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a GLM 5.3: cos’è, caratteristiche e come utilizzarlo al meglio","\u003Ch1>\u003Cspan data-sheets-root=\"1\">\u003Cstrong>Guida a \u003Cspan class=\"text-color-primary-400\">GLM 5.3:\u003C/span> cos’è, caratteristiche e come utilizzarlo al meglio\u003C/strong>\u003Cbr />\n\u003C/span>\u003C/h1>\n","GLM 5.3 è un modello AI di Z.ai pensato per la programmazione e per attività che richiedono più passaggi, come analizzare un progetto software, proporre modifiche e verificarne il risultato. Puoi usarlo attraverso un servizio API oppure scaricarne i pesi ed eseguirlo su un’infrastruttura adeguata. La scelta dipende dal lavoro che vuoi svolgere. Correggere una […]",29896,"21 Ottobre 2026",{"url":904,"width":905,"height":905,"alt":21},"https://website-prod.datamasters.it/wp-content/uploads/2026/10/cover-16.png",1254,[907,911,935,937],{"block_layout":908,"classes":909,"text":910},"simple_text","above-the-fold","\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\" style=\"font-weight: 400;\">GLM 5.3 è un modello AI di Z.ai pensato per la programmazione e per attività che richiedono più passaggi, come analizzare un progetto software, proporre modifiche e verificarne il risultato. Puoi usarlo attraverso un servizio API oppure scaricarne i pesi ed eseguirlo su un’infrastruttura adeguata.\u003C/span>\u003C/p>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\" style=\"font-weight: 400;\">La scelta dipende dal lavoro che vuoi svolgere. Correggere una funzione, interpretare uno screenshot e automatizzare una procedura richiedono capacità diverse. Anche all’interno della famiglia GLM 5.3 cambiano modalità di input, licenza e requisiti di esecuzione.\u003C/span>\u003C/p>\n\u003Ch2>\u003Cstrong>Che cos’è GLM 5.3\u003C/strong>\u003C/h2>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cb>GLM-5.3\u003C/b>\u003Cspan style=\"font-weight: 400;\"> appartiene alla famiglia di modelli linguistici di\u003C/span>\u003Cb> Z.ai\u003C/b>\u003Cspan style=\"font-weight: 400;\"> (conosciuta anche come Zhipu AI) che lo presenta come un modello orientato al software engineering ed alle attività agentiche.\u003C/span>\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>GLM 5.3 e GLM 5.3 Flash\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cb>GLM-5.3-Flash\u003C/b>\u003Cspan style=\"font-weight: 400;\"> ha una base e un’architettura proprie. La \u003C/span>\u003Ca href=\"https://docs.z.ai/guides/vlm/glm-5.3-flash\" target=\"_blank\" rel=\"noopener\">\u003Cspan style=\"font-weight: 400;\">documentazione di Flash\u003C/span>\u003C/a>\u003Cspan style=\"font-weight: 400;\"> descrive input testuali, immagini, video e file, mentre il modello principale accetta input testuali.\u003C/span>\u003C/span>\u003C/p>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\" style=\"font-weight: 400;\">Come consiglio, per una revisione basata su codice e log si potrebbe valutare il modello principale, se il compito comprende la lettura di screenshot o interfacce, verifica le capacità multimodali di Flash.\u003C/span>\u003C/p>\n\u003Ch2>\u003Cstrong>Come funziona GLM 5.3\u003C/strong>\u003C/h2>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">La \u003C/span>\u003Ca href=\"https://huggingface.co/zai-org/GLM-5.3\" target=\"_blank\" rel=\"noopener\">\u003Cspan style=\"font-weight: 400;\">model card ufficiale\u003C/span>\u003C/a>\u003Cspan style=\"font-weight: 400;\"> indica che GLM-5.3 mantiene la base di GLM-5.2 e concentra i miglioramenti nel \u003C/span>\u003Cb>post-training\u003C/b>\u003Cspan style=\"font-weight: 400;\">, l’addestramento successivo alla costruzione del modello di base.