I-API ye-DeepSeek Flash Engacinezelwanga

Uninzi lwamaqela avavanya i-API ye-LLM alungiselela into engalunganga. Alinganisa ngeyona miyalelo inzima ingamashumi amabini anokuyicinga, akhethe ophumeleleyo, aze afumanise emva kweeveki ezintandathu ukuba amashumi asithoba anesihlanu epesenti omsinga wawo ngumsebenzi omfutshane, ocwangcisiweyo, ophindaphindayo imodeli ebiza isiqingatha sesine yaba iza kuwuphatha ngendlela efanayo. I-DeepSeek-V4-Flash ikhona ngenxa yaloo mashumi asithoba anesihlanu epesenti. Eli phepha limalunga nokwazi ukuba ukunyo — nokuba awukho nini.

01Into oyifumanayo ngokwenene

Impawu	DeepSeek-V4-Flash-0731 · W4A16-AUTOROUND-REAP
Isazisi semodeli	DeepSeek-V4-Flash-0731-W4A16-AUTOROUND-REAP
Umxholo / imveliso ephezulu	iitoken ezingama-262,144 / iitoken ezingama-16,384
Ixabiso kwi-1M (engenayo / ephumayo)	$0.50 / $2.00
Ukusasaza · ukubiza izixhobo · ukuqiqa	Ewe — kuzo zontathu iilwimi
Imveliso ecwangcisiweyo	json_schema kunye ne-response_format
Umfanekiso ongenayo (umbono)	Hayi — ngumbhalo kuphela
Umaleko wokwala / isihluzo semveliso	Akukho
Ihanjiswa kwi-	iqoqo leeGPU le-Shannon

Iilwimi ezintathu ze-API zifikelela kubunzima obunye: i-/v1/chat/completions (emilo we-OpenAI), i-/v1/messages (emilo we-Anthropic), kunye ne-/v1/responses. Ukusasaza kuyasebenza kuzo zontathu. Ireferensi epheleleyo yeeparamitha ikwi-amaxwebhu e-API.

02Ivela phi: umnombo we-DeepSeek

I-DeepSeek-AI ichithe izizukulwana zeemodeli ezihlanu kumnqweno omnye: ukufumana ukuziphatha kwomphambili kwimodeli etshiphu ukuyihambisa, kungekhona etshiphu ukuyiqeqesha kuphela. Phantse sonke isigqibo sokwakha kolu tsala sinomnombo koko, kwaye ezibalulekileyo zipapashiwe. Ezintathu zichaza into oyibizayo xa ubetha kule endpoint.

DeepSeekMoE — iingcali ezicokisekileyo kunye nenye eyabelwanayo

Imaleko ye-Mixture-of-Experts ithathela indawo uthungelwano olunye olukhulu lokondla ngezininzi ezincinci kunye nerawuta ekhetha ezimbalwa kwitoken nganye. Uhlobo lwe-DeepSeek lusika iingcali ngokucokisekileyo ngaphezu kobume obuqhelekileyo beengcali ezisibhozo, ngoko ii-FLOPs ezinye ezisebenzayo zithenga umxube ochanekileyo ngakumbi ngokudibanisa, kwaye lubeka bucala ingcali eyabelwanayo apho itoken nganye idlula khona, ngoko ulwazi oluqhelekileyo alufundwa kwakhona ngokuphindaphindeneyo ngaphakathi kwengcali nganye. I-DeepSeek-V3 yahambisa oko njengeengcali ezingama-256 ezirawutwayo kunye nengcali enye eyabelwanayo, isebenzisa ezisibhozo ezirawutwayo kwitoken nganye — iiparamitha ezingama-671B zizonke, ezingama-37B ezisebenzayo — kunye nokulinganisa umthwalo ngaphandle kwelahleko esisincedo: endaweni yesohlwayo esonakalisa umgangatho, ityekelo lengcali nganye lityhala amanqaku okurawuta phezulu okanye phantsi kwinyathelo ngalinye njengoko loo ngcali iqhuba ngaphantsi okanye ngaphezu komthwalo.

