Kimi K2 0905
KimiKimiProprietary
Descripción
Kimi K2 0905 is the September update of Kimi K2 0711. It is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It supports long-context inference up to 256k tokens, extended from the previous 128k. This update improves agentic coding with higher accuracy and better generalization across scaffolds, and enhances frontend coding with more aesthetic and functional outputs for web, 3D, and related tasks. The model is trained with a novel stack incorporating the MuonClip optimizer for stable large-scale MoE training.
Fecha de lanzamiento
2025-09-05
Parámetros
1.0T
Longitud del contexto
262K
Modalidades
text
Radar de capacidades
39
general
54
coding
61
reasoning
47
science
59
agents
0
multimodal
Rankings
| Dominio | #Posición | Puntuación | Fuente |
|---|---|---|---|
| Ranking de codificación | 186 | 55.0 | AA |
| Ranking general | 191 | 56.0 | AA |
| Ciencia | 271 | 47.0 | AA |
Puntuaciones de benchmarks (LLM Stats)
(LLM Stats (zeroeval))Biology
GPQANYU + Cohere + Anthropic (2023)
75.8%Aut.
Code
HumanEvalOpenAI (2021)
94.5%Aut.
Finance
MMLU
90.2%Aut.
MMLU-Pro
82.5%Aut.
Math
MATH
89.1%Aut.
AIME 2024
72.0%Aut.
Índices de evaluación AA
(Artificial Analysis)Math Index(Artificial Analysis)57.3
Intelligence Index(Artificial Analysis)24.0
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))0.8
Gpqa(NYU + Cohere + Anthropic (2023))0.8
Tau2(Sierra + U Toronto + Vector Institute (2025))0.7
Livecodebench(UC Berkeley + MIT + Cornell (2024))0.6
Aime 25(MAA (Mathematical Association of America))0.6
Lcr(Artificial Analysis)0.5
Ifbench(Google Research (2023))0.4
Scicode(UIUC + Argonne National Lab (2024))0.3
Terminalbench Hard(Stanford × Laude Institute (2026))0.2
Hle(Center for AI Safety + Scale AI (2025))0.1
Puntuaciones por categoría LLM Stats
(LLM Stats (zeroeval))Legal90
Language90
Finance90
Healthcare90
Code90
Math80
Physics80
Reasoning80
General80
Biology80
Chemistry80
Precios
Precio de entrada$0.6 / 1M tokens
Precio de salida$2.5 / 1M tokens
Precio mixto (3:1)$1.075 / 1M tokens
Velocidad
Tokens/seg0.0
Retraso del primer token0.00s
Tiempo hasta la respuesta0.00s
Ranking de Precios por Proveedor
Ranking de Precios por Proveedor
10 proveedores
Más barato: HeliconeMás caro: 302.AI
ProveedorEntradaSalida
1HeliconeMás barato
$0.5
$2
2KimiPRINCIPAL
$0.6
$2.5
3OpenRouter
$0.6
$2.5
4Jiekou.AI
$0.6
$2.5
5ZenMux
$0.6
$2.5
6NovitaAI
$0.6
$2.5
7Kilo Gateway
$0.6
$2.5
8Moonshot AI (China)
$0.6
$2.5
9Moonshot AI
$0.6
$2.5
10302.AI
$0.632
$2.53
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