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Check exact model cardOpen weights where releasedUpdated August 2026

Gemma 2 27B Instruct

Gemma 2 27B Instruct is a Gemma-family open-weight model for efficient local, app, and assistant workflow evaluation.

Google · Gemma

Editorial review

Reviewed byOpenSourcesAI EditorialLast updatedAugust 2026SourcesHugging Face model card (config.json max_position_embeddings) (google/gemma-2-27b-it), 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

Efficient local prototypes, app workflows, and Gemma-family comparisons.

Who should use it

  • Efficient local prototypes, app workflows, and Gemma-family comparisons.
  • Builders who want local or self-hosted testing options.

Common workflows

  • Efficient local and app workflows
  • local workflows
  • efficient workflows
  • chat workflows
  • open weights 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 Gemma workflows.
  • Efficient local prototypes, app workflows, and Gemma-family comparisons.
  • 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.
  • 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 (config.json max_position_embeddings) (google/gemma-2-27b-it)Hugging Face

Related resources

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

Gemma family hubBest local LLM toolsPrivate local chatbot stackOllama + Open WebUI starter stackAI tools directory
Hardware~16.5 GB at Q4_K_M (27.2B parameters)RuntimeOllama or LM Studio where supported, llama.cpp, Transformers, vLLMContext8,192 tokensLast updated2026
Hugging Face model card (config.json max_position_embeddings) (google/gemma-2-27b-it) →

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

Gemma family hub →Gemma 2 2B Instruct →Gemma 2 9B Instruct →Gemma 3 12B IT →Gemma 3 27B →Gemma 3 12B →Gemma 3 4B →

Guides, stacks, and comparisons

Best local LLM tools →Private local chatbot stack →Ollama + Open WebUI starter stack →All model comparisons →

Related models

Gemma 2 2B InstructEfficient local prototypes, app workflows, and Gemma-family comparisons.Gemma 2 9B InstructEfficient local prototypes, app workflows, and Gemma-family comparisons.Gemma 3 12B ITEfficient local prototypes, app workflows, and Gemma-family comparisons.Gemma 3 27BDevelopers testing capable medium-sized chat models with broad tooling support.Gemma 3 12B12B open-weight model in the Gemma family.Gemma 3 4B4B open-weight model in the Gemma family.

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