MLA — ingqwalasela elingana kwinkumbulo

Esinye isiqingatha sengxaki yexabiso lokuhambisa yi-KV cache, ekhula ngokuthe tye nomxholo yaye ilawula inkumbulo kubude bolandelelwano obude. I-Multi-head Latent Attention, eyaziswa kwi-DeepSeek-V2, icinezela izitshixo namaxabiso kunye zibe yivektha efihlakeleyo yenqanaba elisezantsi ize igcine leyo, yakhe kwakhona i-K/V esebenzisekayo ngoko nangoko. Amanani e-V2 apapashiweyo e-DeepSeek, xa athelekiswa ne-DeepSeek 67B yabo yangaphambili eshinyeneyo, axela ukwehla kwe-93.3% kwi-KV cache kunye nomsinga wokuvelisa ophezulu ophindwe izihlandlo ezi-5.76×. Yiyo loo nto ifestile yeetoken ezingama-262K iyinto eqhelekileyo kolu sapho endaweni yokuba ibe sisongezelelo esixabisekileyo.

Ingqwalasela esasazekileyo — nomzekelo weetoken ezitshiphu

I-V3.2-Exp yongeza i-DeepSeek Sparse Attention: indeksa elula inika amanqaku iitoken zomxholo ngokuchasene nombuzo, ize umkhethi agcine ezinamanqaku aphezulu kuphela. Inxalenye enomdla yirisithi, ingekuko indlela. I-DeepSeek yapapasha uthelekiso lwecala-ngecala ne-V3.1-Terminus apho i-MMLU-Pro yayilingana kuma-85.0, i-AIME 2025 inyukile (88.4 → 89.3), i-SWE-bench Verified yehle kancinci (68.4 → 67.8) — umgangatho ophantse ulingane — yaza yanciphisa amaxabiso ayo e-API ngaphezu kwe-50% ngemini enye. Isakhiwo, esixelwe ngokunyanisekileyo, sijika sibe lixabiso ngokuthe ngqo. I-Flash yiloo ngxoxo ethathwe inyathelo elinye ngaphambili.

Isizukulwana se-V4

I-V4, eyaboniswa kwangaphambili ngo-Epreli 2026 phantsi kwelayisensi ye-MIT, ithathela indawo isitaki sengqwalasela kwakhona ngento edibeneyo ye-Compressed Sparse Attention ne-Heavily Compressed Attention, iqeqesha nge-optimizer ye-Muon kwiitoken ezingaphezu kwe-32T, kwaye igcina injongo ye-V3 yokuqikelela iitoken ezininzi — esebenza njengokukhupha okuqikelelayo, kwaye i-DeepSeek eyayilinganisa kumlinganiselo wokwamkelwa kwetoken yesibini wama-85–90% ukuze kufunyanwe ukukhawuleza kokukhupha okumalunga ne-1.8× kwi-V3. Isishwankathelo se-V4 sixela i-V4-Pro isebenza kuma-27% ee-FLOPs zokuqikelela kwetoken enye ze-V3.2 nakuma-10% e-KV cache yayo. Usapho luveza amanqanaba amathathu amandla okuqiqa, into iparamitha yethu ye-reasoning_effort ehambelana nayo.

Imithombo: DeepSeek-V2 (arXiv 2405.04434) · DeepSeekMoE (arXiv 2401.06066) · DeepSeek-V3 Technical Report (arXiv 2412.19437) · Isikhokelo seModeli ye-DeepSeek-V3.2-Exp · DeepSeek-V4 (arXiv 2606.19348). Onke amanani axelwe yi-DeepSeek.

