Title: Gemma 4 12B It vs Gemma 4 31B: Par%C3%A2metros, Licen%C3%A7a %E2%80%94 LLM EU Canonical: https://llmeu.com/pt/compare/gemma-4-12b-it-vs-gemma-4-31b/ Markdown mirror: https://llmeu.com/pt/compare/gemma-4-12b-it-vs-gemma-4-31b.md Machine-readable: https://llmeu.com/llms.txt (index) - https://llmeu.com/llms-full.txt (full catalogue) - https://llmeu.com/llms-catalogue.json # Gemma 4 12B It vs Gemma 4 31B Coloque dois a quatro modelos lado a lado nos campos que decidem uma implementa%C3%A7%C3%A3o: contexto, pre%C3%A7o, regi%C3%A3o, licen%C3%A7a, idiomas, alojamento e o que est%C3%A1 verificado. Onde dois modelos diferem, esta tabela mostra a diferen%C3%A7a e para. A LLM EU n%C3%A3o publica um selo de vencedor sem uma pontua%C3%A7%C3%A3o documentada para essa tarefa, e um valor em falta permanece em falta em vez de se tornar zero. ## Quando usar ### [Gemma 4 12B It](/pt/models/gemma-4-12b-it/) #### Pontos fortes - open weights are published on Hugging Face and can be downloaded without a vendor agreement - Apache-2.0 licence, so commercial self-hosting is permitted without a separate agreement - at 12B parameters it fits on a single accelerator - instruction-tuned checkpoint with a chat template in the repository - speech recognition runs locally, so audio never leaves the operator premises #### Limita%C3%A7%C3%B5es - 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 12B 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 #### Tarefas [Suporte multilingue](/pt/tasks/multilingual-support/), [Vis%C3%A3o](/pt/tasks/vision/), [Sumariza%C3%A7%C3%A3o](/pt/tasks/summarization/) ### [Gemma 4 31B](/pt/models/gemma-4-31b/) #### Pontos fortes - open weights are published on Hugging Face and can be downloaded without a vendor agreement - Apache-2.0 licence, so commercial self-hosting is permitted without a separate agreement #### Limita%C3%A7%C3%B5es - 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 32.7B parameters, self-hosting needs a high-memory 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 #### Tarefas [Suporte multilingue](/pt/tasks/multilingual-support/) **Tarefas:** [Suporte multilingue](/pt/tasks/multilingual-support/) ## Comparar modelos - [Aya 23 8B vs Gemma 4 12B It](/pt/compare/aya-23-8b-vs-gemma-4-12b-it/) - [Aya Expanse 8B vs Gemma 4 12B It](/pt/compare/aya-expanse-8b-vs-gemma-4-12b-it/) - [Command R (08-2024) vs Gemma 4 31B](/pt/compare/command-r-08-2024-vs-gemma-4-31b/) - [Diffusiongemma 26B A4B It vs Gemma 4 31B](/pt/compare/diffusiongemma-26b-a4b-it-vs-gemma-4-31b/) - [EuroLLM-22B-Instruct (2512) vs Gemma 4 12B It](/pt/compare/eurollm-22b-instruct-2512-vs-gemma-4-12b-it/) - [EuroLLM-9B-Instruct (2512) vs Gemma 4 12B It](/pt/compare/eurollm-9b-instruct-2512-vs-gemma-4-12b-it/)