Only the same benchmark, version, workload, scenario and unit share a row. Missing results are not zero. System results include the full submitted hardware and software configuration.
Arena text preference / chinesehuman preference · 2026-10-28 · rating
GLM-4.6
1,498.91 rating
Confidence interval: 1,487.51 – 1,510.30
2721 votes
Category
chinese
Evaluated configuration
GLM-4.6
Evaluation type
human preference
Arena text preference / codinghuman preference · 2026-10-28 · rating
GLM-4.6
1,448.66 rating
Confidence interval: 1,441.53 – 1,455.80
7593 votes
Category
coding
Evaluated configuration
GLM-4.6
Evaluation type
human preference
Arena text preference / creative_writinghuman preference · 2026-10-28 · rating
GLM-4.6
1,411.86 rating
Confidence interval: 1,403.39 – 1,420.32
5146 votes
Category
creative_writing
Evaluated configuration
GLM-4.6
Evaluation type
human preference
Arena text preference / englishhuman preference · 2026-10-28 · rating
GLM-4.6
1,448.87 rating
Confidence interval: 1,443.51 – 1,454.24
15319 votes
Category
english
Evaluated configuration
GLM-4.6
Evaluation type
human preference
Arena text preference / exclude_tieshuman preference · 2026-10-28 · rating
GLM-4.6
1,437.13 rating
Confidence interval: 1,431.68 – 1,442.58
25098 votes
Category
exclude_ties
Evaluated configuration
GLM-4.6
Evaluation type
human preference
Arena text preference / experthuman preference · 2026-10-28 · rating
GLM-4.6
1,431.38 rating
Confidence interval: 1,418.47 – 1,444.28
2062 votes
Category
expert
Evaluated configuration
GLM-4.6
Evaluation type
human preference
Arena text preference / frenchhuman preference · 2026-10-28 · rating
GLM-4.6
1,459.60 rating
Confidence interval: 1,436.90 – 1,482.30
706 votes
Category
french
Evaluated configuration
GLM-4.6
Evaluation type
human preference
Arena text preference / germanhuman preference · 2026-10-28 · rating
GLM-4.6
1,446.92 rating
Confidence interval: 1,424.71 – 1,469.13
681 votes
Category
german
Evaluated configuration
GLM-4.6
Evaluation type
human preference
Arena text preference / hard_promptshuman preference · 2026-10-28 · rating
GLM-4.6
1,440.30 rating
Confidence interval: 1,435.35 – 1,445.26
19440 votes
Category
hard_prompts
Evaluated configuration
GLM-4.6
Evaluation type
human preference
Arena text preference / hard_prompts_englishhuman preference · 2026-10-28 · rating
GLM-4.6
1,444.90 rating
Confidence interval: 1,438.00 – 1,451.80
8251 votes
Category
hard_prompts_english
Evaluated configuration
GLM-4.6
Evaluation type
human preference
Arena text preference / industry_business_and_management_and_financial_operationshuman preference · 2026-10-28 · rating
Arena text preference / industry_entertainment_and_sports_and_mediahuman preference · 2026-10-15 · rating
GLM-4.6
1,408.55 rating
Confidence interval: 1,401.15 – 1,415.96
6679 votes
Category
industry_entertainment_and_sports_and_media
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / industry_legal_and_governmenthuman preference · 2026-10-15 · rating
GLM-4.6
1,447.99 rating
Confidence interval: 1,436.20 – 1,459.78
2450 votes
Category
industry_legal_and_government
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / industry_life_and_physical_and_social_sciencehuman preference · 2026-10-15 · rating
GLM-4.6
1,456.24 rating
Confidence interval: 1,448.39 – 1,464.10
5930 votes
Category
industry_life_and_physical_and_social_science
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / industry_mathematicalhuman preference · 2026-10-15 · rating
GLM-4.6
1,446.66 rating
Confidence interval: 1,432.95 – 1,460.37
1783 votes
Category
industry_mathematical
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / industry_medicine_and_healthcarehuman preference · 2026-10-15 · rating
GLM-4.6
1,455.00 rating
Confidence interval: 1,441.57 – 1,468.43
1934 votes
Category
industry_medicine_and_healthcare
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / industry_software_and_it_serviceshuman preference · 2026-10-15 · rating
GLM-4.6
1,455.26 rating
Confidence interval: 1,449.45 – 1,461.07
12610 votes
Category
industry_software_and_it_services
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / industry_writing_and_literature_and_languagehuman preference · 2026-10-15 · rating
GLM-4.6
1,415.41 rating
Confidence interval: 1,408.48 – 1,422.33
8091 votes
Category
industry_writing_and_literature_and_language
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / instruction_followinghuman preference · 2026-10-15 · rating
GLM-4.6
1,410.09 rating
Confidence interval: 1,403.81 – 1,416.38
10293 votes
Category
instruction_following
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / japanesehuman preference · 2026-10-15 · rating
GLM-4.6
1,392.84 rating
Confidence interval: 1,362.91 – 1,422.77
373 votes
Category
japanese
