Compare Models
Select models (max 5)
GPT-6 AstraDeepSeek V4.1 Flash 1017
 |  |  |
|---|---|---|
| Vals IndexGDP-weighted benchmark | 63.13%±1.19 | 56.58%±1.27 |
| Legal Research BenchAgentic US legal research | 39.42%±3.40 | 45.19%±3.46 |
| Finance Agent (v2)Core financial analyst tasks | 53.54%±2.08 | 56.96%±2.05 |
| Tax Agent BenchAgentic US corporate tax research | 20.72%±2.92 | 44.35%±3.57 |
| MedCodeMedical billing code support | 48.49%±2.13 | N/A |
| Terminal-Bench-ScienceExpert-authored scientific research workflows | 62.86%±5.82 | N/A |
| Code MigrationRewriting programs in new languages | 67.74%±4.22 | 44.21%±4.46 |
| Terminal-Bench 4.0Frontier-difficulty terminal tasks | 59.60%±4.40 | 31.82%±2.62 |
| Vibe Code Bench v1.1Building web apps from scratch | 89.59%±2.17 | 87.73%±2.75 |
Benchmarks
Vals Index *
GPT-6 Astra
0.00%± 1.19
(50/50)DeepSeek V4.1 Flash 1017
0.00%± 1.27
(50/50)Legal Research Bench *
GPT-6 Astra
0.00%± 3.40
(80/80)DeepSeek V4.1 Flash 1017
0.00%± 3.46
(80/80)Finance Agent (v2) *
GPT-6 Astra
0.00%± 2.08
(80/80)DeepSeek V4.1 Flash 1017
0.00%± 2.05
(80/80)Tax Agent Bench *
GPT-6 Astra
0.00%± 2.92
(71/71)DeepSeek V4.1 Flash 1017
0.00%± 3.57
(71/71)MedCode *
GPT-6 Astra
0.00%± 2.13
(107/107)DeepSeek V4.1 Flash 1017
N/ATerminal-Bench-Science
GPT-6 Astra
0.00%± 5.82
(41/41)DeepSeek V4.1 Flash 1017
N/ACode Migration *
GPT-6 Astra
0.00%± 4.22
(79/79)DeepSeek V4.1 Flash 1017
0.00%± 4.46
(79/79)Terminal-Bench 4.0
GPT-6 Astra
0.00%± 4.40
(50/50)DeepSeek V4.1 Flash 1017
0.00%± 2.62
(50/50)Vibe Code Bench v1.1 *
GPT-6 Astra
0.00%± 2.17
(114/114)DeepSeek V4.1 Flash 1017
0.00%± 2.75
(114/114)Overall performance
Performance on the Vals Index, a GDP-weighted aggregation of tasks across finance, coding, and law
•2026-10-18
Comparison by Industry
Model performance on different sections of the economy.
Legal
22.42%
vs.27.18%
Finance
48.65%
vs.54.37%
Healthcare
68.20%
vs.N/A
Math
99.00%
vs.N/A
Science
54.65%
vs.N/A
Education
46.37%
vs.N/A
Coding
56.20%
vs.54.59%
Cyber
48.97%
vs.N/A
Cost Analysis
Per task and per token model pricing.
Vals Index · USD
$18.46
$0.637
Cost / TestVals Index
$18.46
vs.$0.637
Input Cost/ 1M Tokens
$10.00
vs.$0.30
Input Cache Write/ 1M Tokens
$12.50
vs.N/A
Input Cache Read/ 1M Tokens
$1.00
vs.$0.006
Output Cost/ 1M Tokens
$50.00
vs.$1.20
Model Metadata
Basic information about each model.
| | |
|---|---|---|
| Model provider | OpenAI | DeepSeek |
| Latency | 1667.74s | 2193.12s |
| Cost (In/Out) | $10 / $50 | $0.3 / $1.2 |
| Context Window | 1M | 1M |
| Max Output Token | 128k | 384k |
| Input Modality |