Edge

Check exact model cardOpen weights where releasedUpdated August 2026

Llama 3 8B Instruct

Llama 3 8B Instruct remains useful as a legacy local baseline for lightweight assistant workflows.

Meta · Llama

Editorial review

Reviewed byOpenSourcesAI EditorialLast updatedAugust 2026SourcesHugging Face model card (meta-llama/Meta-Llama-3-8B-Instruct), Hugging Face

Model checkpoints, context windows, provider support, local runtime compatibility, and license terms can change quickly. Verify the exact model card before production or commercial use.

Best for

Local baseline comparisons and lightweight app prototypes.

Who should use it

  • Local baseline comparisons and lightweight app prototypes.
  • Builders who want local or self-hosted testing options.

Common workflows

  • Legacy local assistant baseline
  • legacy workflows
  • local workflows
  • chat workflows

Deployment and hardware notes

Local hardware needs vary by size, quantization, and runtime. Check the exact model card and serving stack.

License and usage notes

Check exact model card. Open weights where released. Verify the exact model card and license terms for the checkpoint or hosted provider you use.

Strengths

  • Open weights where released model option for Llama workflows.
  • Local baseline comparisons and lightweight app prototypes.
  • Use the exact checkpoint and quantization that matches your hardware and latency target.

Limitations

  • Verify license, deployment requirements, runtime support, and fit on your own workload before production use.
  • Local hardware needs vary by size, quantization, and runtime. Check the exact model card and serving stack.
  • Context window and limits: 8,192 tokens, confirmed from the model's published config.
  • Verify the exact model card, provider docs, license, and serving support before production use.

Local workflow notes

Use the exact checkpoint and quantization that matches your hardware and latency target.

Local runtimes: Ollama where supported, LM Studio where supported, llama.cpp where supported, Transformers

Platforms: Windows, macOS, Linux

Sources to verify

Hugging Face model card (meta-llama/Meta-Llama-3-8B-Instruct)Hugging Face

Related resources

Continue with model source notes, local tools, and implementation guides related to this model.

Llama family hubAI tools directoryModel source notesModels directoryGuides library
Hardware~4.9 GB at Q4_K_M (8B parameters)RuntimeOllama or LM Studio where supported, llama.cpp, Transformers, vLLMContext8,192 tokens, confirmed from the model's published configLast updated2026
Hugging Face model card (meta-llama/Meta-Llama-3-8B-Instruct) →

Model ecosystem connections

Use these next-step links to move from this profile into related tools, comparisons, guides, stacks, and curated shortlists.

Recommended runtimes and tools

Ollama →LM Studio →llama.cpp →Transformers →vLLM →

Setup and deployment

Check if this model fits your GPU →What can 12GB VRAM run? →What is quantization? GGUF, Q4, Q8 explained →What is VRAM and how much do you need? →

Related model pages

Llama family hub →Llama 4 Maverick →Llama 4 Scout →Llama Guard 3 →Ministral 3B →Ministral 8B →Llama 3.3 70B →

Guides, stacks, and comparisons

All model comparisons →

Related models

Llama 4 MaverickBuilders comparing current Llama-family models for assistant, multimodal, and reasoning-oriented workflows.Llama 4 ScoutTeams evaluating Llama-family models for multimodal assistant, long-context, and application workflows.Llama Guard 3Safety checks, guardrail experiments, and policy classification workflows.Ministral 3BLow-resource local workflowsMinistral 8BEfficient local workflowsLlama 3.3 70B70B open-weight model in the Llama family.

Ready to run this model locally?

Find a compatible interface in our Local AI Tools directory →