Model Comparison

Qwen3 32B vs GLM-5

Compare the listed model data for Qwen3 32B by Qwen and GLM-5 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

Qwen3 32B: 128K tokens; GLM-5: 128K tokens. The listed context-window values are equal. Qwen3 32B is listed for coding, reasoning, agentic workflows, long-context tasks; GLM-5 is listed for coding, reasoning, agentic workflows, long-context tasks. Shared catalog benchmark entries: MMLU: Qwen3 32B 92.0%; GLM-5 88.0%; LiveCodeBench: Qwen3 32B 64.4%; GLM-5 60.0%. 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: Qwen3 32B − GLM-5 = +4 percentage points (92.0% vs 88.0%); LiveCodeBench: Qwen3 32B − GLM-5 = +4.4 percentage points (64.4% vs 60.0%).
  • A release-date gap cannot be calculated from the catalog values (Qwen3 32B: April 2025; GLM-5: 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 $1 for Qwen3 32B and $0.3 for GLM-5. This excludes provider-specific discounts, caching, and other fees.

Choose Qwen3 32B if…

Choose Qwen3 32B when your task aligns with catalog-listed uses or strengths such as Production coding assistants for enterprise software teams, Mathematical reasoning and data science, Complex document analysis and long-form reporting, Multilingual enterprise applications.

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.

Qwen3 32B

Browse Qwen models

32B dense Qwen3 — excels at complex coding, mathematics, and deep multi-step reasoning. Top performer in its size class.

Parameters: 32B

Context: 128K tokens

Catalog pricing: Open source — free. Third-party API ~$0.14-0.30/MTok

Qwen Coding · Reasoning · Agentic · Long Context Open Source

View Qwen3 32B model profile

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

Feature Comparison — Qwen3 32B vs GLM-5

Catalog specifications for Qwen3 32B and GLM-5
Specification Qwen3 32B GLM-5
Provider Qwen Zhipu AI
Parameters 32B Not publicly disclosed
Context window 128K tokens 128K tokens
Maximum output Not listed Not listed
Catalog pricing Open source — free. Third-party API ~$0.14-0.30/MTok Apache 2.0 — free
Listed input/output cost per 1M tokens input $0.3, output $0.7 per 1M tokens input $0.1, output $0.2 per 1M tokens
License Apache 2.0 Apache 2.0
Coding support Listed Listed
Reasoning support Listed Listed
Vision input Not listed Not listed
Multimodal Not listed Not listed
Open weights Yes Yes
Benchmark: MMLU 92.0% 88.0%
Benchmark: LiveCodeBench 64.4% 60.0%

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 Qwen3 32B and GLM-5?
Qwen3 32B: 128K tokens; GLM-5: 128K tokens. The listed context-window values are equal. Qwen3 32B is listed for coding, reasoning, agentic workflows, long-context tasks; GLM-5 is listed for coding, reasoning, agentic workflows, long-context tasks. Shared catalog benchmark entries: MMLU: Qwen3 32B 92.0%; GLM-5 88.0%; LiveCodeBench: Qwen3 32B 64.4%; GLM-5 60.0%. 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 Qwen3 32B and GLM-5?
MMLU: Qwen3 32B 92.0%; GLM-5 88.0%; LiveCodeBench: Qwen3 32B 64.4%; GLM-5 60.0%. 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?
Qwen3 32B: 128K tokens; GLM-5: 128K tokens. The listed context-window values are equal.
What are the listed costs per million tokens for Qwen3 32B and GLM-5?
Qwen3 32B: input $0.3, output $0.7 per 1M tokens (Open source — free. Third-party API ~$0.14-0.30/MTok). GLM-5: input $0.1, output $0.2 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 Qwen3 32B and GLM-5?
The catalog lists Qwen3 32B as April 2025 and GLM-5 as 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 Qwen3 32B and GLM-5?
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.

Still deciding? Try both free — no commitment.

Create your free LITHOVEX account and compare Qwen3 32B and GLM-5 on your actual tasks. No credit card, no API key, no subscriptions needed.