I-API ye-GLM engacinezelwanga: elona xabiso lilungileyo ngetoken

Uninzi lothelekiso "lweyona modeli itshiphu" alunyanisekanga, kuba ukhetho olutshiphu ngokuqhelekileyo yimodeli encinci enxibe ubuchule bokuthengisa bemodeli enkulu. Ayikuko oko kwenzekayo apha. I-GLM-5.2 sesinye sezona ziseko zinkulu zobunzima obuvulekileyo ezikhe zakhutshwa ngumntu, kwaye nge-$0.73 engenayo / $2.34 ephumayo ihleli inqanaba elinye phezu komgangatho wekhathalogu yethu ngoxa iphethe isiseko esiphindwe kaninzi ubungakanani baloo mgangatho udla ngokuthenga. Loo mahluko — imodeli enkulu, ixabiso elikufuphi nomgangatho — sisizathu esenza eli phepha libekho.

01Ivela phi i-GLM: iTsinghua, ukugcwalisa izikhewu, notshintsho olunzima olujolise kwii-agent

I-GLM ayilulo uhlobo lwe-Llama olunikwe elinye igama. Lolunye lweentsapho ezimbalwa zeemodeli ezinenjongo yazo yoqeqesho lwangaphambili, ephindwaphindwe iminyaka emihlanu liqela lophando elinye. Igama limele i-General Language Model, kwaye iphepha lokusekwa — GLM: General Language Model Pretraining with Autoregressive Blank Infilling, ACL 2022 — lacebisa ukhetho lwesithathu ecaleni kokumodelwa kolwimi olugqunyiweyo kwe-BERT kunye ne-autoregression eqinileyo esuka ekhohlo isiya ekunene ye-GPT. I-GLM icima izithuba ezilandelelanayo ize izivelise ngokutsha nge-autoregression ngolandelelwano oluxutyiweyo, ngeekhowudi zendawo ezimbaxa-mbini ezilandela zombini indawo yetoken kuxwebhu olonakalisiweyo nendawo yayo ngaphakathi kwesithuba esigcwaliswayo: uyilo olunye oluphatha ukuqonda nokuvelisa ngokulinganayo.

Iqela elingasemva kwayo yayiliKnowledge Engineering Group leTsinghua University, elazala inkampani eyaziwa ngoku ngokuba yi-Z.ai (ngaphambili yayiyiZhipu AI). Umsebenzi wayo wokuqala ophambili yayiyi-GLM-130B ngo-Oktobha 2022 — imodeli eshinyeneyo yeelwimi ezimbini isiNgesi/isiTshayina yeeparamitha ezilikhulu elinamashumi amathathu ezibhiliyoni, ubunzima nekhowudi kukhutshelwe esidlangalaleni ngexesha lokupapashwa. Ukukhutshwa okuvulekileyo yindlela yendlu ukususela ngoko.

Ixesha le-MoE, kunye nokujika kuye kwii-agent

Umgca odlulayo ubaluleke ngaphezu kokukhutshwa okunye. Ukususela kwi-GLM-4.5, inguqulelo nganye iphuculelwe into enye: ukuhlala ihambelana kumashumi eziko lokubizwa kwezixhobo. Leyo yinjongo eyahlukileyo ekwandiseni amanqaku obalo-mgangatho omjikelo omnye, kwaye ivela njengeempikiswano zezixhobo ezonakeleyo ezimbalwa, ukuphambuka okuncinci kwisicwangciso eside, nokuncipha kwendlela ethi "iqalisa ngokutsha umsebenzi ngokuzithemba kumjikelo we-14" eyenza izakhelo ze-agent zibize.

02Iyintoni i-GLM-5.2, kwaye yalinganiselwa kutheni

I-Z.ai ipapasha amanani obalo-mgangatho e-GLM-5.2 kuvimba we-GLM-5. Mabini adibana nomsebenzi we-agentic wokwenene endaweni yokukhumbula izinto ezingabalulekanga:

Terminal-Bench 2.1 — imisebenzi ye-agent yomgca womyalelo yexesha elide. Ixelwe yi-Z.ai.

SWE-bench Pro — ukusonjululwa kwemiba yovimba wekhowudi wokwenene. Ixelwe yi-Z.ai; i-GLM-5.1 yafumana ama-58.4 kuvavanyo olunye.

Lawo ngamanani elebhu, ingengawethu, kwaye achaza isiseko esingacinezelwanga. Amisela udidi lwemodeli ojongene nayo, ingekuko isiqinisekiso.

