Z.ai (Zhipu), open weights

GLM-4.6

GLM-4.6 by Z.ai (Zhipu) ranks 135th of 354 ranked models on the Noometry Index as of October 2026, with a score of 41.4. Its strongest category is agentic & tool use, where it ranks 66th. API pricing starts at $0.60 per million input tokens and $2.20 per million output tokens, with a 205K-token context window.

Last verified

Specifications

Noometry rank
#135 of 354
Index score
41.4
Evidence
Confirmed 29 results
Released
September 30, 2025
Weights
Open weights
Reasoning
Yes
Context window
205K
Max output
131K
Input price
$0.60 / M
Output price
$2.20 / M
Blended price
$1 / M
Output speed
12 tokens/s Kagi
Value
#113 of 219
Knowledge cutoff
April 2025
Input
text
Hugging Face
zai-org/GLM-4.6

Category scores

Each category score combines every public result we have in that category.

GLM-4.6 category scores
  1. Coding 40.1
  2. Agentic & Tool Use 32.3
  3. Reasoning 23.7
  4. Math 39.1
  5. Knowledge 40.2
  6. Multilingual 53.5
  7. Instruction Following 74.3
  8. Long Context 43.4
  9. Writing & Preference 61.1
GLM-4.6 category ranks
CategoryScoreRankResults
Coding40.1#1484
Agentic & Tool Use32.3#662
Reasoning23.7#1723
Math39.1#1111
Knowledge40.2#1242
Multilingual53.5#661
Instruction Following74.3#981
Long Context43.4#941
Writing & Preference61.1#904

Strengths and weaknesses

Categories where GLM-4.6 places highest and lowest among the models ranked in each, with its score against that category's median.

Strongest categories

GLM-4.6: strongest categories
CategoryScorevs medianRank
Multilingual53.5+6.1#66 of 297, top 23%
Writing & Preference61.1+7.3#90 of 312, top 29%
Long Context43.4+2.5#94 of 296, top 32%

Weakest categories

GLM-4.6: weakest categories
CategoryScorevs medianRank
Reasoning23.7+0.1#172 of 350, top 50%
Coding40.1+1.4#148 of 340, top 44%
Agentic & Tool Use32.3+2.0#66 of 154, top 43%

Closest competitors

The models ranked just above and below GLM-4.6. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to GLM-4.6
ModelRankScoreBlended $/MSpeed
Muse Glimmer#13141.7——Compare
o4-mini#13241.6$1.936Compare
Gemini 3.5 Flash Lite#13341.5$0.85—Compare
Grok 4.1#13441.5——Compare
Grok 4.1 Fast#13641.4$0.28—Compare
GLM-4.6V#13741.3$0.45—Compare
MiMo-V2-Flash#13841.3$0.18—Compare
Hunyuan Turbos 20250226#13941.3——Compare

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Benchmark results

Every published result we track, with its source. Bold rows are the ones used for ranking; where several exist we prefer independent runs over self-reported numbers.

Coding

GLM-4.6 Coding benchmark results
BenchmarkScorePositionSettingSourceDate
SWE-bench Verified (bash only)55.4%#23 of 39, top 59%SWE-bench2025-12-01
LMArena WebDev1340#90 of 113, top 80%LMArena2026-10-08
SciCode38.4%#88 of 121, top 73%Epoch AI
LMArena Coding1449#87 of 294, top 30%LMArena2026-10-08
ALE-Bench340.82#95 of 105, top 91%Epoch AI

Agentic & Tool Use

GLM-4.6 Agentic & Tool Use benchmark results
BenchmarkScorePositionSettingSourceDate
Terminal-Bench24.5%#35 of 41, top 86%Epoch AI
Berkeley Function Calling Leaderboard72.4%#4 of 49, top 9%fc thinkingBerkeley Function Calling Leaderboard

Reasoning

GLM-4.6 Reasoning benchmark results
BenchmarkScorePositionSettingSourceDate
Kagi LLM Benchmark45.7%Kagi LLM Benchmark
Kagi LLM Benchmark47.4%#69 of 99, top 70%Kagi LLM Benchmark
CritPt1.1%#80 of 134, top 60%Epoch AI
LMArena Hard Prompts1440#81 of 297, top 28%LMArena2026-10-08

