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Z.ai

GLM-5.2

Best Overall

Text model for long-horizon engineering with 1M context, 128K output and configurable thinking.

1M contextLong horizon
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At a glance

Know the model before you prompt.

Z.ai API specifications
Context window
1M
Maximum output
128K
Inputs → output
Text → Text
Knowledge cutoff
Not verified

API model ID: glm-5.2

Capabilities & boundaries

What it supports. Where the limits are.

Tool support requires the appropriate API integration; a supported tool is not automatically active in every chat.

Supported API features and tools

  • 1M-token context for extensive text and repository material
  • Long-horizon coding and engineering planning
  • Configurable thinking with documented effort compatibility mappings
  • Function calling, structured output and streaming in the API

Before you choose

  • Context and output limits use the provider's published K/M units. They are capacity ceilings, not a guarantee of complete recall or a final answer of that length. A model-specific knowledge cutoff was not verified.
  • This is a text-input guide. Supply extracted text for document analysis; do not assume the model can directly inspect images, videos or attached files just because other GLM models can.
  • Answers and proposed code still need validation. A tool call is a request for an integration to execute an action, not proof it ran. Keep approvals around consequential changes and check results against source evidence.

Choose the reasoning effort

highmax · default

Thinking is enabled by default and can be disabled. With reasoning enabled, high and max are the effective effort levels. The API maps low/medium to high and xhigh to max; none/minimal skip thinking. These compatibility mappings differ from GLM-5.3's three always-on levels.

  • GLM-5.2's published context is 1M, compared with 200K for GLM-5.1. Do not copy the older model's context limit.
  • The API documents effort aliases for compatibility; use explicit effective levels and test request behavior before migrating between GLM generations.
  • Select the exact API identifier shown here. Website slugs use hyphens for URLs and are not substitutes for dotted API model names. API access and the GLM Coding Plan endpoint have different entitlements.
  • For supported interleaved-thinking tool loops, retain the returned reasoning_content with the tool history. Preserved thinking uses thinking.clear_thinking false and unmodified history; its documented defaults differ between the standard API and Coding Plan endpoints. Check model support before enabling it.

Put it to work

Start with a more useful prompt.

Original examples from EZ Ai Assist. Adapt these to your task and the features available in your workspace.

Workflow 01

Build a staged engineering plan

Keep long work bounded by checkpoints.

Using this issue, repository map and acceptance criteria, propose a staged engineering plan. For each stage list required files, expected artifacts, tests, failure conditions and a point for human review. Separate actions already supported by evidence from assumptions. Do not start external work or imply an autonomous runtime is available.

Workflow 02

Find cross-file inconsistencies

Use long context to connect concrete contracts.

Inspect the supplied API definitions, client code and tests for inconsistencies. For each finding cite both sides of the mismatch and describe a minimal reproducer. Rank findings by user impact, then propose focused regression tests. Avoid conclusions about files not included in the material.

Workflow 03

Audit completion evidence

Check whether a project is actually ready.

Compare this implementation report, diff and test output with the original requirements. Mark each requirement verified, contradicted or unverified, and cite the evidence. Distinguish visual checks, functional tests and architecture work. Return only the remaining work and the evidence needed to close it, without inventing test results.

Developer reference

Z.ai API pricing

These are Z.ai direct API reference prices, not EZ Ai Assist subscription prices.

View EZ Ai Assist plans
Standard processing · USD per 1,000,000 tokens
Token typePrice
Input$1.40
Cached input$0.26
Output$4.40
  • Input and output are billed separately per 1,000,000 tokens. Compare actual task usage, retries and latency rather than the input rate alone. These rates are not guaranteed reseller or app prices.
  • Only eligible cache hits receive the cached-input rate. Cached-input storage is listed as limited-time free, not permanently free. Recheck the provider table for storage terms and future changes.
  • The pricing page separately lists built-in Web Search at $0.01 per use. This is a service fee when that tool is used, not a charge on every prompt or a promise that this model or your workspace has automatic search.

Common questions

A few things worth knowing.

Does GLM-5.2 have the same context as GLM-5.1?

No. The provider lists 1M for GLM-5.2 and 200K for GLM-5.1. Both list 128K maximum output.

Can its thinking be disabled?

Yes. Unlike GLM-5.3, its documented controls support skipping thinking. The API also treats none/minimal effort as skipping it.

What happens to low, medium and xhigh effort?

The API maps low and medium to high, and xhigh to max. These are compatibility aliases, not additional independent effort levels.

Does long-horizon capability mean unattended execution?

No. Sustained work needs an agent runtime, tools, state management and approval boundaries. The model guide alone does not establish those features in your workspace.

Does the context window guarantee complete recall?

No. A large context is a capacity limit, not an accuracy guarantee. Label sources, split unrelated material, ask for evidence references and test whether important details were omitted. Output also has its own ceiling.

Are these prices the cost of my EZ Ai Assist plan?

No. This is a dated reference to direct Z.ai API token pricing. EZ Ai Assist subscriptions, Z.ai's GLM Coding Plan, optional tools and third-party hosting are separate products with their own terms.

Are all of these capabilities available in the app?

Not necessarily. The guide describes provider documentation, not workspace entitlements or an integration test. Check your model picker, accepted inputs and available controls. None of these examples runs tools or changes external systems by itself.

Check the source

Official documentation

Specifications and API prices checked on . Example prompts and workflow advice are editorial guidance from EZ Ai Assist.

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