\u003C/span>\u003C/span>\u003C/p>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\" style=\"font-weight: 400;\">Durante l’utilizzo, il modello elabora il contesto disponibile e genera testo o richieste di chiamata agli strumenti. Nel lavoro su un repository puoi immaginarlo come una persona alla quale consegni un fascicolo e un insieme di strumenti autorizzati. Il fascicolo contiene codice, istruzioni e risultati precedenti; l’applicazione controlla quali strumenti può usare.\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>GLM 5.3 è davvero open source?\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">Per GLM 5.3 la definizione \u003C/span>\u003Cb>open weights\u003C/b>\u003Cspan style=\"font-weight: 400;\"> è più precisa dell’etichetta generica “open source”. I pesi, cioè i parametri appresi durante l’addestramento, sono scaricabili, ma il loro utilizzo resta soggetto alla licenza GLM-5.3.\u003C/span>\u003C/span>\u003C/p>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">Il testo permette uso, modifica e distribuzione a determinate condizioni e prevede una revisione di sicurezza per alcuni grandi operatori Model-as-a-Service. La \u003C/span>\u003Ca href=\"https://huggingface.co/zai-org/GLM-5.3-Flash\" target=\"_blank\" rel=\"noopener\">\u003Cspan style=\"font-weight: 400;\">model card di Flash\u003C/span>\u003C/a>\u003Cspan style=\"font-weight: 400;\"> riporta invece la licenza MIT, prima di pianificarne l’integrazione o la distribuzione di uno dei due modelli ti consigliamo di controllare la licenza del checkpoint scelto.\u003C/span>\u003C/span>\u003C/p>\n\u003Ch2>\u003Cstrong>Le principali caratteristiche di GLM 5.3\u003C/strong>\u003C/h2>\n\u003Ch3>\u003Cstrong>Capacità di coding\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">Z.ai pubblica valutazioni su terminale, modifica di repository e altri compiti software. Su Terminal-Bench 3.0 la model card riporta \u003C/span>\u003Cb>28,3 per GLM-5.3 contro 4,6 per GLM-5.2\u003C/b>\u003Cspan style=\"font-weight: 400;\">. Sono risultati dichiarati dal produttore, accompagnati dalle condizioni di esecuzione. \u003C/span>\u003Ca href=\"https://huggingface.co/zai-org/GLM-5.3\" target=\"_blank\" rel=\"noopener\">\u003Cspan style=\"font-weight: 400;\">Risultati e note metodologiche\u003C/span>\u003C/a>\u003Cspan style=\"font-weight: 400;\">.\u003C/span>\u003C/span>\u003C/p>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\" style=\"font-weight: 400;\">Per stimare il beneficio nel tuo progetto, confronta le correzioni prodotte, i test superati e il tempo necessario per revisionare le modifiche.\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>Ragionamento su problemi complessi\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">Il modello mantiene il ragionamento abilitato e permette di scegliere tra i livelli \u003C/span>\u003Cspan style=\"font-weight: 400;\">low\u003C/span>\u003Cspan style=\"font-weight: 400;\">, \u003C/span>\u003Cspan style=\"font-weight: 400;\">high\u003C/span>\u003Cspan style=\"font-weight: 400;\"> e \u003C/span>\u003Cspan style=\"font-weight: 400;\">max\u003C/span>\u003Cspan style=\"font-weight: 400;\"> tramite \u003C/span>\u003Cspan style=\"font-weight: 400;\">reasoning_effort\u003C/span>\u003Cspan style=\"font-weight: 400;\">. Puoi quindi variare il budget di ragionamento in funzione del compito, una spiegazione più lunga va comunque verificata rispetto ai requisiti e ai dati disponibili.