Math

GLM-4.6 Math benchmark results
BenchmarkScorePositionSettingSourceDate
LMArena Math1432#80 of 285, top 29%LMArena2026-10-08
FrontierMath (Feb 2025 set)3.8%#51 of 68, top 75%Epoch AI2025-12-08
FrontierMath Tier 4 (v1)2.1%#36 of 55, top 66%Epoch AI2025-12-08

Knowledge

GLM-4.6 Knowledge benchmark results
BenchmarkScorePositionSettingSourceDate
Vectara Hallucination Rate (lower is better)9.5%#50 of 96, top 53%Vectara Hallucination Leaderboard
LMArena Expert1431#95 of 273, top 35%LMArena2026-10-08

Multilingual

GLM-4.6 Multilingual benchmark results
BenchmarkScorePositionSettingSourceDate
LMArena Non-English1426#66 of 297, top 23%LMArena2026-10-08
LMArena Chinese1499#45 of 285, top 16%LMArena2026-10-08
LMArena French1459#53 of 223, top 24%LMArena2026-10-08
LMArena German1447#48 of 231, top 21%LMArena2026-10-08
LMArena Japanese1393#66 of 211, top 32%LMArena2026-10-08
LMArena Korean1400#53 of 213, top 25%LMArena2026-10-08
LMArena Russian1419#83 of 283, top 30%LMArena2026-10-08
LMArena Spanish1436#71 of 226, top 32%LMArena2026-10-08

Instruction Following

GLM-4.6 Instruction Following benchmark results
BenchmarkScorePositionSettingSourceDate
LMArena Instruction Following1410#87 of 298, top 30%LMArena2026-10-08

Long Context

GLM-4.6 Long Context benchmark results
BenchmarkScorePositionSettingSourceDate
LMArena Longer Query1422#87 of 291, top 30%LMArena2026-10-08

Writing & Preference

GLM-4.6 Writing & Preference benchmark results
BenchmarkScorePositionSettingSourceDate
LMArena Text1440#62 of 297, top 21%LMArena2026-10-08
LMArena Creative Writing1411#62 of 295, top 22%LMArena2026-10-08
EQ-Bench Creative Writing1411#71 of 115, top 62%EQ-Bench
LMArena Multi-Turn1427#87 of 295, top 30%LMArena2026-10-08

API pricing by provider

GLM-4.6 API prices
RouteInput $/MOutput $/MCached input $/MChecked
deepinfra$0.50$2$0.102026-10-10
openrouter$0.50$2$0.102026-10-10
zai$0.60$2.20$0.112026-10-10

Compare GLM-4.6

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Frequently asked questions

How good is GLM-4.6?

GLM-4.6 by Z.ai (Zhipu) ranks 135th of 354 ranked models on the Noometry Index as of October 2026, with a score of 41.4. Its strongest category is agentic & tool use, where it ranks 66th. API pricing starts at $0.60 per million input tokens and $2.20 per million output tokens, with a 205K-token context window.

How much does GLM-4.6 cost?

GLM-4.6 costs $0.60 per million input tokens and $2.20 per million output tokens on Z.ai (Zhipu)'s own API, with cached input at $0.11.

What is GLM-4.6's context window?

GLM-4.6 accepts up to 205K tokens of input and can write up to 131K tokens in one response.

Is GLM-4.6 open source?

Yes. GLM-4.6's weights are downloadable from Hugging Face (zai-org/GLM-4.6); check the license for commercial terms.

How fast is GLM-4.6?

GLM-4.6 generated about 12 output tokens per second in the Kagi LLM Benchmark's timed runs. Speed varies by provider, load and reasoning effort.

What are GLM-4.6's strengths and weaknesses?

Relative to other ranked models, GLM-4.6 places best in multilingual, writing & preference, long context and lowest in reasoning, coding, agentic & tool use.

What is GLM-4.6 best at?

Its best category is agentic & tool use, where it ranks 66th on Noometry.