Compare Models

Select models (max 5)
Qwen 3.7 MaxGLM 5.3 Flash
Benchmarks

Legal Research Bench *

Qwen 3.7 Max
0.00%± 3.03
(73/73)
GLM 5.3 Flash
0.00%± 3.46
(73/73)

Finance Agent (v2) *

Qwen 3.7 Max
0.00%± 0.73
(74/74)
GLM 5.3 Flash
0.00%± 2.06
(74/74)

Tax Agent Bench *

Qwen 3.7 Max
0.00%± 3.24
(65/65)
GLM 5.3 Flash
0.00%± 3.26
(65/65)

MedCode *

Qwen 3.7 Max
0.00%± 2.20
(104/104)
GLM 5.3 Flash
N/A

Terminal-Bench Science

Qwen 3.7 Max
N/A
GLM 5.3 Flash
0.00%± 2.01
(38/38)

Code Migration *

Qwen 3.7 Max
0.00%± 2.86
(73/73)
GLM 5.3 Flash
0.00%± 4.21
(73/73)

Vibe Code Bench v1.1 *

Qwen 3.7 Max
0.00%± 4.63
(108/108)
GLM 5.3 Flash
0.00%± 5.28
(108/108)

Overall performance

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

2026-10-02

Comparison by Industry

Model performance on different sections of the economy.

Legal
37.35%
45.26%
Finance
56.88%
62.83%
Healthcare
59.07%
88.94%
Math
N/A
21.00%
Science
N/A
2.86%
Academic
89.73%
86.14%
Coding
54.15%
41.56%
Cyber
N/A
67.86%

Cost Analysis

Per task and per token model pricing.

Vals Index · USD
N/A
N/A
Cost / TestVals Index
N/A
N/A
Input Cost/ 1M Tokens
$2.50
$0.075
Input Cache Write/ 1M Tokens
$3.125
N/A
Input Cache Read/ 1M Tokens
$0.25
$0.015
Output Cost/ 1M Tokens
$7.50
$0.25

Model Metadata

Basic information about each model.

Model provider
AlibabaAlibaba
zAIzAI
LatencyN/AN/A
Cost (In/Out)$2.5 / $7.5$0.075 / $0.25
Context Window984k1M
Max Output Token66k128k
Input Modality