Inqaku elinye lidata lixabiseke ngaphezu kobalo-mgangatho, kuba livela kumvavanyi ongenasizathu sokuncoma imodeli. NgoJulayi 2026 iCenter for AI Standards and Innovation ye-US National Institute of Standards and Technology yavavanya i-GLM-5.2 yaza yagqiba kwelokuba mhlawumbi yayiyeyona modeli ye-AI yobunzima obuvulekileyo inamandla efumanekayo ngexesha yakhutshwa ngalo, inamandla ewonke athelekiswa nawe-GPT-5.2 namandla e-cyber athelekiswa nawe-Claude Opus 4.6. Uvavanyo olufanayo lwaqaphela ukuba i-GLM-5.2 ivalela izicelo ezinobuethe-ethe ezimbalwa kuneemodeli zesalathiso zase-US, nokuba izikhuseli ezibhakwe kubunzima obuvulekileyo zinokujikelezwa xa obo bunzima busingathwa ngokuzimeleyo. Icandelo lesi-05 libuyela kuloo nto.

03Ithetha ntoni i-"3BIT-REAP", kwaye ikuxabisa ntoni

I-REAP: ukuthena iingcali endaweni yokuzidibanisa

Imodeli ye-MoE yeeparamitha ezingama-744B ineengcali ezingama-256 kumaleko ngamnye, ezisibhozo kuzo ezidubulayo kuyo nayiphi na itoken. Irawuta ayiwusasazi umsebenzi ngokulinganayo — ezinye iingcali zibethwa rhoqo, kwaye umsila omde ubethwa kanqabe yaye unegalelo elincinci xa ubethwa. I-REAP (Router-weighted Expert Activation Pruning), evela kwi-Cerebras Research yaye yamkelwa kwi-ICLR 2026, isebenzisa oko: ivavanya ingcali nganye ngomlinganiselo wokuqaqamba odibanisa ukuba irawuta iyivula ngamandla angakanani nangokufuthi kangakanani kunye nobukhulu begalelo lemveliso yayo, ize icime abo banamanqaku asezantsi ngokusisigxina.

Inxalenye enomdla luthelekiso i-REAP eliphumelelayo. Enye indlela ecacileyo endaweni yokususa ingcali kukuyidibanisa kwesindayo, into evakala ikhuselekile ngakumbi. Okufunyanwe leli phepha kwiimodeli ze-MoE ukusuka kwiiparamitha ezingama-20B ukuya kwi-1T kukuba ukudibanisa kubi ngokwenene kumsebenzi wokuvelisa, yaye ukuthena kubambelela ngokumangalisayo: kuphantse kungalahleki kubalo-mgangatho lokuvelisa ikhowudi nolokubiza izixhobo nasemva kokususa isiqingatha seengcali, kwiziseko ezibandakanya i-Qwen3-Coder-480B ne-Kimi-K2. Ikhowudi nokubiza izixhobo okusinda kungonakalanga kuyiyo kanye into ofuna ukuyigcina kwimodeli esizathu sayo sokubakho bubunjineli be-agentic.

Ubunzima obuyi-3-bit, kunye nomahluko onyanisekileyo

Ngaphezu kokuthena, ubunzima obusindayo bugcinwa kwiibhithi ezintathu — bunamandla ngaphezu kwamanqanaba e-W4A16-AUTOROUND-REAP ne-W8A16 kwenye indawo kwikhathalogu yethu, yaye agcinelwe ezona ziseko zinkulu, apho kungekho enye indlela yokufaka imodeli yeeparamitha ezisithathu kwezine zesithriliyoni kwinodi yenkonzo kwaye ugcine iitoken zihamba ngesantya esisebenzisekayo.

Ukucinezela akusimahla. Eyona ngcinga ichanekileyo: ukuthena nokucutha kwehlisa umsila omde kuqala. Ukuziphatha okushinyeneyo, okusetyenziswa rhoqo — ukulandela imiyalelo, ubume bekhowudi, ukumiselwa kokubizwa kwezixhobo, ukucwangcisa kwamanyathelo amaninzi — kusinda kakuhle, ekuyiyo kanye into eboniswa ziziphumo ze-REAP. Ukukhunjulwa kweenyani ezingaqhelekanga, iilwimi ezinqabileyo nezinto ezingabalulekanga zamacandelo athile kulapho kufuneka ulindele khona umahluko xa uthelekisa ne-GLM-5.2 engacinezelwanga. Ukuba umsebenzi wakho ngu "yazi inyaniso engaqhelekanga ngokupheleleyo", hlawulela inqanaba elithembeke ngakumbi. Ukuba ngu "qhuba isicwangciso kumaziko okubiza izixhobo angamashumi amane ungaphambuki", eli linqanaba indlela eyayilelwe lona.

