GLM-4.5
BenchLM is tracking GLM-4.5, but sourced benchmark results are not published on the site yet. This page currently shows the model metadata we can verify now, and score-level benchmark coverage will appear once public evaluations land.
GLM-4.5 is a proprietary model with a 128K token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.
This profile currently has 0 sourced benchmarks on BenchLM, so the benchmark sections below are intentionally marked as coming soon.
Its strongest category is Agentic (#72), while its weakest is Instruction Following (#104). This performance profile makes it particularly useful for coding agents, browser research, and computer-use workflows.
Ranking Distribution
Category rank across 7 benchmark categories — sorted by best rank
Category Performance
Scores across all benchmark categories (0-100 scale)
Category Breakdown
Agentic
#72Coding
#80Reasoning
#83Knowledge
#87Math
#80Multilingual
#96Multimodal
#104Inst. Following
#104Chatbot Arena Performance
Benchmark Details
Only benchmark rows with an attached exact-source record are shown here. Source-unverified manual rows and generated rows are hidden from model pages.
Compare This Model
See how GLM-4.5 stacks up against similar models
Frequently Asked Questions
How does GLM-4.5 perform overall in AI benchmarks?
BenchLM is tracking GLM-4.5, but sourced benchmark coverage is still coming soon. We currently list its creator, model type, and context window while we wait for public benchmark results.
Does GLM-4.5 have full benchmark coverage on BenchLM?
Not yet. GLM-4.5 currently has 0 published benchmark scores out of the 152 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.
What is the context window size of GLM-4.5?
GLM-4.5 has a context window of 128K, which determines how much text it can process in a single interaction.
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