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AI model comparison

Claude Opus 4 (latest) vs zai-org/GLM-5.2

Compare pricing, context limits, supported inputs and deployment options to choose a model for your workflow.

Claude Opus 4 (latest) from Anthropic lists 200K context, 32K maximum output. zai-org/GLM-5.2 from zai-org lists 1M context, 131.07K maximum output, $1.40 input per 1M tokens, $4.40 output per 1M tokens. Compare the inputs, outputs and deployment options below to see which fits your workflow.

Side-by-sideCapabilities and practical differences

Anthropic

Claude Opus 4 (latest)

Claude Opus 4 (latest) from Anthropic: Flagship Claude model for deep reasoning, coding, and long-horizon agents.

Context
200K
Max output
32K

Accepts

  • Text input
  • Image input
  • PDF input

Produces

  • Text output
Full model profilegithub.com ↗
VS

At a glance

Key differences

Compare the available figures below, then try both models on the work you need to do.

zai-org/GLM-5.2

  • Context capacity: 1M
  • Maximum output: 131.07K

Context capacity

Higher listed limit

Claude Opus 4 (latest):200K

zai-org/GLM-5.2:1M

zai-org/GLM-5.2

Maximum output

Higher listed limit

Claude Opus 4 (latest):32K

zai-org/GLM-5.2:131.07K

zai-org/GLM-5.2

Specifications

Pricing, limits and capabilities

Specifications for Claude Opus 4 (latest) and zai-org/GLM-5.2. Higher limits and lower prices describe these figures only.
SpecificationClaude Opus 4 (latest)zai-org/GLM-5.2
ProviderAnthropiczai-org
Listed pricing routeAnthropiczai-org
Model familyclaude-opus—
Accepted inputstext, image, pdftext
Produced outputstexttext
Context window200K1MHigher
Max output32K131.07KHigher
Input price / 1M—$1.40
Output price / 1M—$4.40
Reasoning modeDocumentedDocumented
Tool callingDocumentedDocumented
Image inputDocumentedNot documented
Audio inputNot documentedNot documented
Structured outputNot documentedNot documented
LicenseProprietaryNot documented

Workload guidance

Which model should you choose?

Consider zai-org/GLM-5.2 if you need larger context or larger maximum output. Test both on the same representative examples and judge the output against your acceptance criteria. Include tool failures, retries and the time to a completed task.

Documentation and model profiles

Explore each model’s features, API requirements and licence terms in the sources below.

Questions people ask

It brings together documented inputs and outputs, token limits, deployment terms and available pricing. When both models have source-linked, verified results on a shared benchmark, those results are shown with their individual sources. The comparison is a starting point for evaluating your own workload.

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