Compare Models
Select models (max 7)
Qwen 3.6 27BKimi 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 | 11.94%±3.41 | 84.89%±2.95 |
Benchmarks
Vals Index *
Qwen 3.6 27B
N/AKimi K3.1 Pro
0.00%± 1.14
(27/27)Legal Research Bench *
Qwen 3.6 27B
N/AKimi K3.1 Pro
0.00%± 3.37
(85/85)Finance Agent v2.1 *
Qwen 3.6 27B
N/AKimi K3.1 Pro
0.00%± 2.10
(31/31)Tax Agent Bench *
Qwen 3.6 27B
N/AKimi K3.1 Pro
0.00%± 3.12
(76/76)Terminal-Bench 4.0
Qwen 3.6 27B
N/AKimi K3.1 Pro
0.00%± 1.75
(55/55)Vibe Code Bench v1.1 *
Qwen 3.6 27B
0.00%± 3.41
(119/119)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
Comparison by Industry
Model performance on different sections of the economy.
Legal
N/A
vs.24.58%
Finance
69.77%
vs.52.12%
Education
45.58%
vs.N/A
Coding
40.97%
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
N/A
vs.$0.20
Output Cost/ 1M Tokens
$3.60
vs.$10.00
Model Metadata
Basic information about each model.
| | |
|---|---|---|
| Model provider | Alibaba | Kimi |
| Latency | N/A | 3816.45s |
| Cost (In/Out) | $0.6 / $3.6 | $2 / $10 |
| Context Window | 262k | 1M |
| Max Output Token | 66k | 1M |
| Input Modality |