EXAONE 4.5 33B vs. K2-V2: comparación de lanzamientos
Comparación de los lanzamientos EXAONE 4.5 33B y K2-V2: 2 y 3 modelos respectivamente, cada uno con distintas características de inteligencia, rendimiento y precio. A continuación se comparan las métricas clave de los 5 modelos.
- En inteligencia, EXAONE 4.5 33B obtiene la puntuación más alta: EXAONE 4.5 33B, con 13, frente a K2-V2 (high), con 10 de K2-V2.
Lanzamientos comparados
Inteligencia
Artificial Analysis Intelligence Index
Intelligence Index vs. Cost per Intelligence Index Task
Cost per Task (USD, Log Scale)
Costo
Cost per Intelligence Index Task
Velocidad y latencia
Output Speed
Puntuaciones de capacidades
Índices de capacidades
Incorporates 7 evaluations: AA-Omniscience, GDPval-AA v2.1, AA-Briefcase v1.1, Humanity's Last Exam, AutomationBench-AA, AA-LCR v1.1, GDP.pdf · Higher is better
Incorporates 6 evaluations: AA-Omniscience, GDPval-AA v2.1, AA-Briefcase v1.1, AutomationBench-AA, AA-LCR v1.1, GDP.pdf · Higher is better
Incorporates 7 evaluations: AA-Omniscience, GDPval-AA v2.1, AA-Briefcase v1.1, Humanity's Last Exam, AA-LCR v1.1, GDP.pdf, AutomationBench-AA · Higher is better
Incorporates 6 evaluations: AA-Omniscience, GDPval-AA v2.1, AA-Briefcase v1.1, MLCR-AA, Humanity's Last Exam, AutomationBench-AA · Higher is better
Incorporates 6 evaluations: AA-Omniscience, Humanity's Last Exam, CritPt, GDPval-AA v2.1, AA-Briefcase v1.1, Terminal-Bench 4.0 · Higher is better
Incorporates 5 evaluations: AA-Omniscience, Humanity's Last Exam, GDPval-AA v2.1, AA-Briefcase v1.1, AA-LCR v1.1 · Higher is better
Más detalles
Modalidad de entrada | Modalidad de salida | Pesos | Benchmarks de proveedores | ||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| EXAONE 4.5 33B |  LG AI Research | 13 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 34.4B | 262k | abr 2026 | - | Sí | Admite: texto e imágenes | Admite: texto | - | |||
| K2-V2 (high) |  Institute of Foundation Models | 10 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 70B | 512k | dic 2025 | - | Sí | Admite: texto | Admite: texto | - | |||
| K2-V2 (medium) | Institute of Foundation Models | 9 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 70B | 512k | dic 2025 | - | Sí | Admite: texto | Admite: texto | - | |||
| K2-V2 (low) | Institute of Foundation Models | 7 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 70B | 512k | dic 2025 | - | Sí | Admite: texto | Admite: texto | - | |||
| EXAONE 4.5 33B (Non-reasoning) | LG AI Research | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 34.4B | 262k | abr 2026 | - | No | Admite: texto e imágenes | Admite: texto | - | |||