03Ithetha ntoni ngokwenene i-"Flash"

Leli linqaku uninzi lothelekiso oluliphosayo, ngoko kufanelekile ukutshiwo ngokuthe tye: i-Flash ye-DeepSeek ayiyiyo i-Pro ecutshiweyo, ethenwe okanye ecinezelweyo. Yimodeli ye-Mixture-of-Experts eqeqeshwe ngokwahlukileyo, encinci, enokuqeqeshwa kwayo kwangaphambili. Iphepha lokubonisa kwangaphambili le-V4 linika ubungakanani obubini:

Amanani avela kwiphepha lokubonisa kwangaphambili le-DeepSeek-V4. Iindawo zokugcina ezisemthethweni esizihambisayo — i-V4-Flash-0731 ne-V4-Pro-0813 — zidwelisa amanani apheleleyo amakhulwana kancinci angama-304B ne-1.7T kwizikhokelo zawo zeemodeli; i-DeepSeek ayiwabuyeleli amanani eeparamitha ezisebenzayo kwezo zakhiwo.

Amanani amabini enza umsebenzi apha. Iiparamitha zizonke zimisela ubungakanani benkumbulo, obugqiba ukuba zizixhobo ezingakanani ezithatyathwa kukukhutshelwa kwemodeli. Iiparamitha ezisebenzayo zimisela izibalo kwitoken nganye, ezigqiba umsinga. I-Flash incinci malunga nezihlandlo eziyi-5.6× kokokuqala kwaye incinci izihlandlo eziyi-3.8× kokwesibini — kwaye kukho into ecokisekileyo efanele ukuqatshelwa kuloo msantsa: i-Flash isebenzisa ezili-13 kwiiparamitha ezingama-284 zezigidigidi, malunga nama-4.6%, ngoxa i-Pro isebenzisa ezingama-49 kwezili-1,600 zezigidigidi, malunga nama-3.1%. I-Flash yeyona modeli isasazeke kancinci. Ayisiyiyo nje i-Pro enezingcali ezimbalwa ezivuliweyo; luyilo olushinyene ngakumbi, olulinganiswe ngokwahlukileyo oluchitha isabelo esikhulu sokwayo kwitoken nganye eliveliswayo. Sisigqibo sobunjineli sokwenene, ingekuko ukuhliswa.

Athini amanani e-DeepSeek

Zombini izikhokelo zeemodeli ezisemthethweni zipapasha amanqaku kwiibalo-mgangatho ezinye ze-agentic nezobunjineli besoftwe, into eyenza olu thelekiso lucoceke ngokungaqhelekanga — ilebhu enye, ikhaneli yovavanyo enye, ubungakanani obubini:

Ubalo-mgangatho (oluxelwe yi-DeepSeek)	V4-Flash-0731	V4-Pro-0813
Terminal Bench 2.1	82.7	87.9
Toolathlon-Verified	70.3	74.1
DeepSWE	54.4	62.7
NL2Repo	54.2	61.5
DSBench-FullStack	68.7	71.1

I-Pro iphumelela kuwo wonke umqolo. Sisihloko esinyanisekileyo eso, kwaye singathanda ukuba usifunde apha endaweni yokusifumana kwimveliso. Kodwa funda imida, kuba yiyo into oyithengayo ngokwenene. Kwi-Terminal Bench 2.1 umsantsa ngamanqaku ama-5.2 kwimodeli enesamashumi amabini anesihlanu seeparamitha; ekusetyenzisweni kwezixhobo ngamanqaku ama-3.8. Umsantsa uyanda apho umsebenzi uba nzulu khona — amanqaku ama-8.3 kwi-DeepSWE, ama-7.3 kwi-NL2Repo, zombini ezivuza ukuqiqa kwekhowudi okuqhubekayo kwamanyathelo amaninzi. Ngumilo wentengiselwano lowo kwitheyibhile enye: i-Flash ivala uninzi lomgama kwimisebenzi emiselweyo ize ilahlekelwe kwimisebenzi engenasiphelo.

Isikhokelo se-Flash se-DeepSeek senza inqaku ngokuthe krele ngakumbi: i-Flash-0731 isebenza ngcono kunokubonwa kwangaphambili kwe-V4-Pro kwiibalo-mgangatho ezidweliweyo nangona inenani leeparamitha ezisebenzayo elincinci kakhulu. Imodeli entsha encinci ibetha endala enkulu yimeko eqhelekileyo kulo mkhakha, kwaye sisizathu sokuba "inqanaba elikhulu" lingaze libe yimpendulo yakho engagqibekanga.

