Compare Models
Select models (max 5)
Claude Opus 4.8GPT-6 Luna
 |  |  |
|---|---|---|
| Vals IndexGDP-weighted benchmark | 55.10%±1.01 | 51.22%±1.07 |
| Legal Research BenchAgentic US legal research | 43.75%±3.45 | 30.29%±3.19 |
| Finance Agent (v2)Core financial analyst tasks | 53.92%±0.16 | 49.87%±0.23 |
| Tax Agent BenchAgentic US corporate tax research | 64.91%±3.17 | 58.86%±3.21 |
| MedCodeMedical billing code support | 53.22%±2.17 | 44.69%±2.30 |
| Terminal-Bench ScienceExpert-authored scientific research workflows | 4.29%±2.44 | 4.29%±2.44 |
| Code MigrationRewriting programs in new languages | 47.25%±4.18 | 42.55%±4.42 |
| Terminal-Bench 4.0Frontier-difficulty terminal tasks | 23.23%±1.34 | 13.64%±1.51 |
| Vibe Code Bench v1.1Building web apps from scratch | 82.72%±3.08 | 81.65%±3.38 |
Benchmarks
Vals Index *
Claude Opus 4.8
0.00%± 1.01
(43/43)GPT-6 Luna
0.00%± 1.07
(43/43)Legal Research Bench *
Claude Opus 4.8
0.00%± 3.45
(73/73)GPT-6 Luna
0.00%± 3.19
(73/73)Finance Agent (v2) *
Claude Opus 4.8
0.00%± 0.16
(74/74)GPT-6 Luna
0.00%± 0.23
(74/74)Tax Agent Bench *
Claude Opus 4.8
0.00%± 3.17
(65/65)GPT-6 Luna
0.00%± 3.21
(65/65)MedCode *
Claude Opus 4.8
0.00%± 2.17
(104/104)GPT-6 Luna
0.00%± 2.30
(104/104)Terminal-Bench Science
Claude Opus 4.8
0.00%± 2.44
(38/38)GPT-6 Luna
0.00%± 2.44
(38/38)Code Migration *
Claude Opus 4.8
0.00%± 4.18
(73/73)GPT-6 Luna
0.00%± 4.42
(73/73)Terminal-Bench 4.0
Claude Opus 4.8
0.00%± 1.34
(43/43)GPT-6 Luna
0.00%± 1.51
(43/43)Vibe Code Bench v1.1 *
Claude Opus 4.8
0.00%± 3.08
(108/108)GPT-6 Luna
0.00%± 3.38
(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
45.63%
vs.16.60%
Finance
66.75%
vs.59.08%
Healthcare
69.49%
vs.64.20%
Math
N/A
vs.64.00%
Science
4.29%
vs.28.38%
Academic
89.53%
vs.N/A
Education
54.79%
vs.48.09%
Coding
55.69%
vs.38.78%
Cyber
N/A
vs.76.25%
Social Mobility
68.13%
vs.57.65%
Cost Analysis
Per task and per token model pricing.
Vals Index · USD
$13.14
$0.431
Cost / TestVals Index
$13.14
vs.$0.431
Input Cost/ 1M Tokens
$5.00
vs.$0.10
Input Cache Write/ 1M Tokens
$6.25
vs.$0.125
Input Cache Read/ 1M Tokens
$0.50
vs.$0.01
Output Cost/ 1M Tokens
$25.00
vs.$0.50
Model Metadata
Basic information about each model.
| | |
|---|---|---|
| Model provider | Anthropic | OpenAI |
| Latency | 2388.43s | 1833.68s |
| Cost (In/Out) | $5 / $25 | $0.1 / $0.5 |
| Context Window | 1M | 1M |
| Max Output Token | 128k | 128k |
| Input Modality |