Title: DeepSeek R1 Distill Qwen 7B vs DeepSeek R1 Distill Qwen %E2%80%94 LLM EU
Canonical: https://llmeu.com/pt/compare/deepseek-r1-distill-qwen-7b-vs-deepseek-r1-distill-qwen-14b/
Markdown mirror: https://llmeu.com/pt/compare/deepseek-r1-distill-qwen-7b-vs-deepseek-r1-distill-qwen-14b.md
Machine-readable: https://llmeu.com/llms.txt (index) - https://llmeu.com/llms-full.txt (full catalogue) - https://llmeu.com/llms-catalogue.json

# DeepSeek R1 Distill Qwen 7B vs DeepSeek R1 Distill Qwen 14B

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

### [DeepSeek R1 Distill Qwen 7B](/pt/models/deepseek-r1-distill-qwen-7b/)

#### Pontos fortes

- open weights are published on Hugging Face and can be downloaded without a vendor agreement
- mit licence, so commercial self-hosting is permitted without a separate agreement
- at 7.6B parameters it fits on a single accelerator

#### 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 7.6B parameters, the weights fit on a single modest accelerator

#### Tarefas

[Racioc%C3%ADnio](/pt/tasks/reasoning/), [Baixo custo](/pt/tasks/cheap/)

### [DeepSeek R1 Distill Qwen 14B](/pt/models/deepseek-r1-distill-qwen-14b/)

#### Pontos fortes

- open weights are published on Hugging Face and can be downloaded without a vendor agreement
- mit 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 14.8B parameters, self-hosting needs a single accelerator with enough memory for the weights

#### Tarefas

[Racioc%C3%ADnio](/pt/tasks/reasoning/)

**Tarefas:** [Racioc%C3%ADnio](/pt/tasks/reasoning/)

## Comparar modelos

- [Deepseek Coder 7B Instruct V1.5 vs DeepSeek R1 Distill Qwen 7B](/pt/compare/deepseek-coder-7b-instruct-v1-5-vs-deepseek-r1-distill-qwen-7b/)
- [DeepSeek R1 Distill Qwen 1.5B vs DeepSeek R1 Distill Qwen 7B](/pt/compare/deepseek-r1-distill-qwen-1-5b-vs-deepseek-r1-distill-qwen-7b/)
- [DeepSeek R1 Distill Qwen 14B vs Devstral Small 2 (24B)](/pt/compare/deepseek-r1-distill-qwen-14b-vs-devstral-small-2-24b/)
- [DeepSeek R1 Distill Qwen 14B vs ERNIE 4.5 21B-A3B Thinking](/pt/compare/deepseek-r1-distill-qwen-14b-vs-ernie-4-5-21b-a3b-thinking/)
- [DeepSeek R1 Distill Qwen 14B vs ERNIE 4.5 VL 28B-A3B](/pt/compare/deepseek-r1-distill-qwen-14b-vs-ernie-4-5-vl-28b-a3b/)
- [DeepSeek R1 Distill Qwen 14B vs EuroLLM-22B-Instruct (2512)](/pt/compare/deepseek-r1-distill-qwen-14b-vs-eurollm-22b-instruct-2512/)