Title: Gemma 3 4B It vs Gemma 3 27B It: Parametrai, Licencija %E2%80%94 LLM EU
Canonical: https://llmeu.com/lt/compare/gemma-3-4b-it-vs-gemma-3-27b-it/
Markdown mirror: https://llmeu.com/lt/compare/gemma-3-4b-it-vs-gemma-3-27b-it.md
Machine-readable: https://llmeu.com/llms.txt (index) - https://llmeu.com/llms-full.txt (full catalogue) - https://llmeu.com/llms-catalogue.json

# Gemma 3 4B It vs Gemma 3 27B It

Sud%C4%97kite du%E2%80%93keturis modelius greta pagal laukus, kurie lemia diegim%C4%85: kontekstas, kaina, regionas, licencija, kalbos, talpinimas ir tai, kas patikrinta.

Kai du modeliai skiriasi, %C5%A1i lentel%C4%97 parodo skirtum%C4%85 ir sustoja. LLM EU neskelbia nugal%C4%97tojo %C5%BEenklo be dokumentuoto tos u%C5%BEduoties balo, o tr%C5%ABkstamas skai%C4%8Dius lieka tr%C5%ABkstamas, o ne tampa nuliu.

## Kada naudoti

### [Gemma 3 4B It](/lt/models/gemma-3-4b-it/)

#### Stipryb%C4%97s

- open weights are published on Hugging Face and can be downloaded without a vendor agreement
- at 4.3B parameters it fits on a single accelerator
- instruction-tuned checkpoint with a chat template in the repository

#### Apribojimai

- catalogue only %E2%80%94 LLM EU does not run this model, and nothing on this card implies an LLM EU endpoint
- no evaluation has been run by LLM EU
- the published configuration records no context window, so the card carries none
- at 4.3B parameters, the weights fit on a single modest accelerator
- vision checkpoints are heavier to serve than their parameter count alone suggests, because the image encoder and pre-processing run alongside the language model

#### U%C5%BEduotys

[Daugiakalbis palaikymas](/lt/tasks/multilingual-support/), [Vizija](/lt/tasks/vision/), [Ma%C5%BEa kaina](/lt/tasks/cheap/)

### [Gemma 3 27B It](/lt/models/gemma-3-27b-it/)

#### Stipryb%C4%97s

- open weights are published on Hugging Face and can be downloaded without a vendor agreement
- instruction-tuned checkpoint with a chat template in the repository

#### Apribojimai

- catalogue only %E2%80%94 LLM EU does not run this model, and nothing on this card implies an LLM EU endpoint
- no evaluation has been run by LLM EU
- the published configuration records no context window, so the card carries none
- at 27.4B parameters, self-hosting needs a single accelerator with enough memory for the weights
- vision checkpoints are heavier to serve than their parameter count alone suggests, because the image encoder and pre-processing run alongside the language model

#### U%C5%BEduotys

[Daugiakalbis palaikymas](/lt/tasks/multilingual-support/), [Vizija](/lt/tasks/vision/), [M%C4%85stymas](/lt/tasks/reasoning/)

**U%C5%BEduotys:** [Daugiakalbis palaikymas](/lt/tasks/multilingual-support/), [Vizija](/lt/tasks/vision/)

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