04Ukufunda impumezelo: W4A16-AUTOROUND-REAP

Izazisi zeemodeli zethu zichaza icebo lazo lokucinezela ngokuvakalayo, kuba yiyo into echaphazela kakhulu umgangatho wemveliso yaye phantse akukho mntu uyivezayo. Le yahlulwa ibe ngamabango amathathu.

W4A16 — ubunzima beebhithi ezine, ukusebenza kweebhithi ezilishumi elinesithandathu

Ubunzima bugcinwa kwiibhithi ezine ngabunye; ukusebenza kuhamba ngokuchaneka kweebhithi ezilishumi elinesithandathu. Kukucuthwa kobunzima kuphela oku, kwaye kujolise kwingxaki yokwenene ekuveliseni iitoken, engububanzi benkumbulo endaweni yezibalo. Ukucutha nokusebenza kwakhona bekuya kuthenga isantya esincinci ngakumbi kuze kubeke emngciphekweni ukuwa kokuchaneka okukhulu kakhulu; ukukushiya kwiibhithi ezilishumi elinesithandathu lukhetho olukhuselekileyo, olunokuthembeka okuphezulu. Le nkcazo sisifinyezo senkqubo yokuhambisa — uncwadi lokucutha lubhala into enye njenge-W4 ngobungakanani beqela.

AUTOROUND — ukujikeleza okufundiweyo, hayi ukujikelezela kweyona ikufuphi

Ukucuthwa okungenabuchule kujikelezela ubunzima ngabunye kwelona xabiso likufuphi elinokumelwa. Oko akungcono ngokubonakalayo: ukujikeleza ubunzima obunye ngendlela "engalunganga" kunokurhoxisa impazamo eyaziswa ngabamelwane bayo, kwaye ngobunzima obuzizigidigidi olo dibaniso lulawulayo. I-AutoRound, evela kwi-Intel, iphatha isigqibo sokujikeleza ngokwaso njengento emayifundwe — utshintsho lobunzima ngabunye olunokuqeqeshwa oluthintelwe ku-±0.5, okwaneleyo kanye ukuguqula naliphi na isigqibo esinye sokujikeleza yaye kungengaphezulu, kunye neenqanaba zokunqumla ezinokufundwa, ezilungiselelwe kukwehla kwesantya okunophawu ngokuchasene nenjongo yokwakhiwa kwakhona kwemveliso ngebhloko kwiseti encinci yolungelelaniso. Amanyathelo angamakhulu amabini, kugqityiwe.

Uthelekiso olupapashiweyo lwe-Intel lubonisa i-AutoRound isibetha i-GPTQ kwiimeko ezingama-30 kwezingama-32 ezivavanyiweyo, i-AWQ kwezingama-27 kwezingama-32 kunye ne-OmniQuant kwezingama-29 kwezingama-32 kwiisetingi zobunzima kuphela beebhithi ezine, kunye nokuphucuka ngaphezu kokujikelezela kweyona ikufuphi kwamanqaku okuchaneka angama-6.9 ukuya kuma-33.2 kwiibhithi ezimbini. Akukho nanye kuzo ebiza nantoni na ngexesha lokuqikelela: lukhetho olungcono lwamanani, olwenziwa kanye, ngaphandle kwelayini.

REAP — ukulahla iingcali ekungekho mntu urawuta kuzo

I-REAP (Router-weighted Expert Activation Pruning), evela kwi-Cerebras Systems naseYunivesithi yaseCalgary, kukucinezela kwesitshotsho esinye kwiimodeli ze-MoE. Inika inqaku ingcali nganye ngokuba irawuta ivula ngamandla angakanani nangokufuthi kangakanani kuyo, kuphindwe ngobungakanani bemveliso yaloo ngcali, ize icime ngokuthe ngqo iingcali ezibaluleke kancinci — akukho qeqesho lutsha emva koko.

