I-API ye-DeepSeek Engacinezelwanga

Abantu abafika kwibinzana elithi "i-API ye-DeepSeek engacinezelwanga" bafuna into enye ethile: imodeli enamandla okuqiqa nokukhowuda e-DeepSeek ephendula umbuzo abawubuzileyo ngokwenene. Isiqingatha samandla sibhaliwe kakuhle — i-DeepSeek-AI ipapashe uyilo namanani, kwaye ubunzima bukwi-Hugging Face phantsi kwe-MIT. Isiqingatha sesibini sisigqibo sokusebenza, kwaye sihlala sisenzelwa wena. Eli phepha ligubungela zombini: sithini isiseko se-V4-Pro, senza ntoni kuso isakhiwo sethu se-3BIT-REAP, kwaye kuthetha ntoni kanye "ukungacinezelwa" xa sikutsho.

01Kuthetha ntoni ngokwenene "i-API ye-DeepSeek engacinezelwanga"

Zimbini iindlela ezahlukeneyo ezifakwa phantsi kwegama elinye. Eyokuqala kukulungelelaniswa okubhakwe kubunzima — ukuziphatha ngokwala okufundwe ngexesha loqeqesho lwasemva. Eyesibini ngumaleko wolinganiselo ohlangothini lwenkonzo: isahluli-ndidi esahlukileyo esihlola umyalelo wakho phambi kokuba imodeli iwubone kunye nemveliso phambi kokuba uyibone, esinokunqumla impendulo phakathi kwesivakalisi nokuba imodeli ibifuna ukuthini na.

Zombini ziyalinganiseleka, kwaye inkonzo yeqela lokuqala ye-DeepSeek ilinganiselwe. I-Promptfoo yaqokelela iseti yemiyalelo eyi-1,360 yemibuzo enobuethe-ethe ngokwezopolitiko yaza yaxela ukuba i-R1 ebisingathwe yi-DeepSeek yayala okanye yaphambukisa eyi-1,156 kuyo — malunga nama-85%. Umsebenzi wemfundo kolu sapho lunye wafumana indlela yokusilela eyahlukileyo ababhali abayibiza ngokuba kukucinezelwa kwengcinga, apho umkhondo wokuqiqa wemodeli uphelela phantse kwangoko uqala kumxholo onobuethe-ethe. Uphicotho olwahlukileyo olupapashwe ku-Information Sciences lwabhala ukucinezelwa kwenqanaba lentsingiselo: isiqulatho esikhoyo ekuqiqeni kwangaphakathi kwemodeli esisuswa ngokuthe cwaka okanye sibhalwe ngokutsha phambi kokuba sifikelele kumsebenzisi. Leyo yingxaki enzima ngaphezu kokwala ngokuphandle, kuba impendulo enqunyulweyo ikhangeleka ngathi yimpendulo.

Into esiyiqhubayo lulokuvulwa kobunzima obuvulekileyo, kwimatshini esiyiqhubayo, e-United States, phantsi kwe-Shannon Lab LLC. Akukho maleko wokwala phambi kwemodeli kwaye akukho sihluzi esisetyenziswa kwinto ebuyayo: umyalelo wakho awuhlelwa ngokomgaqo-nkqubo phambi kokuba uhanjiswe, kwaye umsinga wemveliso awuhlolwa ngoxa uphuma. Kuba isiseko silayisenswe phantsi kwe-MIT yaye sisesidlangalaleni, unako ukuthelekisa iimveliso zethu nobunzima besalathiso ngokwakho endaweni yokuthatha ilizwi lethu.

02Isiseko: i-DeepSeek-V4-Pro, i-MoE ye-1.6T

I-DeepSeek-V4 lusapho lwangoku lobunzima obuvulekileyo lwe-DeepSeek-AI, olwaboniswa kwangaphambili ngo-Aprili 2026 lwaza lwahanjiswa phantsi kwe-MIT ngobungakanani obubini: i-V4-Flash (ezingama-284B zizonke, ezingama-13B ezisebenzayo) kunye ne-V4-Pro (ezingama-1.6T zizonke, ezingama-49B ezisebenzayo). Eli nqaku limalunga nenqanaba le-Pro. Zombini zaqeqeshwa kwangaphambili kwiitoken ezimalunga nezithriliyoni ezingama-33 kwaye zombini zixhasa ngokwemvelo umxholo wetoken enye yezigidi.