04Ityala lexabiso: ixabisa ntoni ngokwenene ukuqhuba i-API ye-LLM engacinezelwanga etshiphu

Ixabiso loluhlu lwe-API elipapashwe yi-Z.ai ngokwayo le-GLM-5.2 ngu-$1.40 kwitoken enye yezigidi ezingenayo kunye ne-$4.40 kwitoken enye yezigidi eziphumayo. Ixabiso lethu kwisiseko esinye ngu-$0.73 / $2.34 — malunga nama-48% ngaphantsi kwezingenayo nama-47% ngaphantsi kwezimayo. Elo cutho yiloo nto ukucinezela okuyithengayo, kwaye kuza nento yesibini ongenako ukuyithenga kwindlu yokuqala nangaliphi na ixabiso: akukho maleko wokwala.

Kwikhathalogu yethu, ixabiso elidibeneyo lelona nani libalulekileyo. Nali kumlinganiselo we-3:1 wezingenayo kwezimayo, malunga nendlela i-agent yokubiza izixhobo ekhangeleka ngayo ekusebenzeni — umxholo omninzi neziphumo zezixhobo ezingenayo, iitoken ezimbalwa ngokuthelekisa eziphumayo.

Imodeli	Engenayo / 1M	Ephumayo / 1M	Edibeneyo 3:1	Umbono
GLM-5.2 · 3BIT-REAP	$0.73	$2.34	$1.13	Hayi
Nemotron3Ultra · 3BIT-REAP	$0.75	$3.30	$1.39	Hayi
Kimi-K2.6 · W4A16-AUTOROUND-REAP	$0.78	$3.67	$1.50	Ewe
DeepSeek-V4-Pro-0813 · 3BIT-REAP	$1.95	$3.90	$2.44	Hayi
inkling · W4A16-AUTOROUND-REAP	$1.42	$6.07	$2.58	Ewe
Kimi-K3 · 3BIT-REAP	$3.83	$19.12	$7.65	Ewe

Iimodeli ezithandathu zihleli kumgangatho we-$0.50 / $2.00 — i-MiniMax-M3, i-DeepSeek-V4-Flash, i-Laguna-S-2.1, i-MiMo-V2.5, i-MiMo-V2.5-Pro ne-Hy3 — umlinganiselo odibeneyo we-$0.875. I-GLM-5.2 ingama-29% ngaphezu kwaloo mgangatho yaye ikuthengela isiseko sodidi lwe-744B esinotyalo-mali oluzinzileyo kwindlela ye-agentic ngasemva kwaso. Yonke into exabiso lingaphezulu kwayo ixabisa okungenani ama-23% ngaphezulu ngokudibeneyo, kwaye i-Kimi-K3 ixabisa izihlandlo eziyi-6.8 ngaphezulu. Ingxoxo yexabiso ikumqolo omnye: eyona ndawo itshiphu kwikhathalogu yokuthenga isiseko se-agentic senqanaba eliphezulu.

Kuguqulelwe kumsebenzi

• Ukuzaliswa komxholo kanye — iitoken ezingama-262,144 ezingenayo: $0.19. Uvimba wekhowudi omkhulu wonke ufundwe wangena efestileni ngaphantsi kweesenti ezingamashumi amabini.
• Ukugqitywa okunye kobude obuphezulu — iitoken ezingama-16,384 eziphumayo: $0.038.
• Umjikelo omnye we-agent — ezingama-20K ezingenayo, ezingama-2K eziphumayo: $0.019. Umjikelo omnye uxabisa $0.115 kwi-Kimi-K3 kunye ne-$0.047 kwi-DeepSeek-V4-Pro.
• Imijikelo elikhulu ye-agent: $1.93, xa kuthelekiswa ne-$11.48 kweyona modeli ibiza kakhulu kwikhathalogu.

Imisebenzi ye-agentic izele zizingenayo, kwaye ithuba le-GLM likhulu kanye apho: ixabiso layo lezingenayo lisezantsi ngezihlandlo ezi-5.2 kunelo le-Kimi-K3 nangezihlandlo ezi-2.7 kunelo le-DeepSeek-V4-Pro. Ukuba i-agent yakho ithumela kwakhona incoko ekhulayo kumjikelo ngamnye — yaye phantse zonke ii-agent ziyenza loo nto — loo mphindi yiyo ephelela kwityala lakho.

