Title: Gemma 3 1B It vs Gemma 3 27B It: Parametri, Licen%C8%9B%C4%83 %E2%80%94 LLM EU
Canonical: https://llmeu.com/ro/compare/gemma-3-1b-it-vs-gemma-3-27b-it/
Markdown mirror: https://llmeu.com/ro/compare/gemma-3-1b-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 1B It vs Gemma 3 27B It

Pune%C8%9Bi dou%C4%83 p%C3%A2n%C4%83 la patru modele al%C4%83turi pe c%C3%A2mpurile care decid o implementare: context, pre%C8%9B, regiune, licen%C8%9B%C4%83, limbi, g%C4%83zduire %C8%99i ce este verificat.

Acolo unde dou%C4%83 modele difer%C4%83, acest tabel arat%C4%83 diferen%C8%9Ba %C8%99i se opre%C8%99te. LLM EU nu public%C4%83 nicio insign%C4%83 de c%C3%A2%C8%99tig%C4%83tor f%C4%83r%C4%83 un punctaj documentat pentru acea sarcin%C4%83, iar o cifr%C4%83 lips%C4%83 r%C4%83m%C3%A2ne lips%C4%83 %C3%AEn loc s%C4%83 devin%C4%83 zero.

## C%C3%A2nd se folose%C8%99te

### [Gemma 3 1B It](/ro/models/gemma-3-1b-it/)

#### Puncte forte

- open weights are published on Hugging Face and can be downloaded without a vendor agreement
- at 1B parameters it fits on a single accelerator
- instruction-tuned checkpoint with a chat template in the repository

#### Limit%C4%83ri

- 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 1B parameters, the weights fit on a single modest accelerator

#### Sarcini

[Suport multilingv](/ro/tasks/multilingual-support/), [Cost redus](/ro/tasks/cheap/)

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

#### Puncte forte

- 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

#### Limit%C4%83ri

- 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

#### Sarcini

[Suport multilingv](/ro/tasks/multilingual-support/), [Viziune](/ro/tasks/vision/), [Ra%C8%9Bionament](/ro/tasks/reasoning/)

**Sarcini:** [Suport multilingv](/ro/tasks/multilingual-support/)

## Compara%C8%9Bi modele

- [Bloom 1b1 vs Gemma 3 1B It](/ro/compare/bloom-1b1-vs-gemma-3-1b-it/)
- [Bloom 560M vs Gemma 3 1B It](/ro/compare/bloom-560m-vs-gemma-3-1b-it/)
- [Bloomz 560M vs Gemma 3 1B It](/ro/compare/bloomz-560m-vs-gemma-3-1b-it/)
- [Command R (08-2024) vs Gemma 3 27B It](/ro/compare/command-r-08-2024-vs-gemma-3-27b-it/)
- [DeepSeek R1 Distill Qwen 1.5B vs Gemma 3 1B It](/ro/compare/deepseek-r1-distill-qwen-1-5b-vs-gemma-3-1b-it/)
- [DeepSeek R1 Distill Qwen 14B vs Gemma 3 27B It](/ro/compare/deepseek-r1-distill-qwen-14b-vs-gemma-3-27b-it/)