Kimi K2.5 (Non-reasoning)
KimiKimiOpen WeightMIT · Uso Comercial
Descripción
Kimi K2.5 is Moonshot AI's flagship agentic model and a new SOTA open model. It unifies vision and text, thinking and non-thinking modes, and single-agent and multi-agent execution into one model. Built with Full-Parameter RL tuning, it achieves state-of-the-art performance across agents, coding, image, and video benchmarks.
Fecha de lanzamiento
2026-01-27
Parámetros
1.0T
Longitud del contexto
262K
Modalidades
image, text, video
Radar de capacidades
18
general
50
coding
79
reasoning
59
science
50
agents
80
multimodal
Rankings
| Dominio | #Posición | Puntuación | Fuente |
|---|---|---|---|
| Ranking de codificación | 285 | 53.0 | AA |
| Ranking general | 255 | 47.0 | AA |
| Ranking multimodal | 23 | 62.0 | LS |
| Ciencia | 261 | 50.0 | AA |
Puntuaciones de benchmarks (LLM Stats)
(LLM Stats (zeroeval))Code
PaperBench
63.5%Aut.
CyberGym
41.3%Aut.
FrontierSWE
26.0%
Finance
FinSearchComp T2&T3
67.8%Aut.
Language
MMLU-Pro
87.1%Aut.
Long Context
LongBench v2
61.0%Aut.
Math
AIME 2025
96.1%Aut.
HMMT 2025
95.4%Aut.
MathVista-Mini
90.1%Aut.
MathVision
84.2%Aut.
IMO-AnswerBench
81.8%Aut.
LiveBench
69.1%
Multimodal
Video-MME
87.4%Aut.
VideoMMMU
86.6%Aut.
Reasoning
GPQANYU + Cohere + Anthropic (2023)
87.6%Aut.
LiveCodeBench v6
85.0%Aut.
CharXiv-R
77.5%Aut.
SWE-Bench Verified
76.8%Aut.
BrowseCompOpenAI (2025)
74.9%Aut.
SWE-bench Multilingual
73.0%Aut.
AA-LCR
70.0%Aut.
OJBench (C++)
57.4%Aut.
Seal-0
57.4%Aut.
Terminal-Bench 2.0Stanford × Laude Institute (2026)
50.8%Aut.
SWE-Bench ProPrinceton NLP (2024)
50.7%Aut.
Humanity's Last Exam
50.2%Aut.
SciCode
48.7%Aut.
Search
WideSearch
79.0%Aut.
DeepSearchQA
77.1%Aut.
Vision
InfoVQAtest
92.6%Aut.
OCRBench
92.3%Aut.
OmniDocBench 1.5
88.8%Aut.
MMVU
80.4%Aut.
LongVideoBench
79.8%Aut.
MMMU-Pro
78.5%Aut.
LVBench
75.9%Aut.
SimpleVQA
0.71 / 100Aut.
MotionBench
70.4%Aut.
WorldVQA
46.3%Aut.
ZEROBench
0.11 / 100Aut.
Índices de evaluación AA
(Artificial Analysis)Tau2(Sierra + U Toronto + Vector Institute (2025))81.3
Gpqa(NYU + Cohere + Anthropic (2023))78.9
Lcr(Artificial Analysis)67.3
Ifbench(Google Research (2023))43.7
Intelligence Index(Artificial Analysis)19.4
Terminalbench Hard(Stanford × Laude Institute (2026))18.9
Hle(Center for AI Safety + Scale AI (2025))13.2
Puntuaciones por categoría LLM Stats
(LLM Stats (zeroeval))Language90
Legal90
Finance90
Image To Text80
Long Context80
Math80
Frontend Development80
Video80
Multimodal70
Physics70
Reasoning70
Search70
Structured Output70
General70
Healthcare70
Biology70
Chemistry70
Vision70
Agents60
Code50
Tool Calling50
Safety40
Precios
Precio de entrada$0.6 / 1M tokens
Precio de salida$3 / 1M tokens
Precio mixto (3:1)$1.2 / 1M tokens
Precio de lectura caché$0.07 / 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
11 proveedores
Más barato: NanoGPTMás caro: Ofox
ProveedorEntradaSalida
1NanoGPTMás barato
$0.3
$1.9
2OpenRouter
$0.45
$2.25
3TensorX
$0.5
$2.8
4ZenMux
$0.58
$3.02
5KimiPRINCIPAL
$0.6
$3
6Jiekou.AI
$0.6
$3
7NovitaAI
$0.6
$3
8Kilo Gateway
$0.6
$3
9Vercel AI Gateway
$0.6
$3
10HPC-AI
$0.6
$3
11Ofox
$0.6
$3
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