\u003C/span>\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>Gestione di attività a lungo orizzonte\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">La documentazione dichiara una \u003C/span>\u003Cb>finestra di contesto di un milione di token\u003C/b>\u003Cspan style=\"font-weight: 400;\"> e un output massimo di 128K token. I token sono le unità in cui viene rappresentato il testo. Puoi fornire materiale esteso, ma la capienza non garantisce che ogni dettaglio venga recuperato e interpretato correttamente. \u003C/span>\u003Ca href=\"https://docs.z.ai/guides/llm/glm-5.3\" target=\"_blank\" rel=\"noopener\">\u003Cspan style=\"font-weight: 400;\">Specifiche del modello\u003C/span>\u003C/a>\u003Cspan style=\"font-weight: 400;\">.\u003C/span>\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>Utilizzo di strumenti e applicazioni\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">Il \u003C/span>\u003Cb>function calling\u003C/b>\u003Cspan style=\"font-weight: 400;\">, chiamato anche tool calling, consente al modello di richiedere l’esecuzione di funzioni esterne. Una funzione potrebbe leggere l’esito di una pipeline o recuperare un documento, l’applicazione deve validare la richiesta, eseguire l’operazione e restituire il risultato.\u003C/span>\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>Supporto a workflow automatizzati\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\" style=\"font-weight: 400;\">Per automatizzare una procedura servono anche regole di esecuzione, gestione degli errori e criteri di completamento. In un flusso di analisi dei log, per esempio, puoi far proporre al modello una classificazione e affidare a codice deterministico la validazione dei campi e l’instradamento del risultato.\u003C/span>\u003C/p>\n\u003Cp>\u003Cimg fetchpriority=\"high\" decoding=\"async\" class=\"\" src=\"https://website-prod.datamasters.it/wp-content/uploads/2026/10/inline-01-22.png\" alt=\"glm 5.3\" width=\"830\" height=\"553\" />\u003C/p>\n",{"block_layout":912,"gutter_top":913,"gutter_bottom":913,"list":914,"h_align":934,"v_align":934},"cta_list","xl",[915],{"link":916,"config":918,"modal":922},{"title":917,"url":148,"target":21},"ISCRIVITI ALLA NEWSLETTER",{"variant":160,"theme":919,"size":920,"class":921},"theme-primary","size-default","iscritto-nl qs-link",{"api_url":923,"title":924,"text":925,"name_label":926,"name_placeholder":927,"surname_label":928,"surname_placeholder":929,"email_label":930,"email_placeholder":931,"privacy_text":932,"submit_text":933},"/wp-json/dm/v1/modal-form/26876","Iscriviti alla Newletter","\u003Cp>Ricevi direttamente sulla tua mail gli ultimi articoli pubblicati nella nostra sezione AI NEWS per rimanere sempre aggiornato e non perderti nessun contenuto.\u003C/p>\n","Nome","Inserisci il tuo nome","Cognome","Inserisci il tuo cognome","E-mail","Inserisci la tua e-mail","Dichiaro di aver letto l’informativa \u003Ca href=\"https://datamasters.it/privacy-policy/\" target=\"_blank\" rel=\"noopener\">privacy\u003C/a> e di prestare espresso consenso al \u003Ca href=\"https://datamasters.it/trattamento-dati/\" target=\"_blank\" rel=\"noopener\">trattamento dei dati\u003C/a> personali","ISCRIVITI ORA","center",{"block_layout":908,"text":936},"\u003Ch2>\u003Cstrong>Cosa si può fare con GLM 5.3\u003C/strong>\u003C/h2>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">Gli esempi che seguono sono \u003C/span>\u003Cb>prove da costruire sul proprio progetto\u003C/b>\u003Cspan style=\"font-weight: 400;\">, non risultati misurati per questa guida. Per ciascuna attività definisci prima come riconoscere una risposta corretta.