HAGAHA Shirkadaha
DeepSeek
DeepSeek is an AI model developer whose releases include DeepSeek-R1 and later versioned model families.
Dhageyso hagahanAI-waa laga sheekeeyay · ~2 min
Boggaan2 daqiiqo akhri
Dulmar
Technical claims, benchmark results, licenses and API features must be tied to the exact release.
quusid qoto dheer
The DeepSeek-R1 paper describes an RL-oriented reasoning approach; R1-Zero uses large-scale reinforcement learning without an initial supervised-fine-tuning stage, while R1 adds cold-start data and additional stages. The official R1 repository states MIT terms for that release’s code and model weights. In September 2026, DeepSeek announced V4.1-Flash as a 552B mixture-of-experts model with 8B active parameters for input and 16B for output, plus native visual understanding. Official API model metadata lists a 1,048,576-token context window for V4.1-Flash. These details belong to specific releases and should not be generalized across the model family.
Dhaqangelinta Adduunka-dhabta ah
Compare the R1 and R1-Zero training descriptions in the dated technical report.
Check the official R1 repository for the license stated for that release.
For V4.1-Flash, verify the architecture and active-parameter counts against its September 2026 release post.
Before integrating an API model, confirm the current model identifier and supported modalities in the official model list.
Mustaqbalka DeepSeek
DeepSeek model names, routing and API specifications can change. Check current official release posts and model metadata before using a particular version. Treat company-reported benchmark comparisons as scoped to their stated tasks and conditions; do not infer that one model is universally cheapest or best.
Ku dhaqangelinta
Maxay muhiim u tahay
- Istaraatiijiyadda iibiyaha. Wadooyinka iibiyuhu waxay saameeyaan sifooyinka ay kooxdaadu dhisi karto marka xigta.
- Qiimaha iyo miisaaniyada. Shuruudaha ganacsiga iyo ikhtiyaarka geynta ayaa saameeya kharashka iyo khatarta muddada-dheer.
- Khatarta iyo badbaadada. Dhiirrigelinta shirkadu waxay qaabaysaa wax-soo-saarka alaabada, booska badbaadada, iyo furfurnaanta.
Iska ilaali
- Ogeysiisyada bilawga ah ayaa laga yaabaa inay ka dheereeyaan xasilloonida socodka shaqo ee wax soo saarka dhabta ah.
- Qiimaynta API ama isbedelada siyaasada waxay jebin karaan malo awaalka habeen dhaxa
- Ku-tiirsanaanta iibiyuhu wuxuu kordhiyaa qufulka iyo kharashaadka socdaalka.
Tallaabooyinka xiga
- Qiimee bixiyeyaasha adiga oo isticmaalaya hawlahaaga iyo kaydinta xogtaada.
- Dib u eeg sirta, amniga, iyo shuruudaha sharciga ka hor is dhexgalka.
- Ilaali qorshaha dib u dhaca ee moodooyinka ama iibiyeyaasha.
- La soco qoraalada sii daynta si isbeddellada khariidadda waddo aysan ula yaabin kooxaha.
Sii wad Sahaminta
Warqad bilaash ah
Hel warbixinta maalinlaha ah ee AI
Saddex sheeko oo la xaqiijiyay oo AI ah maalin kasta oo shaqo ah, oo lagu qoray Ingiriis fudud. Bilaash had iyo jeer, aan xayaysiis lahayn.
Hal iimayl maalin kasta oo shaqo ah. Ka bax hal gujin. Marna ma iibinno ama ma wadaagno ciwaankaaga.
Is tijaabi
Take the DeepSeek quiz
Fikrad degdeg ah oo ku saabsan jawaab kasta, iyo shahaado la wadaajin karo oo leh aqoonsi la xaqiijin karo markaad ka gudubto koorso.
Taageer waxbarashada AI bilaashka ah. AI Understanding waa 501(c)(3) aan faa'iido doon ahayn — xayaysiis la'aan, albaab lacag ah ma jiro, had iyo jeer. Samee deeq
Su'aalaha soo noqnoqda
Waa maxay DeepSeek?
DeepSeek is an AI model developer whose releases include DeepSeek-R1 and later versioned model families. Technical claims, benchmark results, licenses and API features must be tied to the exact release.
Which reasoning model did DeepSeek announce on January 20, 2025?
DeepSeek’s dated release announcement introduced DeepSeek-R1 on January 20, 2025; this identifies the model without making a comparative price or performance claim.
What architecture and active-parameter counts does DeepSeek report for V4.1-Flash?
DeepSeek’s September 10, 2026 release announcement describes V4.1-Flash as a 552B MoE model with 8B active parameters for input and 16B for output. These details apply to this version only.
Which organization published the official DeepSeek-R1 model release?
The R1 paper and official repository are published by DeepSeek-AI; this is directly supported by the release rather than an inferred corporate-origin claim.
How did R1-Zero differ from DeepSeek-R1’s training recipe?
The primary report says R1-Zero used large-scale RL without supervised fine-tuning as a preliminary step, whereas R1 adds cold-start data and a multi-stage process.
Which reward signals does the DeepSeek-R1 paper describe for its reasoning-oriented reinforcement-learning stage?
The R1 technical report describes rule-based rewards for verifiable accuracy and format adherence in its reinforcement-learning stages; it does not establish that every DeepSeek model uses the same recipe.
Sii wad waxbarashada
Tilmaamaha la xidhiidha
Tilmaamayaal badan ayaa loo doortay mawduucan