Compare Models
Select models (max 5)
GPT-5.6 LunaMiMo V2.6 Flash
 |  |  |
|---|---|---|
| Vals IndexGDP-weighted benchmark | 51.69%±1.06 | 53.23%±1.10 |
| Legal Research BenchAgentic US legal research | 36.54%±3.35 | 37.98%±3.37 |
| Finance Agent (v2)Core financial analyst tasks | 55.04%±0.31 | 56.28%±0.46 |
| Tax Agent BenchAgentic US corporate tax research | 60.81%±3.26 | 59.90%±3.13 |
| MedCodeMedical billing code support | 42.39%±2.27 | 41.06%±2.03 |
| Terminal-Bench ScienceExpert-authored scientific research workflows | 0.00%±0.00 | 4.29%±2.44 |
| Code MigrationRewriting programs in new languages | 44.55%±4.24 | 40.93%±4.35 |
| Terminal-Bench 4.0Frontier-difficulty terminal tasks | 11.62%±1.01 | 24.24%±1.51 |
| Vibe Code Bench v1.1Building web apps from scratch | 77.06%±3.07 | 78.96%±4.04 |
Benchmarks
Vals Index *
GPT-5.6 Luna
0.00%± 1.06
(43/43)MiMo V2.6 Flash
0.00%± 1.10
(43/43)Legal Research Bench *
GPT-5.6 Luna
0.00%± 3.35
(73/73)MiMo V2.6 Flash
0.00%± 3.37
(73/73)Finance Agent (v2) *
GPT-5.6 Luna
0.00%± 0.31
(74/74)MiMo V2.6 Flash
0.00%± 0.46
(74/74)Tax Agent Bench *
GPT-5.6 Luna
0.00%± 3.26
(65/65)MiMo V2.6 Flash
0.00%± 3.13
(65/65)MedCode *
GPT-5.6 Luna
0.00%± 2.27
(104/104)MiMo V2.6 Flash
0.00%± 2.03
(104/104)Terminal-Bench Science
GPT-5.6 Luna
0.00%± 0.00
(38/38)MiMo V2.6 Flash
0.00%± 2.44
(38/38)Code Migration *
GPT-5.6 Luna
0.00%± 4.24
(73/73)MiMo V2.6 Flash
0.00%± 4.35
(73/73)Terminal-Bench 4.0
GPT-5.6 Luna
0.00%± 1.01
(43/43)MiMo V2.6 Flash
0.00%± 1.51
(43/43)Vibe Code Bench v1.1 *
GPT-5.6 Luna
0.00%± 3.07
(108/108)MiMo V2.6 Flash
0.00%± 4.04
(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
40.61%
vs.24.62%
Finance
65.29%
vs.60.55%
Healthcare
63.39%
vs.63.17%
Math
60.00%
vs.63.00%
Science
25.30%
vs.31.72%
Academic
87.58%
vs.N/A
Education
44.22%
vs.43.53%
Coding
46.38%
vs.38.46%
Cyber
73.63%
vs.39.78%
Social Mobility
61.16%
vs.67.59%
Cost Analysis
Per task and per token model pricing.
Vals Index · USD
$0.824
$0.202
Cost / TestVals Index
$0.824
vs.$0.202
Input Cost/ 1M Tokens
$0.20
vs.$0.14
Input Cache Write/ 1M Tokens
$0.25
vs.N/A
Input Cache Read/ 1M Tokens
$0.02
vs.$0.003
Output Cost/ 1M Tokens
$1.20
vs.$0.28
Model Metadata
Basic information about each model.
| | |
|---|---|---|
| Model provider | OpenAI | Xiaomi |
| Latency | 1767.44s | 3481.73s |
| Cost (In/Out) | $0.2 / $1.2 | $0.14 / $0.28 |
| Context Window | 1M | 1M |
| Max Output Token | 128k | 128k |
| Input Modality |