\u003C/span>\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>Scrivere e correggere codice\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\" style=\"font-weight: 400;\">Puoi chiedere una funzione a partire da requisiti ed esempi, oppure fornire un errore riproducibile. Per una funzione che gestisce date, specifica formati accettati, fuso orario e comportamento sugli input non validi. Chiedi una modifica circoscritta e controlla che superi i test senza cambiare il contratto della funzione.\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>Analizzare repository e progetti software\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">Un esercizio utile consiste nel ricostruire il percorso di una richiesta, dal punto di ingresso fino all’accesso ai dati. Fornisci i file pertinenti e chiedi riferimenti a percorsi e simboli. La \u003C/span>\u003Cb>tracciabilità delle risposte\u003C/b>\u003Cspan style=\"font-weight: 400;\"> ti permette di controllare la ricostruzione e individuare eventuali informazioni mancanti.\u003C/span>\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>Creare agenti con tool calling\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\" style=\"font-weight: 400;\">Puoi collegare una funzione che restituisce lo stato di un job di prova. Il modello sceglie quando richiamarla; l’applicazione controlla l’identificatore e restituisce dati strutturati. Questo esperimento permette di verificare l’intero ciclo prima di aggiungere funzioni che modificano lo stato di un sistema.\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>Automatizzare attività tecniche ripetitive\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\" style=\"font-weight: 400;\">Prova a trasformare log anonimizzati in una scheda con errore, componente coinvolto ed evidenze. Confronta le schede con casi già classificati e prevedi una gestione esplicita per risposte incomplete o fuori formato. Puoi così misurare quanto lavoro resta a chi revisiona.\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>Analizzare testi e documenti molto lunghi\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\" style=\"font-weight: 400;\">Puoi confrontare specifiche, estrarre requisiti o ricostruire decisioni da documentazione estesa. Con il modello principale prepara il contenuto testuale; se le informazioni dipendono da immagini o pagine scansionate, valuta Flash o una fase preliminare di estrazione. Chiedi riferimenti ai passaggi originali per controllare le conclusioni.\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>Supportare attività di cybersecurity autorizzata\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">La model card include valutazioni sulla ricerca di vulnerabilità. Un impiego difensivo da valutare è la revisione di codice di tua proprietà, con verifica dei rilievi da parte di una persona competente. Mantieni un \u003C/span>\u003Cb>perimetro autorizzato\u003C/b>\u003Cspan style=\"font-weight: 400;\"> e considera ogni segnalazione un’ipotesi da validare. \u003C/span>\u003Ca href=\"https://huggingface.co/zai-org/GLM-5.3\" target=\"_blank\" rel=\"noopener\">\u003Cspan style=\"font-weight: 400;\">Valutazioni pubblicate da Z.ai\u003C/span>\u003C/a>\u003Cspan style=\"font-weight: 400;\">.\u003C/span>\u003C/span>\u003C/p>\n\u003Ch2>\u003Cstrong>Come usare GLM 5.3\u003C/strong>\u003C/h2>\n\u003Ch3>\u003Cstrong>Utilizzare il modello tramite interfaccia web\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\" style=\"font-weight: 400;\">L’interfaccia web di Z.ai  permette di esplorare il servizio senza costruire un’integrazione. Verifica nel tuo account quale versione è disponibile e selezionata. Usa una richiesta con un risultato controllabile, come spiegare una funzione accompagnata da un test fallito.