Title: DeepSeek V4 Flash vs DeepSeek-V4-Flash: Parametri %E2%80%94 LLM EU
Canonical: https://llmeu.com/ro/compare/deepseek-v4-flash-vs-deepseek-v4-flash-0731/
Markdown mirror: https://llmeu.com/ro/compare/deepseek-v4-flash-vs-deepseek-v4-flash-0731.md
Machine-readable: https://llmeu.com/llms.txt (index) - https://llmeu.com/llms-full.txt (full catalogue) - https://llmeu.com/llms-catalogue.json

# DeepSeek V4 Flash vs DeepSeek-V4-Flash (0731)

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 V4 Flash](/ro/models/deepseek-v4-flash/)

#### 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 290.9B parameters, self-hosting needs multiple high-memory accelerators

#### Sarcini

[Ra%C8%9Bionament](/ro/tasks/reasoning/), [Codare](/ro/tasks/coding/), [Cost redus](/ro/tasks/cheap/)

### [DeepSeek-V4-Flash (0731)](/ro/models/deepseek-v4-flash-0731/)

#### Puncte forte

- MIT licence with no user threshold or field-of-use restriction
- 1M-token context window
- three reasoning-effort levels for latency control
- vendor reports it beats its own larger preview model on published benchmarks

#### Limit%C4%83ri

- 304B parameters require a multi-GPU node even at reduced precision
- all benchmark claims are self-reported by DeepSeek
- no evaluation has been run by LLM EU

#### Sarcini

[Ra%C8%9Bionament](/ro/tasks/reasoning/), [Codare](/ro/tasks/coding/), [Sumarizare](/ro/tasks/summarization/), [Reg%C4%83sire (RAG)](/ro/tasks/rag/)

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

## Compara%C8%9Bi modele

- [Command A+ (05-2026) vs DeepSeek-V4-Flash (0731)](/ro/compare/command-a-plus-05-2026-vs-deepseek-v4-flash-0731/)
- [DeepSeek V4 Flash vs DeepSeek V4.1 Flash](/ro/compare/deepseek-v4-flash-vs-deepseek-v4-1-flash/)
- [DeepSeek V4 Flash vs DeepSeek V4 Pro](/ro/compare/deepseek-v4-flash-vs-deepseek-v4-pro/)
- [DeepSeek V4 Flash vs GLM 4.5](/ro/compare/deepseek-v4-flash-vs-glm-4-5/)
- [DeepSeek V4 Flash vs GLM 4.6](/ro/compare/deepseek-v4-flash-vs-glm-4-6/)
- [DeepSeek V4 Flash vs GLM 5.3 Flash](/ro/compare/deepseek-v4-flash-vs-glm-5-3-flash/)