Meta: Llama 3 8B Instruct

Text input Text output
Author's Description

Meta's latest class of model (Llama 3) launched with a variety of sizes & flavors. This 8B instruct-tuned version was optimized for high quality dialogue usecases. It has demonstrated strong performance compared to leading closed-source models in human evaluations. To read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).

Key Specifications
Cost
$
Context
8K
Parameters
8B
Released
Apr 17, 2024
Speed
Ability
Reliability
Supported Parameters

This model supports the following parameters:

Stop Presence Penalty Tool Choice Top P Temperature Seed Min P Tools Response Format Frequency Penalty Max Tokens
Features

This model supports the following features:

Tools Response Format
Performance Summary

Meta's Llama 3 8B Instruct model, released on April 17, 2024, demonstrates a balanced performance profile, particularly excelling in cost-efficiency and reliability. It consistently offers among the most competitive pricing, ranking in the 94th percentile across five benchmarks, making it a highly economical choice. Furthermore, its reliability is exceptionally strong, with a 91st percentile ranking, indicating very few technical issues and consistent provision of usable responses. In terms of speed, the model exhibits competitive response times, placing in the 60th percentile. While excelling in cost and reliability, the model shows mixed performance across specific benchmarks. It demonstrates strong capabilities in Email Classification (96.0% accuracy) and General Knowledge (87.8% accuracy), with particularly fast durations for email classification. However, its performance in Instruction Following (33.0% accuracy), Reasoning (37.1% accuracy), and Ethics (87.5% accuracy) is notably lower, suggesting areas for improvement in complex multi-step instructions, intricate logical deduction, and nuanced ethical judgment. Despite these areas for development, its overall value proposition is significantly enhanced by its high reliability and cost-effectiveness, making it a compelling option for dialogue-focused use cases where budget and consistent operation are critical.

Model Pricing

Current Pricing

Feature Price (per 1M tokens)
Prompt $0.03
Completion $0.06

Price History

Available Endpoints
Provider Endpoint Name Context Length Pricing (Input) Pricing (Output)
DeepInfra
DeepInfra | meta-llama/llama-3-8b-instruct 8K $0.03 / 1M tokens $0.06 / 1M tokens
Novita
Novita | meta-llama/llama-3-8b-instruct 8K $0.04 / 1M tokens $0.04 / 1M tokens
Groq
Groq | meta-llama/llama-3-8b-instruct 8K $0.05 / 1M tokens $0.08 / 1M tokens
Mancer 2
Mancer 2 | meta-llama/llama-3-8b-instruct 16K $0.03 / 1M tokens $0.06 / 1M tokens
Together
Together | meta-llama/llama-3-8b-instruct 8K $0.1 / 1M tokens $0.1 / 1M tokens
Cloudflare
Cloudflare | meta-llama/llama-3-8b-instruct 7K $0.28 / 1M tokens $0.83 / 1M tokens
Benchmark Results
Benchmark Category Reasoning Free Executions Accuracy Cost Duration
Other Models by meta-llama