AISavr

Llama vs Gemma

Meta's open-source LLM vs Google's lightweight open model family.

Llama

Meta's powerful open-source language models

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Gemma

Google's lightweight open-source AI models

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Summary

Llama by Meta is the most popular open-weight large language model, offering top-tier performance across a range of sizes. Gemma by Google provides efficient, lightweight models optimized for deployment on consumer hardware and edge devices.

Feature Comparison

Context Window

Llama128K tokens
Gemma8K–128K tokens

Free Tier

LlamaOpen weights
GemmaOpen weights

API Access

LlamaVia providers
GemmaVia providers

Code Generation

LlamaExcellent
GemmaVery Good

Multimodal

Llama
Gemma

Mobile Apps

LlamaVia third-party
GemmaVia third-party

Model Sizes

Llama8B / 70B / 405B
Gemma2B / 7B / 27B

Local Deployment

Llama
Gemma

Community & Ecosystem

LlamaMassive
GemmaGrowing

Hardware Requirements

LlamaModerate to High
GemmaLow to Moderate

Our Verdict

Choose Llama for the most powerful open-weight model with broad community support. Choose Gemma for efficient, lightweight deployment on limited hardware or edge devices.

Frequently Asked Questions

Which is better for local deployment?
Both can run locally. Gemma is easier to deploy on consumer hardware due to its smaller sizes. Llama's 8B model is also very capable, but the larger models need significant resources.
Are these truly free to use?
Both are open-weight models free for research and commercial use, though each has its own license terms. Llama uses the Meta Community License and Gemma uses a permissive Google license.
Which performs better on benchmarks?
At comparable sizes, Llama generally edges out Gemma on most benchmarks. However, Gemma models punch above their weight, with the 27B model competing with much larger models.
Can I fine-tune these models?
Yes, both support fine-tuning. They have large communities creating LoRA adapters and fine-tuned variants for specialized tasks available on Hugging Face.