GLM 4 32B is a cost-effective foundation language model. It can efficiently perform complex tasks and has significantly enhanced capabilities in tool use, online search, and code-related intelligent tasks. It...
Tested on 6 benchmarks · BenchGecko score 37.5. Top scores: BBH (HuggingFace) (35.8%), MMLU-PRO (34.9%), IFEval (14.3%).
GPT-5 Nano scores 37.7 (101% as good) at $0.05/1M input · 50% cheaper
HuggingFace MuSR (Multi-Step Reasoning). Tests multi-hop reasoning requiring chaining multiple facts together.
HuggingFace evaluation of MATH Level 5 problems. Competition math requiring advanced reasoning and proof construction.
HuggingFace MMLU-Pro. Harder version of MMLU with 10 answer choices instead of 4 and more challenging questions.
HuggingFace evaluation of GPQA (Graduate-Level Google-Proof Q&A). PhD-level science questions that cannot be easily searched.
- Typetext
- Context128K tokens (~64 books)
- ReleasedJul 2025
- LicenseProprietary
- StatusActive
- Cost / Message~$0.000
Frequently Asked Questions
Key facts · as of 2026-05-03
- GLM 4 32B by z-ai. BenchGecko score 37.5, rank 209 of 312 scored models (normalized average of public benchmark scores).
- List price $0.10 input · $0.10 output per 1M tokens (as of 2026-05-03).
How to cite · data as of 2026-05-03
GLM 4 32B · benchmarks, pricing and providers. BenchGecko, data as of 2026-05-03. https://benchgecko.ai/model/glm-4-32b
Credit "Source: BenchGecko" with a link. Prices per provider and Gecko Tests are BenchGecko data (CC BY 4.0); benchmark scores keep their original source, listed in the JSON. JSON · llms.txt · MCP