Meta-Llama-3.1-8B-Instruct
Version: 6
Models from Microsoft, Partners, and Community
Models from Microsoft, Partners, and Community models are a select portfolio of curated models both general-purpose and niche models across diverse scenarios by developed by Microsoft teams, partners, and community contributors- Managed by Microsoft: Purchase and manage models directly through Azure with a single license, world class support and enterprise grade Azure infrastructure
- Validated by providers: Each model is validated and maintained by its respective provider, with Azure offering integration and deployment guidance.
- Innovation and agility: Combines Microsoft research models with rapid, community-driven advancements.
- Seamless Azure integration: Standard Microsoft Foundry experience, with support managed by the model provider.
- Flexible deployment: Deployable as Managed Compute or Serverless API, based on provider preference.
Responsible AI considerations
Safety techniques
As part of our Responsible release approach, we followed a three-pronged strategy to managing trust & safety risks: ● Enable developers to deploy helpful, safe and flexible experiences for their target audience and for the use cases supported by Llama. ● Protect developers against adversarial users aiming to exploit Llama capabilities to potentially cause harm. ● Provide protections for the community to help prevent the misuse of our models. Llama is a foundational technology designed to be used in a variety of use cases, examples on how Meta's Llama models have been responsibly deployed can be found in our Community Stories webpage . Our approach is to build the most helpful models enabling the world to benefit from the technology power, by aligning our model safety for the generic use cases addressing a standard set of harms. Developers are then in the driver seat to tailor safety foQuality and performance evaluations
Source: Meta In this section, we report the results for Llama 3.1 models on standard automatic benchmarks. For all the evaluations, we use our internal evaluations library.Base pretrained models
| Category | Benchmark | # Shots | Metric | Llama 3 8B | Llama 3.1 8B | Llama 3 70B | Llama 3.1 70B | L |
Model Specifications
Context Length131072
LicenseCustom
Training DataDecember 2023
Last UpdatedFebruary 2026
Input TypeText
Output TypeText
ProviderMeta
Languages8 Languages