Umlinganiselo wokusasazeka yiyo into ekufuneka uyiqaphele: malunga nama-3% kuphela eeparamitha adubulayo kuyo nayiphi na itoken, ekuyiloo nto eyenza imodeli enkulu kangaka ikwazi ukuhanjiswa kwaphela. Ibhloko ye-MoE ngokwayo iseyi-DeepSeekMoE — iingcali ezirawutwayo ezicoliweyo kunye neengcali ezabelwanayo ezihlala zivuliwe ezaziswa kwi-V2 — inotshintsho oluncinci lwe-V4, ikakhulu ukurawutwa kwe-hash kwimaleko yokuqala. I-Multi-Token Prediction, injongo eyongezelelweyo ye-V3 ekwavumela ukufumbatha ngokuqikelela, igcinwe ingatshintshanga.

Iinxalenye ezintsha kwi-V4 zezokwakheka. I-Manifold-Constrained Hyper-Connections (mHC) ithatha indawo yendlela eqhelekileyo yeseleyo ngematriki yokuxuba efundiweyo ebophelelwe kwi-manifold yeematriki ezimbaxa ezingaqinisekanga ngokusebenzisa uprojekshini ye-Sinkhorn–Knopp — umsinga oseleyo ophinda ulinganise ubunzima ngegalelo ngalinye ngaphandle kokuphambuka kwamanani okubulala imifumba enzulu kakhulu. Uqeqesho lwasuka kwi-AdamW lwaya kwi-Muon kwiimodyuli ezininzi, lusebenzisa i-Newton–Schulz orthogonalization, i-AdamW igcinelwe kuphela ii-embedding, iintloko zoqikelelo, ukulinganiswa kunye neeparamitha ze-mHC ezingaguqukiyo. Kwaye ubunzima beengcali buqeqeshwa nge-FP4 ngoxa ezinye iiparamitha ezininzi zikwi-FP8 — ziqonda ukucuthwa ukususela ekuqaleni, into ebalulekileyo kwindlela imodeli ethatha ngayo ukucinezelwa okungakumbi ngobunono.

03Ukusuka kwi-MLA ukuya kwi-CSA + HCA: indlela i-DeepSeek egcina ngayo umxholo omde ushipu

Umgca odlula kwizizukulwana ezine ze-DeepSeek asibobungakanani, kokweemali zengqwalasela. Inguqulelo nganye ihlasele i-KV cache, ekhula ngokungqale ngomxholo yaye idlula ekugcinweni kobude obude.

• I-V2 yazisa i-Multi-head Latent Attention (MLA) — ukucinezelwa okudibeneyo okusezantsi kwezitshixo namaxabiso ibe yi-vector efihlakeleyo, ngoko ukuvelisa kugcina loo vector kunye nesitshixo se-RoPE esahlukanisiweyo endaweni ye-K ne-V epheleleyo yentloko nganye. I-DeepSeek yaxela ukuba i-KV cache yehla yaya malunga nama-4–14% engqwalasela eqhelekileyo yeentloko ezininzi, umgangatho ugcinwe okanye uphuculwa.
• I-V3 yasikhulisa oko saya kuma-671B, yenza i-MLA ibe yingcinga engagqibekanga yomxholo omde oshipu kwiimodeli ezivulekileyo.
• I-V3.2 yongeza i-DeepSeek Sparse Attention (DSA), ikhetha isethana esiphezulu-k semvelaphi kumbuzo ngamnye ngesalathisi esikhaphukhaphu endaweni yokuqwalasela yonke into.
• I-V4 iyadibanisa. I-Compressed Sparse Attention (CSA) kuqala icinezela iingeniso ze-KV zetoken nganye m zibe lingeniso elinye ngobunzima obufundiweyo, ize iqhube ukukhetha okusezantsi okuphezulu-k phezu kwezo ngeniso zicinezelweyo. I-Heavily Compressed Attention (HCA) icinezela kakhulu ngaphezulu kodwa ihlala ishinyene phezu kwesiphumo. Ezi ndidi zimbini zemaleko ziyaphithikezwa kuwo wonke umfumba, ngoko isishwankathelo esishipu sehlabathi kunye nokufunyanwa kwendawo okuchanekileyo ziyahlala kunye.