Okona kufunyaniswe kwiphepha kokusebenzayo: kwimilinganiselo yokucinezela ephezulu, ukuthena iingcali kubetha ukuzidibanisa. Ukudibanisa iingcali ezahlukileyo ngokusebenza kubangela into ababhali abayibiza ngokuwa kwendawo yokusebenza — irawuta ilahlekelwa lulawulo olucokisekileyo, oluxhomekeke kwizinto ezingenayo olwenza i-MoE ifanele ukwakhiwa, ize isale iqhuba phakathi kwezilinganiso ezimileyo. Amanani abo kwiimodeli ezisuka kuma-20B ukuya kwi-1T yeeparamitha: kukucinezelwa kweengcali kwe-25% kwimisebenzi yokukhowuda, i-REAP ilahlekelwa ngama-2.8% okuchaneka okuphakathi apho imilinganiselo yokudibanisa ilahlekelwa ngaphezu kwe-5%; kuma-50%, i-REAP ilahlekelwa ngama-8.0% apho ukudibanisa kulahlekelwa ngaphezu kwama-20%. Kwi-Qwen3-Coder-480B kukuthena kwe-50% ukwehla kukuma-1.4%, xa kuthelekiswa nama-39.3% okuthena okungenabuchule okusekelwe kubuninzi. I-Cerebras ipapashe iindawo zokugcina ze-REAP zotsala lwe-DeepSeek phakathi kwezinye.

Kutheni iibhithi ezine apha nezintathu kwi-Pro

Amanqanaba omabini kufuneka alingane ahlale ekhawuleza kudidi olunye lwezixhobo. I-Pro ithwala iiparamitha ezisithriliyoni esinye nesixhenxe kwelishumi, ngoko ifuna unyango olunamandla ngakumbi lweebhithi ezintathu ukuze ilingane kwaphela. I-Flash ithwala malunga nezigidigidi ezingamakhulu amathathu, ngoko ayifuni — kwaye ibhithi eyigcinayo ichithwa ekuthembekeni endaweni yokulingana.

Loo bhithi eyongezelelweyo ibaluleke ngaphezu koko izibalo zayo zibonisayo, kuba umonakalo wokucutha awuthi tye. Kumalinganiselo e-WikiText-2 ephepha le-AWQ, i-Llama-2-7B isuka kwi-5.47 perplexity kwi-FP16 iye kwi-5.60 kwiibhithi ezine — isohlwayo sama-2.4% — kodwa iye kwi-6.24 kwiibhithi ezintathu, isohlwayo sama-14%. Oko kumalunga nokwehla okuphindwe izihlandlo ezithandathu kukucinezela okungama-25% ngaphezulu, kwaye ipatheni enye ibonakala kwi-70B. Iphepha le-GPTQ likrele ngakumbi: kwiibhithi ezintathu, ukujikelezela kweyona ikufuphi ngokungenabuchule kuyawa kwiimodeli zodidi lwe-175B, kuye kumawaka e-perplexity, ngoxa kuhlala kusebenziseka ngokugqibeleleyo kwiibhithi ezine. Ngaphantsi kweebhithi ezine, i-algorithm elungileyo yokucutha iyeka ukuba yinto entle ize ibe yiyo yodwa into ebambe imodeli kunye.

Ngoko ukufundwa okunyanisekileyo kwezi mpumezelo zimbini kukuthi: i-Flash ihlala ikufuphi kunye nento yayo engacinezelwanga ngaphezu kokuba i-Pro ikufuphi kweyayo. I-Pro isengoyena modeli inamandla — itheyibhile yobalo-mgangatho engasentla iyayigqiba loo nto. Inikezele ngokungaphezulu nje ukuze ifike apha, kwaye uhlawulela elo lungelo.

Imithombo: AutoRound — "Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs" (arXiv 2309.05516), Intel, Findings of EMNLP 2024. REAP — "REAP the Experts: Why Pruning Prevails for One-Shot MoE Compression" (arXiv 2510.13999), Cerebras Systems. Amanani e-perplexity avela kwi-AWQ (arXiv 2306.00978) nakwi-GPTQ (arXiv 2210.17323).

