GLM-4.6
BenchLM is tracking GLM-4.6, but this profile is currently excluded from the public leaderboard because it still lacks enough non-generated benchmark coverage to rank safely. Only non-generated public benchmark rows appear below.
GLM-4.6 is a open weight model with a 200K token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.
This profile currently has 17 of 225 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Ranking Distribution
Category rank across 0 benchmark categories — sorted by best rank
Category Performance
Scores across all benchmark categories (0-100 scale)
Category Breakdown
Agentic
Coding
Reasoning
Knowledge
Math
Multilingual
Multimodal
Inst. Following
Chatbot 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-4.6 stacks up against similar models
Frequently Asked Questions
How does GLM-4.6 perform overall in AI benchmarks?
GLM-4.6 has 17 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.
Is GLM-4.6 good for knowledge and understanding?
GLM-4.6 has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is GLM-4.6 good for coding and programming?
GLM-4.6 has visible benchmark coverage in coding and programming, but BenchLM does not currently assign it a global category rank there.
Is GLM-4.6 good for reasoning and logic?
GLM-4.6 has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Is GLM-4.6 good for agentic tool use and computer tasks?
GLM-4.6 has visible benchmark coverage in agentic tool use and computer tasks, but BenchLM does not currently assign it a global category rank there.
Is GLM-4.6 good for instruction following?
GLM-4.6 has visible benchmark coverage in instruction following, but BenchLM does not currently assign it a global category rank there.
Is GLM-4.6 open source?
Yes, GLM-4.6 is an open weight model created by Z.AI, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Does GLM-4.6 have full benchmark coverage on BenchLM?
Not yet. GLM-4.6 currently has 17 published benchmark scores out of the 225 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-4.6?
GLM-4.6 has a context window of 200K, which determines how much text it can process in a single interaction.
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