAI,在 Access Keys 中创建 API Key,然后使用上方显示的 model id 向 https://llm.wavespeed.ai/v1/chat/completions 发送请求。模型可用性、能力和价格请以当前模型目录为准。