← All models
Zhipu AI · mit
GLM-4.5
GLM-4.5 by Zhipu AI appears in 2 sources with Reasoning at 33.95. Best read for Code quality, Coding, High intelligence.
CreatorZhipu AI
Release date2025-07-28
Knowledge cutoffNot published
ContextUnknown
Input priceUnknown
Output priceUnknown
Modalitytext
CountryCN
Metrics
All source-backed metrics
LLM Stats Rank74ranking · source_rank
Reasoning33.95reasoning · index_reasoning
Math34.25math · index_math
Coding20.72coding · index_code
Research-4.57research · index_search
Writing25.15writing · index_communication
Vision8.19multimodal · index_vision
Tool calling25.62tool_calling · index_tool_calling
Finance41.64domain · index_finance
Legal37.52domain · index_legal
Healthcare37.3domain · index_healthcare
GPQA79.1 %reasoning · gpqa_score
SWE-bench Verified64.2 %coding · swe_bench_verified_score
Code Arena744.07 %coding · coding_arena_score
Humanity Last Exam14.4 %reasoning · hle_score
BrowseComp26.4 %research · browsecomp_score
Terminal Bench37.5 %coding · terminal_bench_score
TAU2 Retail79.7 %agent · tau_bench_retail_score
SciCode41.7 %coding · scicode_score
Parameters355,000,000,000 paramsmodel · params
Arena Rating1,428.95metric
Arena Rank52metric
Vote Count24,340metric
Evidence
Citations and source overlap
FAQ
How should I read this profile?
Treat this as a source-backed model dossier, not an EvalKit-run verification. The public values are replicated from linked sources and kept source-scoped.
Is GLM-4.5 verified by EvalKit?
No. EvalKit currently shows 0 verified rows until real run evidence exists.
Why can metrics disagree?
Different sources test different tasks, dates, prompts, and aggregation methods. EvalKit keeps those differences visible instead of merging them into a fake universal score.