\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>Accedere al modello tramite API\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">Per integrare \u003C/span>\u003Cb>GLM 5.3 tramite API\u003C/b>\u003Cspan style=\"font-weight: 400;\">, è possibile creare una chiave sulla piattaforma di \u003C/span>\u003Ca href=\"http://z.ai\" target=\"_blank\" rel=\"noopener\">\u003Cspan style=\"font-weight: 400;\">Z.ai\u003C/span>\u003C/a>\u003Cspan style=\"font-weight: 400;\">, ti lasciamo di seguito un esempio su come usare l’API standard e la sintassi Bash:\u003C/span>\u003C/span>\u003C/p>\n\u003Cpre>\u003Cspan style=\"font-weight: 400;\">curl https://api.z.ai/api/paas/v4/chat/completions \\\u003C/span>\r\n\r\n\u003Cspan style=\"font-weight: 400;\">  -H \"Content-Type: application/json\" \\\u003C/span>\r\n\r\n\u003Cspan style=\"font-weight: 400;\">  -H \"Authorization: Bearer $ZAI_API_KEY\" \\\u003C/span>\r\n\r\n\u003Cspan style=\"font-weight: 400;\">  -d '{\u003C/span>\r\n\r\n\u003Cspan style=\"font-weight: 400;\">    \"model\": \"glm-5.3\",\u003C/span>\r\n\r\n\u003Cspan style=\"font-weight: 400;\">    \"messages\": [\u003C/span>\r\n\r\n\u003Cspan style=\"font-weight: 400;\">      {\u003C/span>\r\n\r\n\u003Cspan style=\"font-weight: 400;\">        \"role\": \"user\",\u003C/span>\r\n\r\n\u003Cspan style=\"font-weight: 400;\">        \"content\": \"Proponi tre test per una funzione che converte una data ISO in UTC.\"\u003C/span>\r\n\r\n\u003Cspan style=\"font-weight: 400;\">      }\u003C/span>\r\n\r\n\u003Cspan style=\"font-weight: 400;\">    ],\u003C/span>\r\n\r\n\u003Cspan style=\"font-weight: 400;\">    \"thinking\": {\"type\": \"enabled\"},\u003C/span>\r\n\r\n\u003Cspan style=\"font-weight: 400;\">    \"reasoning_effort\": \"low\",\u003C/span>\r\n\r\n\u003Cspan style=\"font-weight: 400;\">    \"max_tokens\": 4096\u003C/span>\r\n\r\n\u003Cspan style=\"font-weight: 400;\">  }'\u003C/span>\u003C/pre>\n\u003Cp> \u003C/p>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">La variabile \u003C/span>\u003Cspan style=\"font-weight: 400;\">ZAI_API_KEY\u003C/span>\u003Cspan style=\"font-weight: 400;\"> deve contenere la tua chiave nell’ambiente di esecuzione. Per il Coding Plan segui le istruzioni dell’endpoint dedicato. Se migri un’integrazione precedente, rimuovi \u003C/span>\u003Cspan style=\"font-weight: 400;\">thinking.type: disabled\u003C/span>\u003Cspan style=\"font-weight: 400;\">, non supportato da GLM-5.3. \u003C/span>\u003Ca href=\"https://docs.z.ai/guides/overview/migrate-to-glm-new\" target=\"_blank\" rel=\"noopener\">\u003Cspan style=\"font-weight: 400;\">Guida alla migrazione\u003C/span>\u003C/a>\u003Cspan style=\"font-weight: 400;\">.\u003C/span>\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>Scaricare i pesi da Hugging Face\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">Per il \u003C/span>\u003Cb>download di GLM 5.3\u003C/b>\u003Cspan style=\"font-weight: 400;\">, parti dal repository ufficiale \u003C/span>\u003Ca href=\"https://huggingface.co/zai-org/GLM-5.3\" target=\"_blank\" rel=\"noopener\">\u003Cspan style=\"font-weight: 400;\">zai-org/GLM-5.3 su Hugging Face\u003C/span>\u003C/a>\u003Cspan style=\"font-weight: 400;\">. Leggi model card, licenza e istruzioni prima di trasferire i file. Annota il checkpoint e la revisione scelti per poter ricostruire la configurazione.