05Kuthetha ntoni "ukungacinezelwa" kule ndidi

Zizinto ezimbini, ngokuchanekileyo: akukho maleko wokwala — akukho sahluli-ndidi sigqiba ukuba zeziphi izicelo imodeli evunyelwe ukuzibona, kwaye akukho modeli yomgaqo-nkqubo ebhala ngokutsha umyalelo wakho phambi kokuba ufike — kunye nokungabikho kokuhluzwa kwemveliso, oko kuthetha ukuba iitoken imodeli eziveliswayo ziitoken ozifumanayo, zingacinywanga zingatshintshwanga.

Leyo yinto eyahlukileyo kwi-API yezorhwebo ebhengeza indlela "ekhululekileyo" okanye "yomphuhlisi". Ezo zisathumela umsinga ngomfumba womgaqo-nkqubo womthengisi; okutshintshayo ngumlinganiselo, ingekuko ubukho besango. Apha akukho sango lokulungiswa — imodeli iqhuba kwiqoqo lethu leeGPU, kwaye indlela eziphatha ngayo yindlela yesiseko. Funda okufunyanwe yi-NIST CAISI kwicandelo lesi-02 njengenkcazelo yobuchwepheshe endaweni yesilumkiso yaye kuyayichaza imveliso: imodeli enokulungelelaniswa okuhlala kubunzima bayo, ehanjiswa ngaphandle komaleko wangaphandle womgaqo-nkqubo, iziphatha ngokobunzima bayo.

Kutheni oku kubalulekile kwii-agent ngokukodwa

Ukwala kudla ngokuxutyushwa njengombuzo wesiqulatho. Kumsebenzi we-agentic ngumbuzo wokuthembeka ubukhulu becala. Ukwala kumjikelo we-31 wokubaleka kwemijikelo engama-40 akulokwala ngobubele okufundayo uze udlule — sisinyathelo esonakeleyo, ngumlungelelanisi ongazi ukuba maqhubeke njani, sisicwangciso esaphukileyo, kunye nemijikelo engama-30 yeetoken ezisetyenzisiweyo ngaphandle kwento onokuyibonisa. Uphando lokhuseleko, uhlalutyo lwe-malware, uvavanyo lokungena, i-red-teaming, intsomi yabantu abadala, ukubhalwa kwezonyango nezomthetho, nokuveliswa kwedatha yoqeqesho lokhuseleko konke kubetha oku rhoqo, kwaye ukusilela kubiza kanye kuba kufika emva kwexesha.

Elinye icala lelokuba umaleko womgaqo-nkqubo ngoku ngowakho. Ukusetyenziswa kweSango le-Shannon AI kulawulwa yiPolisi yethu yoSetyenziso Olunoxanduva; ukususa isigwebo somthengisi kwisangqa kuthetha ukunikela ngesakho.

06Ikunika ntoni ngokwenene le ndidi

Isakhono	GLM-5.2 · 3BIT-REAP
Isazisi semodeli	GLM-5.2-3BIT-REAP
Ifestile yomxholo	262,144 iitoken
Imveliso ephezulu kwisicelo ngasinye	16,384 iitoken
Ukusasaza	Ewe
Ukubiza izixhobo	Ewe
Ukuqiqa / reasoning_effort	Ewe
JSON Schema (json_schema)	Ewe
response_format	Ewe
Umbono / ugalelo lomfanekiso	Hayi — ngumbhalo kuphela
Umaleko wokwala / ukuhluzwa kwemveliso	Akukho

Funda umqolo wombono ngononophelo phambi kokuba wakhe. I-GLM-5.2 ngumbhalo kuphela kwisango lethu. Ukuba ufuna ugalelo lomfanekiso, ikhathalogu inokhetho olusihlanu olunombono — i-MiniMax-M3 ne-MiMo-V2.5 kumgangatho we-$0.50 / $2.00, i-Kimi-K2.6 nge-$0.78 / $3.67, i-inkling nge-$1.42 / $6.07, kunye ne-Kimi-K3 nge-$3.83 / $19.12. Ipatheni enengqiqo kukuthumela ukuqonda umfanekiso kwi-MiniMax-M3 kunye nayo yonke enye into kwi-GLM-5.2, into engabizi nto ngaphandle komtya wemodeli.

Iilwimi ezintathu, imodeli enye

Imodeli enye ifikeleleka ngeendlela ezintathu zezicelo, zonke zisasaza: i-/v1/chat/completions (ulwimi lwe-OpenAI), i-/v1/messages (ulwimi lwe-Anthropic), kunye ne-/v1/responses. Akukho nto itshintshayo ngemodeli phakathi kwazo — khetha nayiphi na esele ithethwa yi-SDK yakho, kwaye udla ngokuba kutshintsho olunye lwe-URL yesiseko ukusuka ekusebenzeni.

