Llama 3.2 1B Instruct

Meta chat

API ID: meta-llama/llama-3.2-1b-instruct

Input Price
$0.03
/1M tokens
Output Price
$0.20
/1M tokens

About Llama 3.2 1B Instruct

Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate efficiently in low-resource environments while maintaining strong task performance. Supporting eight core languages and fine-tunable for more, Llama 1.3B is ideal for businesses or developers seeking lightweight yet powerful AI solutions that can operate in diverse multilingual settings without the high computational demand of larger models. Click here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md). Usage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).

๐Ÿ’ฐ
Price Ranking
#649 lowest price among 1240 Chat models

Model Specifications

Context Length
60k
Max Output
60k
Release Date
2024-09-25
Capabilities
chat
Input Modalities
text
Output Modalities
text

Best For

  • Conversations, content writing, general assistance

Consider Alternatives For

  • Image understanding (needs vision capability)

๐Ÿ’ฐ Real-World Cost Examples

Estimated monthly costs for common use cases

Personal AI Assistant
$0.07
/month
50 conversations/day, ~500 tokens each
Customer Service Bot
$2.21
/month
1000 tickets/day, ~800 tokens each

Meta Model Lineup

Compare all models from Meta to find the best fit

Model Input Output Context Capabilities
Llama 3.2 1B Instruct Current Free Free 60k chat
Llama 3 70B (Base) Free Free 8k chat
Llama 3 70B (Base) Free Free 8k chat
LlamaGuard 2 8B Free Free 8k chat
Llama 3 8B (Base) Free Free 8k chat
Llama 3 8B (Base) Free Free 8k chat

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๐Ÿš€ Quick Start

Get started with Llama 3.2 1B Instruct API

OpenAI-compatible SDK
from openai import OpenAI

client = OpenAI(
    base_url="https://api.provider.com/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="meta-llama/llama-3.2-1b-instruct",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)