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / koreanhuman preference · 2026-10-15 · rating
GLM-4.6
1,400.05 rating
Confidence interval: 1,375.32 – 1,424.79
617 votes
Category
korean
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / longer_queryhuman preference · 2026-10-15 · rating
GLM-4.6
1,422.40 rating
Confidence interval: 1,415.85 – 1,428.94
9145 votes
Category
longer_query
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / mathhuman preference · 2026-10-15 · rating
GLM-4.6
1,431.96 rating
Confidence interval: 1,419.43 – 1,444.50
2153 votes
Category
math
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / multi_turnhuman preference · 2026-10-15 · rating
GLM-4.6
1,426.97 rating
Confidence interval: 1,418.82 – 1,435.11
5615 votes
Category
multi_turn
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / non_englishhuman preference · 2026-10-15 · rating
GLM-4.6
1,426.15 rating
Confidence interval: 1,421.33 – 1,430.96
20465 votes
Category
non_english
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / overallhuman preference · 2026-10-15 · rating
GLM-4.6
1,439.92 rating
Confidence interval: 1,436.03 – 1,443.80
35824 votes
Category
overall
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / polishhuman preference · 2026-10-15 · rating
GLM-4.6
1,446.74 rating
Confidence interval: 1,430.51 – 1,462.97
1301 votes
Category
polish
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / russianhuman preference · 2026-10-15 · rating
GLM-4.6
1,418.56 rating
Confidence interval: 1,408.99 – 1,428.13
3546 votes
Category
russian
Evaluated configuration
glm-4.6
Evaluation type
human preference
Arena text preference / spanishhuman preference · 2026-10-15 · rating
GLM-4.6
1,435.97 rating
Confidence interval: 1,416.99 – 1,454.96
1015 votes
Category
spanish
Evaluated configuration
glm-4.6
Evaluation type
human preference
Run it locally
Inference · memory estimate
GLM-4.6
664.6 GiB checkpoint tensor payload · 356.79 B stored tensor elements · BF16/F32
Stored tensors can include buffers and repeated shared weights. A verified unique parameter count is unavailable. Checkpoint size is not the memory required to run the model.
Capabilities
Context window
202,752 tokens
Maximum input
200,000 tokens*
Maximum output
128,000 tokens*
Reasoning
Yes*
Tool calling
Yes*
Open weights
Yes
API mode
Chat*
Prompt caching
Yes*
Tool choice
Yes*
Model license
mit
Checkpoint tensor payload
664.57 GiB
Input modalities
text
Output modalities
text
Processing & platform
Architecture
glm4_moe
System configuration
Detailed specifications
Specifications · 12 fields
cache creation input token cost
0*Scope and conditions
native_context
provider
zai*
mode
chat*
full_native_model_id
zai/glm-4.6*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
cache read input token cost
1.1e-7*Scope and conditions
native_context
provider
zai*
mode
chat*
full_native_model_id
zai/glm-4.6*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
input cost per token
6.0e-7*Scope and conditions
native_context
provider
zai*
mode
chat*
full_native_model_id
zai/glm-4.6*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
litellm provider
zai*Scope and conditions
native_context
provider
zai*
mode
chat*
full_native_model_id
zai/glm-4.6*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
max input tokens
200,000*Scope and conditions
native_context
provider
zai*
mode
chat*
full_native_model_id
zai/glm-4.6*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
max output tokens
128,000*Scope and conditions
native_context
provider
zai*
mode
chat*
full_native_model_id
zai/glm-4.6*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
mode
chat*Scope and conditions
native_context
provider
zai*
mode
chat*
full_native_model_id
zai/glm-4.6*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
output cost per token
2.2e-6*Scope and conditions
native_context
provider
zai*
mode
chat*
full_native_model_id
zai/glm-4.6*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
supports function calling
Yes*Scope and conditions
native_context
provider
zai*
mode
chat*
full_native_model_id
zai/glm-4.6*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
supports prompt caching
Yes*Scope and conditions
native_context
provider
zai*
mode
chat*
full_native_model_id
zai/glm-4.6*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
supports reasoning
Yes*Scope and conditions
native_context
provider
zai*
mode
chat*
full_native_model_id
zai/glm-4.6*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*
supports tool choice
Yes*Scope and conditions
native_context
provider
zai*
mode
chat*
full_native_model_id
zai/glm-4.6*
pricing_scope
Literal source field names and values retained; provider, region, cache/batch/threshold conditions and per-unit meaning must be checked. max_tokens is not automatically a context limit.*