Umvuzo oxeliweyo kumxholo wetoken enye yezigidi uyamangalisa: i-V4-Pro ifuna malunga nama-27% eeFLOP zokuqikelela ngetoken kunye nama-10% e-KV cache ye-V3.2. Yiyo loo nto isicelo se-262K siziphatha njengesicelo esiqhelekileyo endaweni yesiganeko sokugcina, kwaye yiyo loo nto amanani okufumana kumxholo omde ehlala esimile endaweni yokuwa emva kwamashumi ambalwa amawaka eetoken.

04Ithetha ntoni impumezelo ye-3BIT-REAP

Isazisi sethu sekhathalogu siphelela ku-3BIT-REAP, kwaye oko kuchaza amanyathelo amabini azimeleyo okucinezela asetyenziswe ngokulandelelana.

I-REAP: ukuthena iingcali, ingekuko ukuzidibanisa

I-REAP yi-Router-weighted Expert Activation Pruning, evela kwi-Cerebras Research — "REAP the Experts: Why Pruning Prevails for One-Shot MoE Compression", eyamkelwe kwi-ICLR 2026. Kwi-MoE esasazekileyo irawuta ayizisebenzisi ngokulinganayo iingcali zayo: umsila omde ukhethwa kanqabe, buthathaka, okanye zombini. I-REAP ivavanya ingcali nganye ngokudibanisa amaxabiso egeyithi yerawuta (ukhethwa kangaphi kwaye ngamandla angakanani) kunye neenqobo zokusebenza kwengcali (imveliso yayo inegalelo elingakanani), ize icime abaphulukeneyo ngokupheleleyo.

Ingxoxo yeli phepha kukuba ukuthena koyisa ukudibanisa: ukudibanisa kususa ngomndilili ukukhethekiswa okusebenzayo okwenza i-MoE ifaneleke ukwakhiwa, ngoxa ukucima iingcali irawuta engaphantse ukuzifikelela kukugcina oko. Kwiimodeli ukusuka kuma-20B ukuya kwi-1T, i-REAP yoyisa ukudibanisa neendlela zokuthena ezikhuphisanayo kubalo-mgangatho lokuvelisa, kwaye ababhali baxela iziphumo eziphantse zingalahleki ekuveliseni ikhowudi nasekubizeni izixhobo kukuthenwa kweengcali okungama-50% kwi-Qwen3-Coder-480B nakwi-Kimi-K2 — ekuyiyo kanye imbonakalo yomsebenzi le modeli ekhoyo ngenxa yawo.

Ubunzima obuyi-3-bit: inqanaba lokucinezela lezona ziseko zinkulu

Oko kusindayo kuye kucuthelwe kubunzima obuyi-3-bit. Iibhithi ezintathu zinamandla, kwaye asizenzisi ngenye indlela: kulo lonke uluhlu sisebenzisa i-W8A16 apho isiseko sincinci ngokwaneleyo ukuba singasidingi isicinezelo, i-W4A16-AUTOROUND-REAP phakathi, kunye ne-3BIT-REAP kwezona ziseko zinkulu kuphela, apho ingumahluko phakathi kokuyihambisa imodeli nokungayihambisi.

