Compare Models
Select models (max 5)
Qwen 3.8 MaxGLM 5.2
 |  |  |
|---|---|---|
| Vals IndexGDP-weighted benchmark | 48.27%±1.34 | N/A |
| Legal Research BenchAgentic US legal research | 47.60%±3.47 | 31.25%±3.22 |
| Finance Agent (v2)Core financial analyst tasks | 50.59%±0.58 | 49.70%±0.88 |
| Tax Agent BenchAgentic US corporate tax research | 65.96%±3.18 | N/A |
| MedCodeMedical billing code support | 40.67%±2.03 | 40.77%±2.17 |
| Terminal-Bench ScienceExpert-authored scientific research workflows | 12.86%±4.03 | N/A |
| Code MigrationRewriting programs in new languages | 23.96%±4.31 | 37.87%±4.14 |
| Terminal-Bench 4.0Frontier-difficulty terminal tasks | 34.34%±3.94 | N/A |
| Vibe Code Bench v1.1Building web apps from scratch | 64.70%±5.36 | 63.96%±4.79 |
Benchmarks
Vals Index *
Qwen 3.8 Max
0.00%± 1.34
(43/43)GLM 5.2
N/ALegal Research Bench *
Qwen 3.8 Max
0.00%± 3.47
(73/73)GLM 5.2
0.00%± 3.22
(73/73)Finance Agent (v2) *
Qwen 3.8 Max
0.00%± 0.58
(74/74)GLM 5.2
0.00%± 0.88
(74/74)Tax Agent Bench *
Qwen 3.8 Max
0.00%± 3.18
(65/65)GLM 5.2
N/AMedCode *
Qwen 3.8 Max
0.00%± 2.03
(104/104)GLM 5.2
0.00%± 2.17
(104/104)Terminal-Bench Science
Qwen 3.8 Max
0.00%± 4.03
(38/38)GLM 5.2
N/ACode Migration *
Qwen 3.8 Max
0.00%± 4.31
(73/73)GLM 5.2
0.00%± 4.14
(73/73)Terminal-Bench 4.0
Qwen 3.8 Max
0.00%± 3.94
(43/43)GLM 5.2
N/AVibe Code Bench v1.1 *
Qwen 3.8 Max
0.00%± 5.36
(108/108)GLM 5.2
0.00%± 4.79
(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
47.21%
vs.40.80%
Finance
63.23%
vs.61.52%
Healthcare
62.81%
vs.62.15%
Math
58.00%
vs.N/A
Science
18.37%
vs.N/A
Academic
90.11%
vs.86.16%
Education
51.25%
vs.N/A
Coding
46.69%
vs.49.95%
Cyber
28.57%
vs.0.00%
Social Mobility
67.12%
vs.N/A
Cost Analysis
Per task and per token model pricing.
Vals Index · USD
$4.964
N/A
Cost / TestVals Index
$4.964
vs.N/A
Input Cost/ 1M Tokens
$2.00
vs.$1.40
Input Cache Write/ 1M Tokens
$2.50
vs.N/A
Input Cache Read/ 1M Tokens
$0.25
vs.$0.26
Output Cost/ 1M Tokens
$6.00
vs.$4.40
Model Metadata
Basic information about each model.
| | |
|---|---|---|
| Model provider | Alibaba | zAI |
| Latency | 6070.72s | N/A |
| Cost (In/Out) | $2 / $6 | $1.4 / $4.4 |
| Context Window | 1M | 1M |
| Max Output Token | 128k | 131k |
| Input Modality |