05I-Flash ngokuchasene ne-Pro kwi-endpoint

Icandelo 03 ligubungele iziseko. Nanku umbono weenqanaba ezimbini njengeemveliso kwiSango lethu:

	DeepSeek-V4-Flash-0731	DeepSeek-V4-Pro-0813
Ukucuthwa	W4A16-AUTOROUND-REAP	3BIT-REAP
Ukuchaneka kobunzima	Iibhithi ezine, ukujikeleza okufundiweyo	Iibhithi ezintathu
Isiseko (sizonke / esisebenzayo)	~304B / 13B	~1.7T / 49B
Ezingenayo kwitoken enye yezigidi	$0.50	$1.95
Eziphumayo kwitoken enye yezigidi	$2.00	$3.90
Umxholo / imveliso ephezulu	262,144 / 16,384	262,144 / 16,384
Izixhobo · imveliso ecwangcisiweyo · ukusasaza	Ewe	Ewe
Umbono	Hayi	Hayi
Umaleko wokwala	Akukho	Akukho

Qaphela into engatshintshiyo: umxholo, uphahla lwemveliso, ukubiza izixhobo, imveliso ecwangcisiweyo, kunye nokungabikho komaleko wokwala kuyafana. Izinto ezishukumayo kuphela sisiseko, ukucuthwa, nexabiso. Loo nto yenza ukutshintsha phakathi kwazo kube lutshintsho lomtya omnye kwikhowudi yakho nesigqibo soqoqosho ngokupheleleyo kwisakhiwo sakho.

Ubiza malini umbizo omnye wobungakanani obuphezulu

Zalisa wonke umxholo weetoken ezingama-262,144 uze uthathe imveliso epheleleyo yeetoken ezingama-16,384:

Ngexabiso loluhlu. I-Flash: $0.131 engenayo + $0.033 ephumayo. I-Pro: $0.511 + $0.064. Umlinganiselo 3.51×. I-Flash ikwabelana ngomgangatho osezantsi we-$0.50 / $2.00 ne-MiniMax-M3, i-Laguna-S-2.1, i-MiMo-V2.5, i-MiMo-V2.5-Pro ne-Hy3 — bona ikhathalogu epheleleyo ukubona indlela ezahluka ngayo kumbono nakwimveliso ecwangcisiweyo.

06Izibalo zomthamo, zisenziwe

"Itshiphu izihlandlo eziyi-3.9×" iyinyani kwezingenayo kuphela. Kwezimphumayo i-Flash itshiphu izihlandlo eziyi-1.95×. Ukonga kwakho kokwenene ngoko kuxhomekeke kumlinganiselo wakho wezingenayo kwezimphumayo, kwaye umsantsa ubanzi ngokwaneleyo ukuguqula izigqibo zoyilo. Imisebenzi emine engenakwenzeka, nganye kwizicelo eziyi-100,000:

Umsebenzi	Ezingenayo / eziphumayo kumbizo	Flash	Pro	Ukonga
Ukwahlula amatikiti ngeendidi	1,200 / 120	$84	$281	3.3×
Ukuphendula imibuzo yeRAG	8,000 / 600	$520	$1,794	3.4×
Isishwankathelo soxwebhu olude	60,000 / 1,500	$3,300	$12,285	3.7×
Ukwenziwa kwedatha yokwenziwa	500 / 2,000	$425	$878	2.1×

Ipatheni: okukhona utyhala umxholo omninzi kwaye uvelisa umbhalo omncinci, kokukhona i-Flash ikonga ngakumbi. Imigca yokusebenza yokufumana, ukucubungula amaxwebhu, uhlalutyo lwemifumba nolwezinto ezibhaliweyo, kunye nokukhupha komxholo omde ziindawo ezilungileyo — zilawulwa zizinto ezingenayo ngokweqondo lodidi, kwaye kwezingenayo kulapho isaphulelo esiyi-3.9× sihlala khona. Ukuba endaweni yoko umsebenzi wakho ngumyalelo omfutshane ovelisa amawaka eetoken zombhalo, umsantsa uncipha uye kuma-2× malunga kwaye ingxoxo yesakhono ngokwe-Pro iba namandla ngokulinganayo.

