meta-llama/llama-3.3-70b-instruct
Ngày phát hành: 2024-12-07
131,072 context · $0.10/M input tokens · $0.32/M output tokens
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...
Pricing
Pay-per-use
No upfront costs, pay only for what you use
Try the model
API Usage
Use the following code examples to integrate with our 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="meta-llama/llama-3.3-70b-instruct",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content or "")
except Exception as exc:
raise SystemExit(f"LLM request failed: {exc}") from excModel Introduction
Meta-Llama llama-3.3-70b-instruct
meta-llama llama-3.3-70b-instruct
Why It Looks Great
- Large Language Model architecture for efficient processing
- 131072 context window for long document handling
- Competitive pricing at $0.1/$0.3 per million tokens
Key Features
- Context Window: 131072 tokens
- Max Output: 16384 tokens
- Vision: Supported
- Function Calling: Supported
Specifications
| 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 |
Pricing
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.1 |
| Output | $0.3 |
How to Use
- Write your prompt — describe the task, provide context, and specify desired output format.
- Submit — the model processes your request and returns the response.
API Integration
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: meta-llama/llama-3.3-70b-instruct
API Usage
Python SDK
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-3.3-70b-instruct",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)cURL
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "meta-llama/llama-3.3-70b-instruct",
"messages": [{"role": "user", "content": "Hello!"}]
}'Notes
- Model: meta-llama/llama-3.3-70b-instruct
- Provider: Meta-Llama
Info
Supported Functionality
API Access Guide
Llama 3.3 70b Instruct API
meta-llama/llama-3.3-70b-instruct
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...
Input
$0.1 /M
Output
$0.32 /M
Context
131K
Max Output
16K
Tool Use
Supported
Try Llama 3.3 70b Instruct on WaveSpeedAI
Access Llama 3.3 70b Instruct through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Frequently Asked Questions about Llama 3.3 70b Instruct
How much does Llama 3.3 70b Instruct cost via the API?+
Pricing on WaveSpeedAI: $0.10 per million input tokens and $0.32 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.
What is the context window of Llama 3.3 70b Instruct?+
Llama 3.3 70b Instruct supports up to 131K tokens of context with up to 16K tokens of output per request.
Is Llama 3.3 70b Instruct OpenAI-compatible?+
WaveSpeedAI exposes Llama 3.3 70b 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.
How do I get started with Llama 3.3 70b Instruct?+
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.