Umahluko ufanele ukuchazwa ngokucacileyo: i-MoE ye-1.6T ye-3-bit ayifani ngebhithi nokukhutshwa kwesalathiso, kwaye ixabiso elincinci lomgangatho likhona ngokwenene. Into oyifumanayo ngenxa yayo sisiseko esinophahla olungacinezelwanga olungaphezulu lee kunayo nayiphi na into elingana ngokukhululekileyo ngokuchaneka okuphezulu — kwaye kuba iingcali ze-V4 zaqeqeshwa nge-FP4 ukususela ekuqaleni, imodeli iziphatha kakuhle ngokungaqhelekanga phantsi kokucinezelwa okungakumbi kobunzima. Ukuba ufuna isakhiwo se-DeepSeek esinesandla esithambileyo ekuchanekeni, i-DeepSeek-V4-Flash-0731-W4A16-AUTOROUND-REAP isebenzisa ubunzima obuyi-4-bit kunye nokusebenza okuyi-16-bit kunye nokujikeleza okufundiweyo kwe-AutoRound, kumxholo omnye we-262K nge-$0.50 engenayo / $2.00 ephumayo.

05Ukuqiqa, nequbu le-reasoning_effort

Uqeqesho lwasemva lwe-V4 luqeqesha iingcali zecandelo ngokwahlukeneyo — imathematika, ukukhowuda, ii-agent, ukulandela imiyalelo — nge-SFT elandelwa yi-GRPO, indlela ye-Group Relative Policy Optimization eyaziswa yi-DeepSeek ngo-R1. Ezo ngcali ziye zidityaniswe zibe yimodeli enye ngokwahlukanisa okusemgaqweni phantsi kwenjongo ye-reverse-KL, ngoko indawo yokugcina enye iphatha ukuziphatha kwenqanaba lengcali kumacandelo aliqela ngaxeshanye endaweni yokuba yimodeli eqhelekileyo ephakathi kuwo onke.

Imodeli ekhutshiweyo ivula iindlela zokucinga ezinamanqanaba endaweni yeqhosha elivulayo/elivalayo. Kwisango lethu leyo yiparamitha eqhelekileyo ye-reasoning_effort, elona qhosha liluncedo kule modeli:

• Ephantsi — impendulo ephantse ithe ngqo: ukwahlula ngeendidi, ukukhupha, ukubhala ngokutsha, nantoni na apho uhlawulela ulwazi lwemodeli endaweni yokucamngca kwayo.
• Ephakathi — indlela yokusebenza engagqibekanga yokuhlola ikhowudi, ukulungisa iimpazamo nohlalutyo lwamanyathelo amaninzi.
• Ephezulu — ukucamngca okude phambi kokuphendula. Apho iingxaki ezinzima zisonjululwa khona, nalapho ityala lakho leetoken eziphumayo lihlala khona, kuba iitoken zokuqiqa zibhatalwa njengemveliso.

Kuba kungekho maleko wokwala, umkhondo wokuqiqa awunqunyulwa kumxholo onobuethe-ethe — ipatheni yokucinezelwa kwengcinga ebhalwe kwinkonzo yeqela lokuqala ayinandlela yokwenzeka apha.

06Ikhowudi nomsebenzi we-agentic: isiseko sifumana ntoni

La ngamanani apapashwe yi-DeepSeek-AI ngokwayo ngokukhutshwa kwe-V4-Pro — ingengawethu, kwaye angalinganiselwanga kwisakhiwo sethu esicuthiweyo. Siyawabonisa kuba asisizathu esinyanisekileyo sokukhetha esi siseko, kwaye siwaphawula njengawendlu yokuqala ukuze uwanike ubunzima ngokufanelekileyo.

Mabini afanele izimvo. I-SWE-bench Verified kuma-80.6% kukusonjululwa kwemiba yovimba wekhowudi wokwenene — ukufunda ikhowudi ongayiqhelanga, ukufumana isiphene, ukuvelisa isichibi esiphumelela iimvavanyo zeprojekthi ngokwayo. I-MRCR kwitoken enye yezigidi (83.5) kukufunyanwa kwe-coreference kwimijikelo emininzi kubude obupheleleyo, linani elikuxelela ukuba ibango lomxholo omde alilohombiso. I-DeepSeek ikwaxela ulinganiso lwe-Codeforces olungama-3206 kwimodeli, kunye ne-62.0 kwi-CorpusQA kumxholo we-1M.

