Title: Llama Guard 3 8B vs Llama Guard 4 12B: Parametri %E2%80%94 LLM EU
Canonical: https://llmeu.com/ro/compare/llama-guard-3-8b-vs-llama-guard-4-12b/
Markdown mirror: https://llmeu.com/ro/compare/llama-guard-3-8b-vs-llama-guard-4-12b.md
Machine-readable: https://llmeu.com/llms.txt (index) - https://llmeu.com/llms-full.txt (full catalogue) - https://llmeu.com/llms-catalogue.json

# Llama Guard 3 8B vs Llama Guard 4 12B

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

### [Llama Guard 3 8B](/ro/models/llama-guard-3-8b/)

#### Puncte forte

- open weights are published on Hugging Face and can be downloaded without a vendor agreement
- at 8B parameters it fits on a single accelerator
- the model page lists en
- 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 8B parameters, the weights fit on a single modest accelerator
- a classifier, not a chat model: it labels prompts and responses against a safety taxonomy instead of answering them

#### Sarcini

[Date sensibile](/ro/tasks/private/), [Suport clien%C8%9Bi](/ro/tasks/customer-support/)

### [Llama Guard 4 12B](/ro/models/llama-guard-4-12b/)

#### Puncte forte

- open weights are published on Hugging Face and can be downloaded without a vendor agreement
- at 12B parameters it fits on a single accelerator
- the model page lists en
- 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 llama4 (other) licence is a custom agreement whose commercial terms were not established from its published text, so commercial serving is not permitted until a human clears it; the router must not route to it
- 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
- a classifier, not a chat model: it labels prompts and responses against a safety taxonomy instead of answering them

#### Sarcini

[Date sensibile](/ro/tasks/private/), [Viziune](/ro/tasks/vision/), [Suport clien%C8%9Bi](/ro/tasks/customer-support/)

**Sarcini:** [Date sensibile](/ro/tasks/private/), [Suport clien%C8%9Bi](/ro/tasks/customer-support/)

## Compara%C8%9Bi modele

- [Aya Expanse 8B vs Llama Guard 3 8B](/ro/compare/aya-expanse-8b-vs-llama-guard-3-8b/)
- [Gemma 3 12B It vs Llama Guard 4 12B](/ro/compare/gemma-3-12b-it-vs-llama-guard-4-12b/)
- [Gemma 4 12B It vs Llama Guard 4 12B](/ro/compare/gemma-4-12b-it-vs-llama-guard-4-12b/)
- [Gemma 4 E4B IT vs Llama Guard 4 12B](/ro/compare/gemma-4-e4b-it-vs-llama-guard-4-12b/)
- [GLM 4.1V 9B Thinking vs Llama Guard 4 12B](/ro/compare/glm-4-1v-9b-thinking-vs-llama-guard-4-12b/)
- [GLM 4.6V Flash vs Llama Guard 4 12B](/ro/compare/glm-4-6v-flash-vs-llama-guard-4-12b/)