Elinye ilungu lezibalo elifanele ukumbelwa ngaphakathi: nge-$0.50 kwitoken enye yezigidi ezingenayo, yonke ifestile yeetoken ezingama-262,144 ibiza iisenti ezili-13.1 ukuzalisa. Ukuyalela ngomxholo omde kuyeka ukuba ngumbuzo wohlahlo-lwabiwo-mali kwelo xabiso, into ngamanye amaxesha ethetha ukuba unokuwutsiba wonke umaleko wokufumana uze uvumele ifestile yomxholo yenze umsebenzi — ukonga kobunjineli phezu kokonga kwetoken.

07Kuthetha ntoni "ukungacinezelwa" apha, ngokuchanekileyo

Igama lisetyenziswa ngokungakhathali, ngoko nantsi inkcazelo yethu, echazwe njengempawu ye-endpoint: akukho sahluli-ndidi sokwala phambi kwemodeli kwaye akukho kuhluzwa kwesiqulatho okusetyenziswa kwimveliso yayo. Akukho nto ithimba umyalelo ize ibuyise ukwala okusetyiweyo; akukho nto ihlola isigqibo ize isicime. Kumsebenzi wemveliso yomthamo omkhulu iziphumo azimangalisi kwaye zisebenza ngakumbi kunokuba igama libonisa:

• Akukho zimpazamo kumsinga ongenangozi. Ii-endpoint ezihluziweyo zala rhoqo izishwankathelo zonyango, iingxelo zokhuseleko, ukufunyanwa kwezomthetho, intsomi, izinto zokunciphisa umonakalo nomsebenzi wolawulo lomxholo ngokwawo — kanye iindidi apho umsebenzi weqela ucubungula umbhalo ongomxholo obuthathaka endaweni yokuvelisa nantoni na eyingozi. Kwizicelo ezilikhulu lamawaka, umlinganiselo wokwala ngempazamo wepesenti enye ngumqolo owaphukileyo oliwaka.
• Izivumelwano ezimiselweyo. Cela impendulo ye-json_schema uze ufumane i-JSON ehambelana nesikimu, ingekuko isiqendu soxolo apho kufanele kubekho into. Isahluli sakho asifuni sebe lokwala, kwaye ingqiqo yakho yokuzama kwakhona akufuneki yahlule ukusilela kokuhambisa kokomgaqo-nkqubo.
• Umgaqo-nkqubo ngowakho. Yiyo leyo intengiselwano. Ukuba imveliso yakho ifuna izikhuseli kubasebenzisi bakho bokugqibela, uzakha kumaleko wakho, apho ubazi khona abasebenzisi bakho negunya lakho, endaweni yokufumana uqikelelo lomboneleli ngazo zombini. I-akhawunti yakho ihlala ilawulwa yiPolisi yethu yoSetyenziso oluNoxanduva.

Ukungacinezelwa akufani nokungalungelelaniswa okanye nokunganceli. Imodeli isalandela imiyalelo yaye isahlonipha umyalelo wenkqubo. Ukuba ufuna yale iindidi ezithile kubasebenzisi bakho, tsho apho — loo myalelo ngoku ngowakho ukuba uwubhale endaweni yokuba ube ngowethu ukuba siwunyanzelise.

08Izakhono nemida enyanisekileyo

Izakhono ezimbini zithwala uninzi lomthwalo kumsebenzi womthamo. Imveliso engqongqo ye-json_schema iguqula isigqibo sibe ngumqolo wovimba wedatha ngaphandle komaleko wokwahlula nangaphandle kwesebe lokwala. Ukubiza izixhobo kuzo zontathu iilwimi kwenza i-Flash ibe yinjini enengqiqo kumanyathelo asezantsi atshiphu emeli apho umcwangcisi wenqanaba eliphezulu eqhuba kwimodeli enamandla ngakumbi. Yongeza i-reasoning_effort, ekuvumela ukuba uchithe iitoken ezongezelelweyo kwisiqingatha somsinga esizidingayo kuphela, kunye nomxholo weetoken ezingama-262,144 ofana nowe-Pro — awunikezeli ngomxholo ngokukhetha inqanaba elitshiphu, into engaqhelekanga.

