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Model comparison

Claude Opus 5 vs GLM-5.3

Compare Claude Opus 5 and GLM-5.3 using the same provider-sourced text & reasoning rubric. No mystery score and no invented benchmark ranking.

Facts checked September 14, 2026

Estimate your cost

Set your usage. Your estimate updates as you type.

Example: 6,000 input tokens for 10 pages, plus a 500-token summary. Page lengths vary; adjust the numbers below.

One run sends your input to the model once and receives an answer. Tokens are pieces of text: input is what you send, output is the answer you receive.

Advanced options
How this estimate works

Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.

Estimate your cost
ModelEstimated total (USD)
Claude Opus 5Anthropic$0.0425
GLM-5.3Z.aiNo reviewed rate

Quick take

Claude Opus 5

A Claude model for substantial code changes, reasoning and business workflows with many steps.

Best for

  • Codebase changes
  • Multi-step workflows

Watch out for

Thinking is on by default. Reasoning effort and longer answers affect both cost and response time.

GLM-5.3

Z.ai's open-weight long-context reasoning model for coding, tools, and agentic work across self-hosted and managed routes.

Best for

  • Long-context coding agents
  • Open-weight enterprise experiments
  • Teams that want several inference-provider choices

Watch out for

Compare the exact checkpoint and host, not just the model name. Context, maximum output, speed, price, logging, and reasoning controls can all change by route.

Compare the published facts

Claude Opus 5 vs GLM-5.3

Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.

Text & reasoningClaude Opus 5GLM-5.3
Context windowMaximum combined prompt and working context documented by the provider.1M tokensUp to 1.31M on OpenRouter; 1M on QwenCloud
Maximum outputProvider-published response limit, where available.128K tokensUp to 262,144 tokens on OpenRouter
Knowledge cutoffLatest reliable knowledge date explicitly published by the model provider. Search and connected tools can retrieve newer information but do not change the model's built-in cutoff.May 2026Not published
Input priceCurrent standard list price per million input tokens unless noted.$5 / 1MFrom $1.15 / 1M on OpenRouter
Output priceCurrent standard list price per million output tokens unless noted.$25 / 1MFrom $3.50 / 1M on OpenRouter
InputsMedia types accepted by the listed model endpoint.Text, imageText
Tools & agentsSelected native tools and agent-building capabilities, not an exhaustive list.Tool use, agents, vision, coding workflowsTools, structured outputs, controllable reasoning on supported routes

How to choose

Compare the job, not the hype.

Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.

Claude Opus 5

Anthropic does not train on API data without express permission. Retention depends on the API feature, account agreement and cloud provider.

GLM-5.3

Self-hosted weights keep prompts inside infrastructure you control. QwenCloud says it does not retain API inputs or outputs for training; OpenRouter and other providers apply their own route policies.

Frequently asked questions

Claude Opus 5 vs GLM-5.3 FAQ

What is the main difference between Claude Opus 5 and GLM-5.3?

Claude Opus 5: A Claude model for substantial code changes, reasoning and business workflows with many steps. GLM-5.3: Z.ai's open-weight long-context reasoning model for coding, tools, and agentic work across self-hosted and managed routes.

Should I choose Claude Opus 5 or GLM-5.3?

Consider Claude Opus 5 when your priority is Codebase changes. Consider GLM-5.3 when your priority is Long-context coding agents. Test both with your own data and provider route before committing.

Is this Claude Opus 5 vs GLM-5.3 comparison based on Cody benchmarks?

No. This comparison aligns provider-published facts for the Text & reasoning category. It does not claim a universal winner or combine incompatible third-party benchmark scores.