Llama 3 8B: Complete Benchmark Performance Guide

meta 3-8b 2024-04-18 Llama 3 Community License

In-depth analysis of Llama 3 8B performance on MMLU, HumanEval, GSM8K, MATH, BBH benchmarks, including pricing and use cases.

Key Specifications

Vendormeta
Version3-8b
Release Date2024-04-18
Context Window8192 tokens
Input Modalitiestext
Output Modalitiestext
LicenseLlama 3 Community License
Documentationhttps://llama.meta.com/docs/

Benchmark Performance

BenchmarkScoreUnitEvaluated AtNotesSource
MMLU67.8%2024-04-185-shotview
HUMANEVAL65pass@12024-04-18—view
GSM8K56.6%2024-04-180-shot CoTview
MATH40%2024-04-180-shot CoTview
BBH65%2024-04-183-shot CoTview
GPQA27.9%2024-04-180-shotview
IFEVAL68.2%2024-04-18prompt_strictview
ARC91.2%2024-04-18challengeview
MUSR46.1%2024-04-180-shotview
WINOGRANDE75.6%2024-04-180-shotview

Pricing

TierPriceCurrency
Input$0.18 / MtokUSD
Output$0.18 / MtokUSD
Cache Read$0 / MtokUSD
Cache Write$0 / MtokUSD

Source: https://ai.meta.com/blog/ · as of 2024-04-18

Compliance

  • Data Residency: self-host
  • SOC2: ✗
  • HIPAA: ✗
  • GDPR: ✗
  • ISO 27001: ✗

Llama 3 8B

Aperçu du modèle

Meta Llama 3 8B 经济型开源模型, 8K 上下文, 8B 参数, 性能超越 Llama 2 13B, 适合本地部署。

Spécifications principales

FournisseurVersionDate de sortieFenêtre de contexteModalités d’entréeModalités de sortieLicence
Meta3-8b2024-04-188KtexttextLlama 3 Community License

Performance aux benchmarks

BenchmarkScoreUnitéNotes
MMLU (Massive Multitask Language Understanding)67.8%5-shot
HumanEval65.0pass@1—
GSM8K (Grade School Math 8K)56.6%0-shot CoT
MATH40.0%0-shot CoT
BBH (BIG-Bench Hard)65.0%3-shot CoT
GPQA27.9%0-shot
IFEval68.2%prompt_strict
ARC91.2%challenge
MUSR46.1%0-shot
WinoGrande75.6%0-shot

Tarification

EntréeSortieLecture cacheÉcriture cache
————

par million de jetons

Forces

  • 可靠的通用模型。

Faiblesses

  • 闭源专有模型，不支持自托管。
  • 上下文窗口 8K 偏小。

Cas d’usage

  • 通用对话与问答

Références