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Z.ai

Chat with GLM 5.3 online

Z.ai's frontier engineer — a million tokens of context and reasoning that holds across a long agent run.

Coba GLM 5.3 Lihat paket
Dipercaya 790,000+ pengguna

1.048576M tokens

Konteks

131,072 tokens

Output maks

Cepat

Kecepatan

Untuk apa Anda akan menggunakannya

Whole-service refactors

A million tokens of context means the whole codebase in one thread.

Long agent runs

Reasoning before every tool call, kept coherent across many steps.

Architecture and review

Design decisions and trade-offs argued end to end.

Incident analysis

Logs, traces and history read together to find the cause.

Prompts to steal

Tuned to this model — click any line to copy.

Tentang GLM 5.3

GLM 5.3 is Z.ai's August 2026 flagship and the current top of the GLM line, a step up from GLM 5.2. Z.ai built it for the two jobs its predecessors were already used for hardest: complex software engineering, and agent runs that have to stay coherent over many steps. On NinjaChat it is included in every plan, in the same picker as Claude, GPT-5.6 and Gemini.

The headline change is context. GLM 5.3 works with about a million tokens on NinjaChat's rail, roughly five times what 5.2 handled here, which changes what you can put in one thread: a whole service rather than a few files, a long incident history rather than the last hour, a full spec plus the code that is supposed to implement it.

The GLM signature carries through. The model reasons before each response and before each tool call, and it adapts how much reasoning a turn deserves rather than spending the same effort on everything. In a long agent loop that is the difference between a model that drifts by step twenty and one that still remembers what it was asked to do.

It is text in and text out — no image input on this one. If you need to hand it a screenshot or a diagram, GLM 5.3 Flash is the multimodal sibling and it sits right next to it in the picker. For everyday coding at speed, GLM 4.7 is still the cheaper pick; 5.3 is what you escalate to when the problem is genuinely hard.

Cara menggunakan GLM 5.3

Dari nol ke hasil pertama Anda dalam waktu kurang dari satu menit.

01

Create a NinjaChat account and choose a plan

02

Open chat and pick GLM 5.3 from the model list

03

Paste the whole problem: files, logs, constraints, the goal

04

Keep the task in one thread so it carries its reasoning forward

05

Drop to GLM 4.7 or GLM 5.3 Flash when you want speed

Tips untuk hasil yang lebih baik

  • Give it more context rather than less; that is what the million tokens are for
  • Ask it to think longer on the turns that matter
  • Paste error output verbatim rather than describing it
  • Use GLM 5.3 Flash when the task includes images

GLM 5.3 vs alternatif lainnya

Perbandingan jujur — di mana {model} unggul, dan di mana tidak.

vs GLM 5.2

Lihat model

+A much larger context and stronger long-horizon behavior

–5.2 remains a solid flagship for shorter tasks

vs GLM 5.3 Flash

Lihat model

+More depth on genuinely hard engineering problems

–Flash is far cheaper and reads images and video

vs DeepSeek V4 Pro

Lihat model

+Adaptive reasoning tuned for agent loops

–V4 Pro is a strong open alternative at a similar cost

Pertanyaan yang sering diajukan

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GLM 5.3, dan 50 lainnya.

Satu langganan mencakup semua model di NinjaChat, termasuk GLM 5.3.

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Model lain untuk dijelajahi

GLM 5.2

Model andalan Z.ai untuk coding, agen, dan pekerjaan sistem

→

GLM 5.3 Flash

Z.ai's multimodal Flash: images and video in, a million tokens of context

→

GLM 4.7

Model efisien dari Zhipu untuk coding, penalaran, dan tugas umum

→
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