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Model comparison

Grok 4.20 Multi-Agent Beta vs GLM-5.3

Compare Grok 4.20 Multi-Agent Beta and GLM-5.3 using the same provider-sourced text & reasoning rubric. No mystery score and no invented benchmark ranking.

Facts checked September 4, 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)
GLM-5.3Z.aiNo reviewed rate
Grok 4.20 Multi-Agent BetaSpaceXAINo reviewed rate

Quick take

Grok 4.20 Multi-Agent Beta

A specialist Grok model that sends several AI agents to investigate a difficult question in parallel, then combines their work into one researched answer.

Best for

  • Deep research with several lines of inquiry
  • Source gathering and cross-checking
  • Complex questions that benefit from parallel analysis

Watch out for

This is a beta product, not the newest general-purpose Grok. Its interface may change, and built-in searches or code runs can add cost beyond the headline token price.

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

Grok 4.20 Multi-Agent Beta 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 & reasoningGrok 4.20 Multi-Agent BetaGLM-5.3
Context windowMaximum combined prompt and working context documented by the provider.1,000,000 tokensUp to 1.31M on OpenRouter; 1M on QwenCloud
Maximum outputProvider-published response limit, where available.Not publishedUp 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.Not publishedNot published
Input priceCurrent standard list price per million input tokens unless noted.$1.25 / 1MFrom $1.15 / 1M on OpenRouter
Output priceCurrent standard list price per million output tokens unless noted.$2.50 / 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.4–16 agents; functions, web/X, code, collectionsTools, 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.

Grok 4.20 Multi-Agent Beta

SpaceXAI says API inputs and outputs are not used for training without explicit permission. Requests are encrypted and retained for 30 days by default; team-level zero data retention is available with feature tradeoffs.

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

Grok 4.20 Multi-Agent Beta vs GLM-5.3 FAQ

What is the main difference between Grok 4.20 Multi-Agent Beta and GLM-5.3?

Grok 4.20 Multi-Agent Beta: A specialist Grok model that sends several AI agents to investigate a difficult question in parallel, then combines their work into one researched answer. 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 Grok 4.20 Multi-Agent Beta or GLM-5.3?

Consider Grok 4.20 Multi-Agent Beta when your priority is Deep research with several lines of inquiry. 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 Grok 4.20 Multi-Agent Beta 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.