GLM LLM Models

GLM is a cutting-edge LLM series by Z.ai (Zhipu AI) featuring GLM-5, GLM-4.7, and GLM-4.6. Engineered for complex systems and long-horizon agentic tasks, GLM-5 outperforms top-tier closed-source models in elite benchmarks like Humanity’s Last Exam and BrowseComp. While GLM-4.7 specializes in reasoning, coding, and real-world intelligent agents, the entire GLM suite is fast, smart, and reliable, making it the ultimate tool for building websites, analyzing data, and delivering instant, high-quality answers for any professional workflow.

Apa Yang Membuat GLM LLM Models Menonjol

Atlas Cloud menyediakan model kreatif terdepan di industri yang terbaru untuk Anda.

Advanced Reasoning

Tuned for strong logical reasoning, structured analysis, and multi-step problem solving.

Cost-Efficiency

Optimized architectures keep latency and costs under control.

Safety & Governance

Built-in content filters, auditing tools, and policy controls help teams deploy.

Enterprise Reliability

Production-ready SLAs, monitoring, and governance features help teams confidently ship applications.

Chinese–English Excellence

Native-strength Chinese and fluent English support enable high-quality bilingual chat, search, and generation.

Developer-Friendly Ecosystem

Clean APIs, SDKs, and tooling make it easy to integrate, fine-tune, and operate Z.ai across products and platforms.

Kecepatan puncak

Biaya terendah

ModelDescription
GLM-5GLM-5 is Z.ai's flagship LLM featuring a massive 202.75K context window optimized for complex systems and long-horizon agentic tasks. Outperforming elite closed-source models in benchmarks like Humanity’s Last Exam and BrowseComp, it provides robust programming and stable multi-step reasoning at highly competitive baseline pricing.
GLM-4.7GLM-4.7 is a high-performance LLM with a 202.75K context window specifically engineered for real-world intelligent agents, advanced reasoning, and professional coding. Fast, smart, and reliable, it serves as the ideal engine for building complex websites and automating sophisticated professional workflows with precision.
GLM-4.6GLM-4.6 is a powerful MoE LLM with a 202.75K context window designed for rapid data analysis and instant, high-fidelity answers. This dependable model excels at high-efficiency tasks like creating professional slides and web content, offering a smart balance of speed and enterprise-grade performance.

Fitur baru GLM LLM Models + Showcase

Menggabungkan model canggih dengan platform berakselerasi GPU Atlas Cloud memberikan kecepatan, skalabilitas, dan kontrol kreatif tak tertandingi untuk pembuatan gambar dan video.

Arsitektur MoE 744B Masif dan Basis Pengetahuan Universal

Arsitektur MoE 744B Masif dan Basis Pengetahuan Universal

Model GLM-5 memanfaatkan arsitektur Mixture-of-Experts (MoE) dengan 744 miliar parameter yang dilatih pada 28,5 triliun token yang mencengangkan untuk mendefinisikan ulang batas kinerja open-source. Dengan mengoptimalkan 40 miliar parameter aktif, model ini memfasilitasi lompatan besar dalam kepadatan pengetahuan dunia dan presisi pengambilan informasi. Ini adalah fondasi utama untuk tugas kognitif skala besar dan sintesis data yang kompleks.

Rekayasa Sistem Agen Terobosan dengan GLM-5

Rekayasa Sistem Agen Terobosan dengan GLM-5

GLM-5 memperkenalkan kemampuan agen tingkat lanjut yang dirancang untuk eksekusi tugas sistemik jangka panjang di seluruh lingkungan penalaran multi-langkah. Dengan mengintegrasikan logika perencanaan yang canggih ke dalam arsitektur intinya, model ini mempertahankan stabilitas yang luar biasa selama pengembangan perangkat lunak otomatis dan penyusunan hukum profesional. Ini berfungsi sebagai mesin definitif untuk alur kerja otonom yang membutuhkan presisi ekstrem dan konsistensi jangka panjang.

Slime Pembelajaran Penguatan Asinkron dan Evolusi Logika

Slime Pembelajaran Penguatan Asinkron dan Evolusi Logika

GLM-5 memanfaatkan infrastruktur pembelajaran penguatan asinkron "Slime" yang inovatif untuk merevolusi efisiensi pasca-pelatihan dan ketelitian logis. Terobosan ini secara signifikan meningkatkan kualitas pembuatan kode dan penalaran algoritmik, melampaui tolok ukur sebelumnya dan mengamankan peringkatnya sebagai model open-source tingkat atas. Ini adalah solusi utama untuk pengembangan full-stack dan pemecahan masalah struktural tingkat tinggi.

Yang Dapat Anda Lakukan dengan GLM LLM Models

Temukan kasus penggunaan praktis dan alur kerja yang dapat Anda bangun dengan keluarga model ini — dari pembuatan konten dan otomatisasi hingga aplikasi tingkat produksi.

Intelijen Repositori Komprehensif dengan GLM-5

GLM-5 API memberdayakan pengembang untuk menyerap seluruh basis kode (codebase) guna analisis logika mendalam dan refactoring struktural. Dengan memetakan grafik dependensi dan melacak aliran data asinkron yang kompleks, API ini mengidentifikasi kondisi balapan (race conditions) pada kasus tepi dan utang teknis yang tersembunyi. Sempurna untuk onboarding tim yang cepat, tinjauan PR otomatis, dan memelihara arsitektur layanan mikro (microservices) yang dapat diskalakan dan berkinerja tinggi.

