meta-llama/llama-3.1-8b-instruct
Release date: 2024-07-23
16,384 context · $0.02/M input tokens · $0.05/M output tokens
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to...
Pay-per-use
No upfront costs, pay only for what you use
Use the following code examples to integrate with our 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-3.1-8b-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-3.1-8b-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's latest class of model (Llama 3
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient.
It has demonstrated strong performance compared to leading closed-source models in human evaluations.
To read more about the model release, click here. Usage of this model is subject to Meta's Acceptable Use Policy.
| Specification | Value |
|---|---|
| Provider | Meta-Llama |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 16384 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-3.1-8b-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-3.1-8b-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-3.1-8b-instruct",
"messages": [{"role": "user", "content": "Hello!"}]
}'
meta-llama/llama-3.1-8b-instruct
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to...
Input
$0.02 /M
Output
$0.05 /M
Context
16K
Max Output
16K
Tool Use
Supported
Access Llama 3.1 8b Instruct through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Pricing on WaveSpeedAI: $0.02 per million input tokens and $0.05 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.
Llama 3.1 8b Instruct supports up to 16K tokens of context with up to 16K tokens of output per request.
WaveSpeedAI exposes Llama 3.1 8b Instruct at https://llm.wavespeed.ai/v1 through the OpenAI-compatible Chat Completions interface. Most OpenAI SDK clients work by changing the base URL and API key; optional fields depend on the selected model.
Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with the model id shown above. Check the current model catalog for availability, capabilities, and pricing.