Compare Models

Select models (max 7)

GLM 4.5Kimi K3.1 Pro


Vals IndexGDP-weighted benchmark	N/A	62.52%±1.14
Legal Research BenchAgentic US legal research	N/A	37.50%±3.37
Finance Agent v2.1Core financial analyst tasks	N/A	61.49%±2.10
Tax Agent BenchAgentic US corporate tax research	N/A	24.87%±3.12
Terminal-Bench 4.0Frontier-difficulty terminal tasks	N/A	63.64%±1.75
Vibe Code Bench v1.1Building web apps from scratch	N/A	84.89%±2.95

Benchmarks

Vals Index *

GLM 4.5

N/A

Kimi K3.1 Pro

0.00%± 1.14

(27/27)

Legal Research Bench *

GLM 4.5

N/A

Kimi K3.1 Pro

0.00%± 3.37

(85/85)

Finance Agent v2.1 *

GLM 4.5

N/A

Kimi K3.1 Pro

0.00%± 2.10

(31/31)

Tax Agent Bench *

GLM 4.5

N/A

Kimi K3.1 Pro

0.00%± 3.12

(76/76)

Terminal-Bench 4.0

GLM 4.5

N/A

Kimi K3.1 Pro

0.00%± 1.75

(55/55)

Vibe Code Bench v1.1 *

GLM 4.5

N/A

Kimi K3.1 Pro

0.00%± 2.95

(119/119)

Overall performance

Performance on the Vals Index, a GDP-weighted aggregation of tasks across finance, coding, and law

•2026-10-24

GLM 4.5 Kimi K3.1 Pro

Comparison by Industry

Model performance on different sections of the economy.

Legal

75.63%

vs.

24.58%

Finance

72.40%

vs.

52.12%

Academic

76.72%

vs.

N/A

Coding

67.45%

vs.

74.27%

Cost Analysis

Per task and per token model pricing.

Vals Index · USD

N/A

$6.44

Cost / TestVals Index

N/A

vs.

$6.44

Input Cost/ 1M Tokens

$0.60

vs.

$2.00

Input Cache Read/ 1M Tokens

$0.11

vs.

$0.20

Output Cost/ 1M Tokens

$2.20

vs.

$10.00

Model Metadata

Basic information about each model.


Model provider	zAI	Kimi
Latency	N/A	3816.45s
Cost (In/Out)	$0.6 / $2.2	$2 / $10
Context Window	128k	1M
Max Output Token	82k	1M
Input Modality