Title: DeepSeek R1 Distill Qwen 14B vs DeepSeek-R1: Parametri %E2%80%94 LLM EU
Canonical: https://llmeu.com/ro/compare/deepseek-r1-distill-qwen-14b-vs-deepseek-r1/
Markdown mirror: https://llmeu.com/ro/compare/deepseek-r1-distill-qwen-14b-vs-deepseek-r1.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 14B vs DeepSeek-R1

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

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

#### Puncte forte

- 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

#### 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 14.8B parameters, self-hosting needs a single accelerator with enough memory for the weights

#### Sarcini

[Ra%C8%9Bionament](/ro/tasks/reasoning/)

### [DeepSeek-R1](/ro/models/deepseek-r1/)

#### Puncte forte

- MIT licence for a 671B-parameter reasoning model
- published reasoning traces in the base training recipe
- strong maths scores for a January 2025 release

#### Limit%C4%83ri

- 671B parameters, so self-hosting is expensive
- reasoning output is verbose and raises token cost
- superseded by DeepSeek-V3.2 and V4-Flash for most workloads

#### Sarcini

[Ra%C8%9Bionament](/ro/tasks/reasoning/), [Codare](/ro/tasks/coding/), [Sumarizare](/ro/tasks/summarization/)

**Sarcini:** [Ra%C8%9Bionament](/ro/tasks/reasoning/)

## Compara%C8%9Bi modele

- [DeepSeek R1 Distill Qwen 1.5B vs DeepSeek R1 Distill Qwen 14B](/ro/compare/deepseek-r1-distill-qwen-1-5b-vs-deepseek-r1-distill-qwen-14b/)
- [DeepSeek R1 Distill Qwen 14B vs DeepSeek R1 0528](/ro/compare/deepseek-r1-distill-qwen-14b-vs-deepseek-r1-0528/)
- [DeepSeek R1 Distill Qwen 14B vs DeepSeek R1 0528 Qwen3 8B](/ro/compare/deepseek-r1-distill-qwen-14b-vs-deepseek-r1-0528-qwen3-8b/)
- [DeepSeek R1 Distill Qwen 14B vs DeepSeek R1 Distill Llama 8B](/ro/compare/deepseek-r1-distill-qwen-14b-vs-deepseek-r1-distill-llama-8b/)
- [DeepSeek R1 Distill Qwen 14B vs DeepSeek-R1-Distill-Qwen-32B](/ro/compare/deepseek-r1-distill-qwen-14b-vs-deepseek-r1-distill-qwen-32b/)
- [DeepSeek R1 Distill Qwen 14B vs Devstral Small 2 (24B)](/ro/compare/deepseek-r1-distill-qwen-14b-vs-devstral-small-2-24b/)