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GLM 4.6 Thinking

z-ai/glm-4.6:thinking
BackTry Model
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GLM 4.6 Thinking

z-ai/glm-4.6:thinking
BackTry Model

Thinking version of the latest GLM series chat model with strong general performance. Quantized at FP8

Added Sep 29, 2025

Model weights

Context Window

200.0K

Max Output

65.5K

Avg output tokens (7d)

2.3K tokens

82%

Input Price (Auto)

$0.43/1M

Output Price (Auto)

$1.75/1M

Cache Read (Auto)

$0.21/1M

Capabilities

Benchmarks

Performance metrics and benchmarks

Sourced from Artificial Analysis.

Intelligence Index

29.3

Better than 68% of models compared

Coding Index

45.8

Better than 59% of models compared

Agentic Index

18.6

Better than 44% of models compared

Reasoning

GPQA Diamond

Graduate-level scientific reasoning

78.0%

Better than 66% of models compared

HLE

Humanity's Last Exam

14.5%

Better than 68% of models compared

IFBench

Instruction-following benchmark

43.4%

Better than 47% of models compared

T²-Bench Telecom

Conversational AI agents in dual-control scenarios

70.5%

Better than 63% of models compared

AA-LCR

Long context reasoning evaluation

55.3%

Better than 58% of models compared

GDPval-AA

Economically valuable tasks

21.7%

CritPt

Research-level physics reasoning

1.1%

Coding

SciCode

Python programming for scientific computing

38.4%

Better than 64% of models compared

Terminal-Bench Hard

Agentic coding and terminal use

25.0%

Better than 66% of models compared

LiveCodeBench

Contamination-free coding benchmark

69.5%

Better than 79% of models compared

Math

AIME 2025

American Invitational Mathematics Examination 2025

86.0%

Better than 84% of models compared

Knowledge

MMLU-Pro

Professional and academic subject knowledge

82.9%

Better than 82% of models compared

AA-Omniscience Accuracy

Proportion of correctly answered questions

26.9%

AA-Omniscience Hallucination Rate

Rate of incorrect answers among non-correct responses

94.1%

Last updated Aug 16, 2026

Artificial Analysis

Providers

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