llama3.1-8b

llama3.1-8b

Lightweight open-source model
2024-07-23
LLM
Model capability: function_call
Input:
$0.5/1M tokens
Output:
$0.5/1M tokens
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API Overview

Llama 3.1 8B is a lightweight, open-source language model released by Meta, primarily designed as a high-efficiency inference engine that is “small yet powerful, fast and accurate.” It’s ideal for scenarios with limited resources but demanding high-quality outputs.

  • Comprehensive performance upgrade: Compared to the previous Llama 3 8B, its inference capabilities, knowledge coverage, and instruction following have been significantly enhanced.
  • Ultra-long context support: Natively supports up to 128K tokens of context, effortlessly handling long-text inputs and multi-turn conversations.
  • Broad multilingual coverage: Supports over 100 languages, delivering more natural and accurate generation in non-English languages.
  • Extremely low deployment barrier: Can run efficiently on consumer-grade GPUs (such as RTX 3060/4060) or even CPUs.
  • AI agent-friendly: New features include structured output and Function Calling capabilities, making it well-suited for automated tool integration scenarios.

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Core Capabilities

⚡ Ultra-fast local inference: A lightweight architecture delivers second-level response times, enabling smooth execution of complex tasks even on laptops.

🧠 Precise instruction understanding: After enhanced alignment training, it can accurately execute fine-grained requirements such as formatting, style, and logic.

🌍 Truly multilingual: Beyond mere translation, it can understand and generate authentic expressions that are perfectly suited to local contexts.

🧰 Out-of-the-box AI agents: Natively supports tool calls and JSON output, making it easy to integrate into AI automation workflows.

Playground

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API Analytics

API Reference (1)

API DescriptionAPI EndpointRequest MethodStabilityParameter Description
Chat(LLaMA3.1)
POST
Stable
View Details

API Pricing

$
ModelDescriptionContextOfficial Price302.AI Price

llama3.1-8b

-
128000

Input$0.5 / 1M tokens
Output$0.5 / 1M tokens

Input$0.5/ 1M tokens
Output$0.5/ 1M tokens
Original Price