Amanani angasentla axelwe yi-DeepSeek-AI ngokukhutshwa kwesalathiso se-DeepSeek-V4-Pro. Isakhiwo sethu se-3BIT-REAP luhlobo olucinezelweyo lobo bunzima kwaye alukalinganiselwa ngokuzimeleyo kule misebenzi; wathathe amanqaku esalathiso njengophahla lwesiseko, ingekuko njengomlinganiselo wale ndidi.

07Umxholo we-262K: yintoni engena ngokwenene

Imodeli yesalathiso iqeqeshelwe itoken enye yezigidi. Sihambisa ezingama-262,144 — ifestile yonke imodeli esangweni eyabelana ngayo, ngoko ukutshintsha iimodeli lutshintsho lomgca omnye yaye alusoze lube kukubuya umva komxholo. Ekusebenzeni, i-262K idlule kwindawo apho umxholo ubopha kuwo uninzi lomsebenzi wokwenene:

Umsebenzi	Iitoken malunga	Iyangena kwi-262K?
Uvimba wenkonzo ophakathi (~50k yemigca)	~600K	Hayi — khetha iimodyuli
Icandelo elinye kunye neemvavanyo zalo	~60–120K	Ewe, ngokukhululekileyo
Iseti epheleleyo ye-RFC yeprothokholi	~150K	Ewe
Incwadi yobuchwepheshe yamaphepha angama-700	~250K	Ewe, kufuphi nomda
Ukubaleka kwe-agent okude, imijikelo yezixhobo engama-40+	~80–200K	Ewe

Umda ekufuneka ucwangcise ngawo yimveliso: iitoken ezingama-16,384 ubuninzi kwimpendulo nganye. Loo nto luxwebhu olude okanye isichibi esikhulu seefayile ezininzi, kodwa asingovimba wekhowudi. Imisebenzi emikhulu yokuvelisa yenziwa ngokuqhoboshelanisa izicelo ngemveliso yangaphambili ibuyele emxholweni — nto leyo ifestile ye-262K eyenza ishipu — endaweni yokucela ukugqitywa okunye okukhulu kakhulu.

08Ixabiso, nendawo i-V4-Pro ehleli kuyo kuluhlu

Nge-$1.95 engenayo / $3.90 ephumayo kwitoken enye yezigidi, i-V4-Pro linqanaba eliphambili lokuqiqa — imodeli oyilandelayo xa ingxaki inzima. Xa inkulu nje, iimodeli ezitshiphu kwifestile enye ye-262K ziya kuyenza ngesinye kwesine sexabiso.

Imodeli engacinezelwanga	Engenayo / 1M	Ephumayo / 1M	Umbono	Ilungele
DeepSeek-V4-Pro · 3BIT-REAP	$1.95	$3.90	Hayi	Ukuqiqa okunzima, ikhowudi, ii-agent
DeepSeek-V4-Flash · W4A16	$0.50	$2.00	Hayi	Umnombo omnye, umthamo omkhulu
GLM-5.2 · 3BIT-REAP	$0.73	$2.34	Hayi	Inkabi yemisebenzi yonke
Kimi-K3 · 3BIT-REAP	$3.83	$19.12	Ewe	Ii-agent ezisebenzisa iindlela ezininzi zaphezulu
MiniMax-M3 · 3BIT-REAP	$0.50	$2.00	Ewe	Owona mbono utshiphu

Sithetha ngokuthe ngqo ngothelekiso abantu abaza kulwenza ngokwenene: i-API ye-DeepSeek ngokwayo itshiphu kunale — i-V4-Pro yendlu yokuqala idwelisa malunga ne-$0.435 engenayo / $0.87 ephumayo, kwaye amaxabiso abo egaleleyo elifunyenwe kwi-cache asezantsi nangaphezulu. Ukuba ixabiso ngetoken lelona nqobo lilodwa unalo yaye ukuziphatha kolinganiselo akuwuchaphazeli umsebenzi wakho, sebenzisa i-API yendlu yokuqala; singathanda ukukuxelela oko kunokuba uzokwazi kamva. Ixabiso elongezelelweyo lithenga iseti eyahlukileyo yeempawu: akukho maleko wokwala nasihluzi semveliso, umqhubi wase-US phantsi kwe-Shannon Lab LLC, indawo yokugcina enomhla ebopheleleyo (0813) ukuze ukuphuculwa okuthe cwaka kwangasentla kungaze kutshintshe iimveliso zakho phakathi kweprojekthi, iilwimi ezintathu ze-API kwimodeli enye, kunye nefestile enye ye-262K nobuso beeparamitha kuzo zonke iimodeli ezilishumi elinambini kuluhlu.

