Side-by-Side Comparison · 2026

Gemma vs Llama: Full Comparison (2026)

Gemma is google's lightweight open models - gemma 3 leads open-source benchmarks. Llama is meta's open-source llm family - llama 4 with multimodal moe architecture. Use the breakdown below to find the right fit for your needs.

Gemma

Google DeepMind

Free
vs

Llama

Meta

Free
This page presents factual information sourced from publicly available vendor documentation and product pages. AIHub does not endorse either product. The right tool depends on your specific use case, team, and requirements — we recommend evaluating both tools directly before making a decision.

Side-by-Side Overview

Pricing Model
Gemma: FreeLlama: Free
API Access
Gemma: Not availableLlama: Not available
Platforms
Gemma: WebLlama: Web
Integrations
Gemma: —Llama: —
Vendor
Gemma: Google DeepMindLlama: Meta
Category
Gemma: Language ModelsLlama: Language Models
Launch
Gemma: —Llama: —
Models
Gemma: Gemma 3 27B, Gemma 3 12BLlama: Llama 5 (Apr 2026, 600B+ params, multimodal), Llama 4 Maverick (17B active / 400B total)

About Gemma

Gemma 3 (released Mar 2025) is Google DeepMind's family of open-source models available in 1B, 4B, 12B, and 27B parameter sizes. The 27B model leads open-source benchmarks outperforming Llama 3.3 70B at half the size. Features 128K context and multimodal support.

Designed For

  • Local AI deployment
  • Fine-tuning
  • Research
  • Edge devices
Full Gemma details

About Llama

Llama is Meta's family of open-weight large language models. Llama 4 Scout (17B active params, 16 experts MoE) and Maverick (17B active, 128 experts) delivered top multimodal benchmarks at launch Apr 2025. Llama 3.3 70B remains the best open-source value for text tasks.

Designed For

  • Self-hosted AI
  • Fine-tuning for custom tasks
  • Research
  • Edge deployment
Full Llama details

Strengths & Limitations

Gemma

Strengths

  • Runs on consumer hardware
  • Open weights
  • Gemma 3 27B beats 70B models
  • 128K context
  • Multimodal (image input)

Limitations

  • Smaller capability ceiling vs frontier models
  • No official fine-tuning SLAs

Llama

Strengths

  • Fully open weights
  • Multiple size options (1B–400B)
  • Commercial license
  • Multimodal (Llama 4)
  • MoE efficiency

Limitations

  • Requires hosting infrastructure
  • Large models need significant GPU RAM

Frequently Asked Questions

What is the difference between Gemma and Llama?

Gemma is google's lightweight open models - gemma 3 leads open-source benchmarks, while Llama is meta's open-source llm family - llama 4 with multimodal moe architecture. Gemma is designed for Language Models; Llama is designed for Language Models. The right fit depends on your specific requirements.

How do the pricing models compare?

Gemma is available under a Free model. Llama is available under a Free model. Always verify pricing on each vendor's official website as it may change.

How do I choose between Gemma and Llama?

Consider your team's technical requirements, budget, existing tooling, and use case before deciding. We recommend signing up for free trials or demos of both tools where available, and consulting each vendor's documentation. AIHub provides this comparison for informational purposes only.