Imida ithe ngqo ngokulinganayo:

• Akukho mbono. I-Flash ngumbhalo kuphela kwaye iya kuzala iinxalenye zemifanekiso kumyalezo. Ngemifanekiso kwimodeli engacinezelwanga kumgangatho onye osezantsi we-$0.50 / $2.00, i-MiniMax-M3 ne-MiMo-V2.5 zizo ezinombono; i-Kimi-K2.6 ne-Kimi-K3 ziimodeli zombono ezinamandla ngakumbi ngaphezu kwelo nqanaba.
• Ayikho phezulu kwiladi. Amanani e-DeepSeek abeka i-Pro phambili kuwo wonke ubalo-mgangatho lwe-agentic olupapashiweyo, umsantsa ubanzi kakhulu kukuqiqa kwekhowudi okuqhubekayo kwamanyathelo amaninzi. Apho impendulo enye engachanekanga ibiza ngaphezu kweziliwaka ezitshiphu, chitha i-$1.45 eyongezelelweyo kwitoken enye yezigidi kwi-DeepSeek-V4-Pro.
• Iitoken ezingama-16,384 eziphumayo kwisicelo ngasinye. Ukuvelisa okude kufuneka kwahlulwe kwimibizo. Lolo phahla lunye kuyo yonke imodeli esiyihambisayo, kwaye lubopha kudala phambi kokuba ifestile yomxholo yenze njalo.

09Ukuyibiza

Yalathisa nawuphi na umthengi ohambelana ne-OpenAI kwiSango uze utshintshe umtya wemodeli. Akukho nto ingaphezulu kwisitaki sakho ekufuneka ishukume.

curl https://api.shannon-ai.com/v1/chat/completions \
  -H "Authorization: Bearer $SHANNON_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "DeepSeek-V4-Flash-0731-W4A16-AUTOROUND-REAP",
    "messages": [
      {"role": "system", "content": "Label the ticket. Reply only with the schema."},
      {"role": "user", "content": "The invoice PDF renders blank on Safari 18."}
    ],
    "response_format": {
      "type": "json_schema",
      "json_schema": {
        "name": "ticket_label",
        "schema": {
          "type": "object",
          "properties": {
            "category": {"type": "string"},
            "severity": {"type": "integer"},
            "needs_human": {"type": "boolean"}
          },
          "required": ["category", "severity", "needs_human"],
          "additionalProperties": false
        }
      }
    }
  }'

Isazisi semodeli esinye sisebenza singatshintshanga kwi-/v1/messages nakwi-/v1/responses, nto leyo eyeyona ndlela ikhawulezayo yokuvavanya imodeli etshiphu phantsi kodibaniso olukhoyo ngaphandle kokubhala kwakhona umthengi wakho. Iiparamitha, imilo yeziganeko zokusasaza, izikimu zokubiza izixhobo nemida yamaxesha zibhalwe kwi-referensi ye-API; yonke imodeli kwikhathalogu idweliswe kwi-Shannon Research.

10Imibuzo ebuzwa rhoqo

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Imithombo: DeepSeek-V2 (arXiv 2405.04434) · DeepSeekMoE (arXiv 2401.06066) · DeepSeek-V3 Technical Report (arXiv 2412.19437) · DeepSeek-V4 (arXiv 2606.19348) · Izikhokelo zeeModeli ze-DeepSeek-V4-Flash-0731 ne-DeepSeek-V4-Pro-0813 · AutoRound (arXiv 2309.05516, Intel) · REAP (arXiv 2510.13999, Cerebras Systems) · AWQ (arXiv 2306.00978) · GPTQ (arXiv 2210.17323). Onke amanani esiseko nawobalo-mgangatho anjengoko apapashwe ngababhali bawo; amaxabiso e-Shannon AI nomxholo ohanjiswayo ngamaxabiso ethu oluhlu ngokwaSeptemba 2026.