\u003C/span>\u003C/span>\u003C/p>\n\u003Ch3>\u003Cstrong>Verificare requisiti hardware, licenza e compatibilità\u003C/strong>\u003C/h3>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\" style=\"font-weight: 400;\">Prima di scaricare ed installare in locale il modello devi considerare memoria dei pesi, contesto e richieste contemporanee. Verifica anche il supporto del formato numerico, del ragionamento e delle chiamate agli strumenti nel runtime scelto. \u003C/span>\u003C/p>\n\u003Cp>\u003Cimg decoding=\"async\" class=\"\" src=\"https://website-prod.datamasters.it/wp-content/uploads/2026/10/inline-02-12.png\" alt=\"glm 5.3\" width=\"830\" height=\"553\" />\u003C/p>\n\u003Ch2>\u003Cstrong>Limiti e aspetti da valutare\u003C/strong>\u003C/h2>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">GLM-5.3 può generare codice errato, ricostruire male una dipendenza o proporre una funzione inesistente. Mantieni \u003C/span>\u003Cb>test e revisione del codice\u003C/b>\u003Cspan style=\"font-weight: 400;\"> nel processo di lavoro. Per le risposte documentali, controlla che i riferimenti sostengano davvero le conclusioni.\u003C/span>\u003C/span>\u003C/p>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\" style=\"font-weight: 400;\">La disponibilità dei pesi comporta anche responsabilità operative. Se esegui il modello in locale, devi gestire risorse, aggiornamenti e disponibilità del servizio, se usi un provider, verifica condizioni di trattamento dei dati, accessi e costi prima di inviare materiale riservato.\u003C/span>\u003C/p>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">Distingui infine i \u003C/span>\u003Cb>limiti del modello da quelli dell’integrazione\u003C/b>\u003Cspan style=\"font-weight: 400;\">. Un errore può dipendere dal contesto incompleto, da un parser delle tool call o da un permesso mancante, conservare richieste, risposte e risultati degli strumenti aiuta a ricostruire la causa.\u003C/span>\u003C/span>\u003C/p>\n\u003Ch2>\u003Cstrong>Come capire se GLM 5.3 è adatto al proprio progetto: i consigli di Data Masters\u003C/strong>\u003C/h2>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">Parti da un \u003C/span>\u003Cb>compito circoscritto\u003C/b>\u003Cspan style=\"font-weight: 400;\">, come correggere un bug coperto da test o estrarre requisiti verificabili da un documento. Prepara esempi rappresentativi, includendo input incompleti e casi che devono produrre una richiesta di chiarimento.\u003C/span>\u003C/span>\u003C/p>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\" style=\"font-weight: 400;\">Confronta il modello con il processo ed altri modelli che usi già. Registra risultati corretti, tentativi falliti, consumi e tempo di revisione. Aggiungi strumenti o amplia il perimetro solo dopo aver capito quali errori ricorrono e come intercettarli.\u003C/span>\u003C/p>\n\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-black\">\u003Cspan style=\"font-weight: 400;\">Per approfondire lo sviluppo di applicazioni e agenti AI, esplora il \u003C/span>\u003Ca href=\"https://datamasters.it/catalogo/percorsi-di-carriera/ai-engineer/\" target=\"_blank\" rel=\"noopener\">\u003Cspan style=\"font-weight: 400;\">Percorso AI engineer\u003C/span>\u003C/a>\u003Cspan style=\"font-weight: 400;\">. Puoi portare nel tuo percorso di studio un \u003C/span>\u003Cb>caso di prova ripetibile\u003C/b>\u003Cspan style=\"font-weight: 400;\"> e usarlo per valutare ogni nuova integrazione.\u003C/span>\u003C/span>\u003C/p>\n",{"block_layout":938,"classes":939,"bg_color":940,"api_url":941,"text":942,"form":943},"newsletter_form","gutter-mt-xl","color-primary-50","/wp-json/dm/v1/newsletter","\u003Ch6>NEWSLETTER\u003C/h6>\n\u003Cp class=\"font-size-body-1\">Ricevi direttamente sulla tua mail gli ultimi articoli pubblicati nella nostra sezione AI NEWS per rimanere sempre aggiornato e non perderti nessun contenuto.