Pembuatan Prototipe Full-Stack Instan menggunakan GLM-5

Untuk pengembangan berbasis "vibe", GLM-5 mengubah maket visual abstrak dan catatan terfragmentasi menjadi komponen React atau Next.js yang siap diterapkan. Model ini menangani pekerjaan berat pembuatan boilerplate, penataan gaya Tailwind CSS, dan manajemen state sambil memastikan konsistensi lintas halaman. Ideal untuk pendiri solo, eksperimentator UX, dan meluncurkan MVP fungsional secepat kilat.

Orkestrasi Alur Kerja Otonom dengan GLM-5

GLM-5 unggul dalam mengelola tugas penelitian jangka panjang yang memerlukan penalaran multi-langkah dan integrasi alat waktu nyata. Ia dapat secara independen mensintesis data pasar dari berbagai sumber, menyusun ringkasan hukum yang patuh, dan mengotomatiskan penjadwalan lintas platform yang kompleks tanpa kehilangan konteks. Kasus penggunaan ini cocok untuk manajer proyek, profesional hukum, dan siapa pun yang membutuhkan agen digital dengan keandalan tinggi untuk operasi sistemik.

Perbandingan Model

Lihat bagaimana model dari berbagai penyedia dibandingkan — bandingkan performa, harga, dan keunggulan unik untuk membuat keputusan yang tepat.

ModelContextMax OutputInputPositioning
GLM-5202.75K202.75KTextFlagship Foundation Model
GLM-4.7202.75K202.75KTextFlagship Foundation Model
GLM-4.6202.75K202.75KTextEfficient MoE Model
DeepSeek V3.2163.84K163.84KTextFlagship General
MiniMax-M2.5204.8K196.6KTextSOTA Agentic Coding

How to Use GLM LLM Models on Atlas Cloud

Get started in minutes — follow these simple steps to integrate and deploy models through Atlas Cloud’s platform.

Create an Atlas Cloud Account

Sign up at atlascloud.ai and complete verification. New users receive free credits to explore the platform and test models.

Mengapa Menggunakan GLM LLM Models di Atlas Cloud

Gabungkan model GLM LLM Models canggih dengan platform akselerasi GPU Atlas Cloud untuk performa, skalabilitas, dan pengalaman pengembangan yang tak tertandingi.

Performa & Fleksibilitas

Latensi Rendah:
Inferensi yang dioptimalkan GPU untuk respons real-time.

API Terpadu:
Satu integrasi untuk GLM LLM Models, GPT, Gemini, dan DeepSeek.

Harga Transparan:
Billing per token, mendukung mode Serverless.

Enterprise & Skala

Pengalaman Developer:
SDK, analitik data, alat fine-tuning, dan template tersedia lengkap.

Keandalan:
Ketersediaan 99.99%, kontrol izin RBAC, logging kepatuhan.

Keamanan & Kepatuhan:
Sertifikasi SOC 2 Type II, kepatuhan HIPAA, kedaulatan data AS.

Pertanyaan yang Sering Diajukan tentang GLM LLM Models

Dengan 28,5T token data pelatihan dan hasil tolok ukur yang luar biasa, GLM-5 secara luas dianggap sebagai "langit-langit open-source". Model ini menyaingi atau melampaui model komersial global tingkat atas dalam hal kapasitas dan logika, menyediakan fondasi yang kuat dan berkinerja tinggi bagi ekosistem pengembang global.

HLE adalah tolok ukur berkesulitan tinggi yang dirancang untuk menguji apakah AI memiliki pengetahuan dan penalaran manusia tingkat ahli. Pencapaian skor tertinggi oleh GLM-5 menandakan bahwa penguasaannya terhadap sains terdepan dan logika kompleks telah mencapai atau melampaui level model sumber tertutup (closed-source) terkemuka.

BrowseComp adalah papan peringkat definitif untuk kemampuan "Agentic", yang berfokus pada perencanaan dan pelaksanaan tugas yang kompleks dalam lingkungan web dunia nyata. Skor tertinggi mewakili kemampuan GLM-5 untuk menavigasi browser secara mandiri dan mengintegrasikan informasi lintas halaman, menandainya sebagai mesin Web Agent utama.

Arsitektur ini menyediakan "basis pengetahuan" masif sebesar 744 miliar parameter sembari hanya mengaktifkan ~40 miliar selama inferensi. Bagi pengembang, ini berarti kepadatan pengetahuan dan kedalaman penalaran kelas dunia—melampaui model padat (dense models) seperti Llama-3 405B—dengan latensi dan biaya yang lebih rendah.

Total parameter mewakili "kapasitas pengetahuan" model, dengan 744B memungkinkan penyimpanan fakta dunia dan logika ahli yang luas. Parameter aktif mewakili "daya komputasi" yang digunakan per inferensi. Berkat arsitektur MoE, GLM-5 menghadirkan kecerdasan level 744B hanya dengan menggunakan komputasi 40B, menyeimbangkan basis pengetahuan yang masif dengan kinerja berkecepatan tinggi dan hemat biaya.

Volume data pra-pelatihan menentukan "luasnya wawasan" sebuah model. 28,5T token adalah salah satu dataset terbesar secara global (kira-kira dua kali lipat dari Llama-3), mencakup bahasa langka, makalah akademis khusus, dan kode berkualitas tinggi yang luas. Hal ini memastikan GLM-5 memiliki akurasi dan generalisasi yang unggul saat menangani kueri long-tail yang kompleks, nuansa lintas budaya, dan pemrograman sistem tingkat rendah.

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