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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.

Experimentar GLM 5.3 Ver planos
A confiança de 790,000+ usuários

1.048576M tokens

Contexto

131,072 tokens

Saída máxima

Rápido

Velocidade

Para o que você vai usar

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.

Sobre o 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.

Como usar o GLM 5.3

Do zero ao seu primeiro resultado em menos de um minuto.

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

Dicas para resultados melhores

  • 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 as alternativas

Comparações honestas — onde o {model} vence e onde não vence.

vs GLM 5.2

Ver modelo

+A much larger context and stronger long-horizon behavior

–5.2 remains a solid flagship for shorter tasks

vs GLM 5.3 Flash

Ver modelo

+More depth on genuinely hard engineering problems

–Flash is far cheaper and reads images and video

vs DeepSeek V4 Pro

Ver modelo

+Adaptive reasoning tuned for agent loops

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

Perguntas frequentes

Além do chat — imagens e vídeo

Todo plano NinjaChat inclui 50+ modelos, um estúdio completo de imagens e geração de vídeo.

A real FLUX Pro Ultra outputA real Google Imagen 4 outputA real Seedream output
Ver todos os modelos →

GLM 5.3, e mais 50.

Uma única assinatura cobre todos os modelos do NinjaChat, incluindo GLM 5.3.

ComeçarComparar planos
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Mais modelos para explorar

GLM 5.2

O carro-chefe da Z.ai para código, agentes e engenharia de sistemas

→

GLM 5.3 Flash

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

→

GLM 4.7

O modelo eficiente da Zhipu para programação, raciocínio e tarefas gerais

→
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