# OpenAI dialect — point your existing client at the gateway
from openai import OpenAI

client = OpenAI(
    base_url="https://api.shannon-ai.com/v1",
    api_key="sk-...",
)

resp = client.chat.completions.create(
    model="GLM-5.2-3BIT-REAP",
    messages=[{"role": "user", "content": "..."}],
    tools=tools,                 # tool calling supported
    reasoning_effort="medium", # low | medium | high
    stream=True,
)

Iiskimu ezipheleleyo zesicelo nempendulo zazo zontathu iilwimi, ubume bokubiza izixhobo, iimilo zeziganeko zokusasaza, kunye nebala lokudlala elinonxibelelwano zikwamaxwebheni e-API e-Shannon AI.

07Xa ufanele ukukhetha i-GLM-5.2 — naxa ungafanelanga

Yikhethe xa

• Uqhuba ii-agent. Izangqa ezide zokubiza izixhobo kuko oku kumnombo owakhelwe kona waza waqeqeshelwa emva kokuqeqeshwa ngokuphindaphindiweyo, kwaye ixabiso lezingenayo lenza incoko ekhulayo ifaneleke ukuthunyelwa kwakhona kumjikelo ngamnye.
• Usebenza kuvimba wekhowudi omkhulu. Umxholo we-262K, ukumiselwa kokubizwa kwezixhobo okuthembekileyo, kunye ne-$0.19 yokufunda yonke ifestile.
• Umthamo ngumda wakho. Ukwahlula ngeendidi, ukukhupha, ukuveliswa kwedatha eyenziweyo, ukubhala ngokutsha ngobuninzi — nantoni na apho ixabiso lombizo ngamnye liphindwe linani elikhulu ligqiba ukuba iprojekthi iyasebenzeka na.
• Ukwala kophula umgca wakho wokusebenza. Uphando lokhuseleko, uvavanyo lokuchasa, intsomi engacinezelwanga, ukubhala okunobuethe-ethe — indlela yokusilela ayikho apha.

Khetha enye into xa

• Ufuna umbono. Ngumbhalo kuphela. Bona ukhetho olunombono olungasentla.
• Ufuna ukuqiqa okunzulu kakhulu komjikelo omnye. Kwezona ngxaki zinzima zohlalutyo lomjikelo omnye, i-DeepSeek-V4-Pro-0813 · 3BIT-REAP sisixhobo esinzima ngakumbi kwixabiso elidibeneyo eliphindwe kabini nesiqingatha — kwimibizo apho uphahla lungumda, olo lolona thelekiso lulungileyo.
• Ufuna ukuthembeka okuphezulu kulwazi olungaqhelekanga. Inqanaba le-W8A16 — i-MiMo-V2.5-Pro ne-Hy3 — licinezelwe kancinci kakhulu yaye lihleli kumgangatho we-$0.50 / $2.00, kwiziseko ezincinci.

Amanani obalo-mgangatho e-GLM-5.2 (Terminal-Bench 2.1, SWE-bench Pro) axelwe yi-Z.ai ngesiseko esingacinezelwanga; ukuphindwa okuzimeleyo kusalindile. Amanani e-Claude Opus 4.8 nawe-GPT-5.5 aboniswa ngenjongo yesalathiso kuphela. Amaxabiso oluhlu lwe-API ye-GLM-5.2 endlu yokuqala njengoko epapashwe yi-Z.ai, Septemba 2026.

08Imibuzo ebuzwa rhoqo

---

Imithombo: Uvimba we-Z.ai GLM-5 · Du et al., GLM: General Language Model Pretraining with Autoregressive Blank Infilling, ACL 2022 · Zeng et al., GLM-130B: An Open Bilingual Pre-trained Model · Lasby et al., REAP the Experts: Why Pruning Prevails for One-Shot MoE Compression, ICLR 2026 · Uvavanyo lwe-NIST CAISI lwe-GLM-5.2 ye-Z.ai, Julayi 2026. Amanqaku obalo-mgangatho esiseko axelwe lilebhu yaye asexeshana; achaza i-GLM-5.2 engacinezelwanga, ingekuko esi sakhiwo sicinezelweyo. Amanani exabiso, omxholo nawesakhono ngamaxabiso ekhathalogu ye-Shannon AI njengoko kunjalo nge-5 Septemba 2026.