09Ukuyibiza: iilwimi ezintathu, imodeli enye

Yonke imodeli esangweni iyaphendula kuzo zontathu iindidi, nokusasaza kwinye nganye. Awuthathi SDK entsha — utshintsha i-URL yesiseko kunye nesazisi semodeli.

curl https://api.shannon-ai.com/v1/chat/completions \
  -H "Authorization: Bearer $SHANNON_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "DeepSeek-V4-Pro-0813-3BIT-REAP",
    "reasoning_effort": "high",
    "stream": true,
    "messages": [
      {"role": "system", "content": "You are a systems programmer. Be direct."},
      {"role": "user", "content": "Audit this parser for memory-safety bugs."}
    ]
  }'

• /v1/chat/completions — ulwimi lwe-OpenAI; lusebenza nee-SDK ze-OpenAI nayo nantoni na eyakhelwe kuzo.
• /v1/messages — ulwimi lwe-Anthropic, lweekhowudi ezisele zibhalelwe eso simo.
• /v1/responses — ujongano olusimo se-Responses.

Okuxhaswayo kule modeli: ukusasaza, ukubiza izixhobo kwemvelo, imveliso ecwangcisiweyo eqinileyo ye-json_schema, response_format, kunye ne-reasoning_effort. Isalathiso esipheleleyo seeparamitha kunye nebala lokudlala eliphilayo zikwamaxwebheni e-API.

10Imida enyanisekileyo

Zine izinto ekufuneka uzazi phambi kokuba wakhe phezu kwayo:

• Akukho mbono. Ngumbhalo kuphela; ayisayi kulwamkela ugalelo lomfanekiso kuyo nayiphi na indidi. Ukuba ufuna imodeli engacinezelwanga ebonayo, sebenzisa i-Kimi-K3, i-Kimi-K2.6, i-MiniMax-M3, i-MiMo-V2.5 okanye i-inkling.
• Uphahla lweetoken ezingama-16,384 lwemveliso. Iitoken zokuqiqa zibalelwa kulo kumandla aphezulu, ngoko ukucamngca okude kushiya indawo encinci yempendulo. Qhoboshelanisa izicelo kwimisebenzi emikhulu yokuvelisa.
• I-3-bit lukucinezela kokwenene. Amanqaku esalathiso achaza isiseko, ingekuko esi sakhiwo. Kwinqanaba elithembeke kakhulu, iimodeli ze-W8A16 (MiMo-V2.5-Pro, MiMo-V2.5, Hy3) zinolona cutho luncinci.
• Ukungacinezelwa akuphumi kwiziphumo. Ukungabikho komaleko wokwala kuthetha ukuba uxanduva lwento oyibuzayo, nento oyenzayo ngempendulo, luhlala kuwe — phantsi kwemimiselo yethu yenkonzo nomthetho apho usebenza khona.

11Imibuzo ebuzwa rhoqo

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Imithombo: DeepSeek-AI — ikhadi lemodeli ye-DeepSeek-V4-Pro · Ingxelo yobuchwepheshe ye-DeepSeek-V4 (CSA/HCA, mHC, Muon) · DeepSeek-V2 (MLA, DeepSeekMoE) · Ingxelo yobuchwepheshe ye-DeepSeek-V3 · REAP the Experts (Cerebras Research) · Uphicotho locinezelo lwe-Promptfoo · Discovering Forbidden Topics in Language Models. Amanani obalo-mgangatho axelwe yi-DeepSeek-AI ngokukhutshwa kwesalathiso; ukuqinisekiswa okuzimeleyo kweqela lesithathu kwesakhiwo esicinezelweyo kusalindile. Amaxabiso ngamaxabiso oluhlu e-Shannon AI njengoko kunjalo nge-5 Septemba 2026.