Title: Gpt Neo 125M vs Gpt Neo 2.7B: Param%C3%A9terek, Licenc %E2%80%94 LLM EU
Canonical: https://llmeu.com/hu/compare/gpt-neo-125m-vs-gpt-neo-2-7b/
Markdown mirror: https://llmeu.com/hu/compare/gpt-neo-125m-vs-gpt-neo-2-7b.md
Machine-readable: https://llmeu.com/llms.txt (index) - https://llmeu.com/llms-full.txt (full catalogue) - https://llmeu.com/llms-catalogue.json

# Gpt Neo 125M vs Gpt Neo 2.7B

%C3%81ll%C3%ADtson k%C3%A9t%E2%80%93n%C3%A9gy modellt egym%C3%A1s mell%C3%A9 azokon a mez%C5%91k%C3%B6n, amelyek egy telep%C3%ADt%C3%A9st meghat%C3%A1roznak: kontextus, %C3%A1r, r%C3%A9gi%C3%B3, licenc, nyelvek, hosting %C3%A9s az, hogy mi van ellen%C5%91rizve.

Ahol k%C3%A9t modell elt%C3%A9r, ez a t%C3%A1bl%C3%A1zat megmutatja a k%C3%BCl%C3%B6nbs%C3%A9get, %C3%A9s meg%C3%A1ll. Az LLM EU nem tesz k%C3%B6zz%C3%A9 gy%C5%91ztesjelv%C3%A9nyt az adott feladatra vonatkoz%C3%B3 dokument%C3%A1lt pontsz%C3%A1m n%C3%A9lk%C3%BCl, %C3%A9s a hi%C3%A1nyz%C3%B3 sz%C3%A1m hi%C3%A1nyz%C3%B3 marad ahelyett, hogy null%C3%A1v%C3%A1 v%C3%A1lna.

## Mikor %C3%A9rdemes haszn%C3%A1lni

### [Gpt Neo 125M](/hu/models/gpt-neo-125m/)

#### Er%C5%91ss%C3%A9gek

- 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 0.2B parameters it fits on a single accelerator
- the model page lists en

#### Korl%C3%A1tok

- 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 0.2B parameters, the weights fit on a single modest accelerator

#### Feladatok

[Alacsony k%C3%B6lts%C3%A9g](/hu/tasks/cheap/)

### [Gpt Neo 2.7B](/hu/models/gpt-neo-2-7b/)

#### Er%C5%91ss%C3%A9gek

- 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 2.7B parameters it fits on a single accelerator
- the model page lists en

#### Korl%C3%A1tok

- 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 2.7B parameters, the weights fit on a single modest accelerator

#### Feladatok

Nincs ellen%C5%91rizve: a szolg%C3%A1ltat%C3%B3 nem dokument%C3%A1lta ezt az %C3%A1ll%C3%ADt%C3%A1st.

**Feladatok:** Nincs ellen%C5%91rizve: a szolg%C3%A1ltat%C3%B3 nem dokument%C3%A1lta ezt az %C3%A1ll%C3%ADt%C3%A1st.

## Modellek %C3%B6sszehasonl%C3%ADt%C3%A1sa

- [EmbeddingGemma 300M vs Gpt Neo 125M](/hu/compare/embeddinggemma-300m-vs-gpt-neo-125m/)
- [ERNIE 4.5 0.3B vs Gpt Neo 125M](/hu/compare/ernie-4-5-0-3b-vs-gpt-neo-125m/)
- [Flan T5 Base vs Gpt Neo 125M](/hu/compare/flan-t5-base-vs-gpt-neo-125m/)
- [Flan T5 Small vs Gpt Neo 125M](/hu/compare/flan-t5-small-vs-gpt-neo-125m/)
- [Florence 2 Base Ft vs Gpt Neo 125M](/hu/compare/florence-2-base-ft-vs-gpt-neo-125m/)
- [Gpt Neo 125M vs Gpt Neo 1.3B](/hu/compare/gpt-neo-125m-vs-gpt-neo-1-3b/)