Model Comparison

GLM-5 vs GLM-4 32B (Apr 14)

Compare the listed model data for GLM-5 by Zhipu AI and GLM-4 32B (Apr 14) by Zhipu AI. Benchmark and pricing records are not a controlled test and may change.

Data last updated: 2026-10-16. Verify current model details with each provider.

What the listed data says

GLM-5: 128K tokens; GLM-4 32B (Apr 14): 128K tokens. The listed context-window values are equal. GLM-5 is listed for coding, reasoning, agentic workflows, long-context tasks; GLM-4 32B (Apr 14) is listed for no specific capability flags. Shared catalog benchmark entries: MMLU: GLM-5 88.0%; GLM-4 32B (Apr 14) 82.7%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.

Catalog source links

Use these model and provider links to verify current specifications, pricing, and availability.

Computed differences from catalog data

  • The listed context windows are 128K tokens and 128K tokens; the larger is 1× the smaller.
  • On shared numeric benchmark entries, MMLU: GLM-5 − GLM-4 32B (Apr 14) = +5.3 percentage points (88.0% vs 82.7%).
  • A release-date gap cannot be calculated from the catalog values (GLM-5: 2025; GLM-4 32B (Apr 14): April 2025).

Cost example: 1M input and 1M output tokens

Using only the catalog's listed per-million-token rates, 1M input plus 1M output tokens costs about $0.3 for GLM-5 and $0.9 for GLM-4 32B (Apr 14). This excludes provider-specific discounts, caching, and other fees.

Choose GLM-5 if…

Choose GLM-5 when your task aligns with catalog-listed uses or strengths such as Chinese enterprise AI requiring GLM-5 quality, Zhipu AI's flagship GLM-5 model, Best bilingual Chinese-English in GLM family, Apache 2.0.

Choose GLM-4 32B (Apr 14) if…

Choose GLM-4 32B (Apr 14) when your task aligns with catalog-listed uses or strengths such as Enterprise AI for Chinese-speaking markets, Bilingual Chinese-English document analysis, Chinese legal, medical, and financial processing, Strong bilingual Chinese-English — best open 32B for Chinese tasks.

GLM-5

Browse Zhipu AI models

GLM-5 flagship — powerful reasoning model with elite Chinese/English bilingual capabilities and agentic tool use.

Parameters: Not publicly disclosed

Context: 128K tokens

Catalog pricing: Apache 2.0 — free

Zhipu AI Coding · Reasoning · Agentic · Long Context Open Source

View GLM-5 model profile

GLM-4 32B (Apr 14)

Browse Zhipu AI models

Dense 32B GLM-4 — strong performer for coding, math, and complex Chinese/English reasoning tasks.

Parameters: 32B

Context: 128K tokens

Catalog pricing: Apache 2.0 — free

Zhipu AI General Purpose Open Source

View GLM-4 32B (Apr 14) model profile

Feature Comparison — GLM-5 vs GLM-4 32B (Apr 14)

Catalog specifications for GLM-5 and GLM-4 32B (Apr 14)
Specification GLM-5 GLM-4 32B (Apr 14)
Provider Zhipu AI Zhipu AI
Parameters Not publicly disclosed 32B
Context window 128K tokens 128K tokens
Maximum output Not listed Not listed
Catalog pricing Apache 2.0 — free Apache 2.0 — free
Listed input/output cost per 1M tokens input $0.1, output $0.2 per 1M tokens input $0.3, output $0.6 per 1M tokens
License Apache 2.0 Apache 2.0
Coding support Listed Not listed
Reasoning support Listed Not listed
Vision input Not listed Not listed
Multimodal Not listed Not listed
Open weights Yes Yes
Benchmark: MMLU 88.0% 82.7%

Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.

Frequently Asked Questions

What is different between GLM-5 and GLM-4 32B (Apr 14)?
GLM-5: 128K tokens; GLM-4 32B (Apr 14): 128K tokens. The listed context-window values are equal. GLM-5 is listed for coding, reasoning, agentic workflows, long-context tasks; GLM-4 32B (Apr 14) is listed for no specific capability flags. Shared catalog benchmark entries: MMLU: GLM-5 88.0%; GLM-4 32B (Apr 14) 82.7%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
What benchmark values are listed for GLM-5 and GLM-4 32B (Apr 14)?
MMLU: GLM-5 88.0%; GLM-4 32B (Apr 14) 82.7%. The catalog values may use different versions and evaluation setups, so they are reference points rather than a controlled head-to-head result.
Which model has the larger listed context window?
GLM-5: 128K tokens; GLM-4 32B (Apr 14): 128K tokens. The listed context-window values are equal.
What are the listed costs per million tokens for GLM-5 and GLM-4 32B (Apr 14)?
GLM-5: input $0.1, output $0.2 per 1M tokens (Apache 2.0 — free). GLM-4 32B (Apr 14): input $0.3, output $0.6 per 1M tokens (Apache 2.0 — free). Where separate numeric input and output rates are available, the worked example uses 1M input plus 1M output tokens. Confirm current terms with each provider.
How far apart are the listed release dates for GLM-5 and GLM-4 32B (Apr 14)?
The catalog lists GLM-5 as 2025 and GLM-4 32B (Apr 14) as April 2025; a release-date gap cannot be calculated from both records.
When was the comparison data last updated?
The model catalog records 2026-10-16 as its data update date. Provider specifications and prices may have changed since then.
How should I choose between GLM-5 and GLM-4 32B (Apr 14)?
Compare the listed specifications and capabilities, review the benchmark notes, then test both with the same representative prompt for your task. This page does not claim a universal winner.

Explore these models and related comparisons

Read the GLM-5 model profile and GLM-4 32B (Apr 14) model profile, or browse the model directory.

Return to the comparison directory

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