\u003C/p>\n",{"name_label":926,"name_placeholder":927,"surname_label":928,"surname_placeholder":929,"email_label":930,"email_placeholder":931,"privacy_text":932,"submit_text":933,"confirm_message":944,"ac_list":945,"ac_tags":946},"Grazie per esserti iscritto alla nostra newsletter!\u003Cbr />\r\nOra riceverai direttamente nella tua casella di posta gli ultimi aggiornamenti dal mondo AI e Data Science per essere sempre al passo con le novità del settore.","44dadf27d2fd2b62:1b54fba0fc625ab277c3dab8d205162db7f0a73c:La6SqOhgWs0KmjURgIp5pw==","88c166e6180bbb7c:3d0dfdb5c07cce782361c3aa2ccde7376869c827:tqKu8HFN2Twc6nWWRmprcA==",{"first_name":948,"last_name":949,"avatar":950,"linkedin_url":965,"description":966},"Giuseppe","Mastrandrea",{"ID":951,"id":951,"title":952,"filename":953,"filesize":954,"url":955,"alt":863,"author":956,"description":21,"caption":21,"name":952,"status":957,"uploaded_to":958,"date":959,"modified":960,"menu_order":961,"mime_type":843,"type":962,"subtype":963,"width":964,"height":964},1328,"giuseppe","giuseppe-1.png",817480,"https://website-prod.datamasters.it/wp-content/uploads/2024/06/giuseppe-1.png","7","inherit",1313,"2024-06-17 13:54:59","2024-06-17 13:56:07",0,"image","png",1080,"https://www.linkedin.com/in/giuseppe-mastrandrea-43008578/","\u003Cp>Giuseppe è un \u003Cstrong>Ingegnere Informatico\u003C/strong> con una forte specializzazione e pubblicazioni in ambito \u003Cstrong>Computer Vision.\u003C/strong> Da circa 8 anni si dedica all’insegnamento in ambito informatico e alla formazione sulle \u003Cstrong>tecnologie emergenti tra le quali il Machine Learning.\u003C/strong>\u003C/p>\n",[968,970],{"label":823,"link":969},"https://datamasters.it/blog/?tag=glm-5-3",{"label":825,"link":971},"https://datamasters.it/blog/?tag=modelli-ai",[973],{"id":974,"image":975,"raw_date":978,"date":979,"date_day":980,"date_month":981,"title":982,"excerpt":983,"url":984,"taxonomies":985,"is_webinar":605},28438,{"url":976,"width":977,"height":977,"alt":21},"https://website-prod.datamasters.it/wp-content/uploads/2026/02/copertina-1.png",1024,"2026-02-20T13:14:08+01:00","20 Febbraio 2026","20","Feb","Something Big Is Happening: perché i nuovi modelli AI stanno cambiando il lavoro (e cosa devi fare ora)","Negli ultimi mesi c’è una sensazione strana nell’aria, soprattutto se lavori nel digitale, non si tratta della solita ondata di hype, ma qualcosa di più viscerale, quasi fastidioso. Per anni […]","https://datamasters.it/blog/something-big-is-happening-perche-i-nuovi-modelli-ai-stanno-cambiando-il-lavoro-e-cosa-devi-fare-ora/",{"category":986,"tag":988},[987],"blog",[989,990,991,992],"ai-developer","claude-opus-4-6","gpt-5-3","modelli-ai",[994],{"block_layout":995,"gutter_top":996,"gutter_bottom":996,"bg_color":997,"fg_color":183,"text":998,"cta":999,"small":605},"banner_icon_cta","xxl","color-primary-600","\u003Ch4 class=\"fw-semibold\" style=\"text-align: center;\">ISCRIVITI ED INIZIA\u003Cbr />\nAD IMPARARE SUBITO GRATIS\u003C/h4>\n\u003Cp class=\"font-size-body-1\" style=\"text-align: center;\">Accedi ora a risorse di apprendimento gratuite di alta qualità e trasforma le tue ambizioni\u003Cbr />\nin competenze concrete. Il tuo viaggio verso il successo inizia oggi!\u003C/p>\n",{"link":1000,"config":1002},{"title":118,"url":1001,"target":15},"https://datamasters.it/catalogo/?price=gratuito",{"variant":160,"theme":1003,"size":920},"theme-white",1792598863542]