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DeepSeek R1 Distill Qwen 14B vs DeepSeek-R1-Distill-Qwen-32B
Stavite dva do četiri modela jedan pored drugoga na poljima koja odlučuju o implementaciji: kontekst, cijena, regija, licenca, jezici, hosting i što je verificirano.
| DeepSeek R1 Distill Qwen 14B | DeepSeek-R1-Distill-Qwen-32B | |
|---|---|---|
| Pružatelj | DeepSeek | DeepSeek |
| Parametri | 14.8B | 32.76B |
| Prozor konteksta | Nije provjereno: pružatelj nije dokumentirao ovu tvrdnju. | 131k |
| Licenca | mit | mit |
| Modaliteti | text | text |
| Datum izdanja | 20. sij 2025. | 20. sij 2025. |
| Jezici | Nije provjereno: pružatelj nije dokumentirao ovu tvrdnju. | Jako: en, zh Zadovoljavajuće: de, fr, es, it, pt, ru |
| Otvoreni utezi | da | da |
| Zadaci | Zaključivanje | Zaključivanje, Kodiranje, Niska cijena, Sažimanje |
Kada se dva modela razlikuju, ova tablica pokazuje razliku i tu staje. LLM EU ne objavljuje značku pobjednika bez dokumentiranog rezultata za taj zadatak, a brojka koja nedostaje ostaje nedostajuća umjesto da postane nula.
Kada ga koristiti
DeepSeek R1 Distill Qwen 14B
Prednosti
- 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
Ograničenja
- catalogue only — 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
Zadaci
DeepSeek-R1-Distill-Qwen-32B
Prednosti
- fits a single 80GB accelerator
- MIT licence
- retains the R1 reasoning style that smaller base models usually lack
Ograničenja
- a distillation, so quality is bounded by the teacher
- long reasoning traces increase output cost
- no evaluation has been run by LLM EU
Zadaci
Zadaci: Zaključivanje
Usporedi modele
Usporedi modele →- Command R (08-2024) vs DeepSeek-R1-Distill-Qwen-32B
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