DeepSeek R1 0528 (May '25)
DeepSeekDeepSeekOpen WeightMIT · Uso Comercial
Descripción
DeepSeek-R1-0528 is the May 28, 2025 version of DeepSeek's reasoning model. It features advanced thinking capabilities and serves as a benchmark comparison for newer models like DeepSeek-V3.1. This model excels in complex reasoning tasks, mathematical problem-solving, and code generation through its thinking mode approach.
Fecha de lanzamiento
2025-05-28
Parámetros
671.0B
Longitud del contexto
164K
Modalidades
text
Radar de capacidades
39
general
69
coding
83
reasoning
54
science
10
agents
0
multimodal
Rankings
| Dominio | #Posición | Puntuación | Fuente |
|---|---|---|---|
| Capacidad agéntica | 146 | 24.0 | LS |
| Ranking de codificación | 176 | 59.0 | AA |
| Ranking general | 275 | 46.0 | AA |
| Ciencia | 172 | 59.0 | AA |
Puntuaciones de benchmarks (LLM Stats)
(LLM Stats (zeroeval))Agents
t2-bench
80.2%Aut.
Terminal-Bench 2.0Stanford × Laude Institute (2026)
46.4%Aut.
Toolathlon
35.2%Aut.
BrowseCompOpenAI (2025)
8.9%Aut.
Terminal-Bench
5.7%Aut.
Biology
GPQANYU + Cohere + Anthropic (2023)
81.0%Aut.
Code
LiveCodeBench
73.3%Aut.
Aider-Polyglot
71.6%Aut.
SWE-Bench Verified
44.6%Aut.
SWE-bench Multilingual
30.5%Aut.
Factuality
SimpleQA
92.3%Aut.
Finance
MMLU-Pro
85.0%Aut.
General
MMLU-Redux
93.4%Aut.
Math
AIME 2024
91.4%Aut.
AIME 2025
87.5%Aut.
HMMT 2025
79.4%Aut.
CodeForces
0.64 / 3000Aut.
Humanity's Last Exam
17.7%Aut.
Reasoning
BrowseComp-zh
35.7%Aut.
Índices de evaluación AA
(Artificial Analysis)Math Index(Artificial Analysis)76.0
Intelligence Index(Artificial Analysis)20.4
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))1.0
Aime(MAA (Mathematical Association of America))0.9
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))0.8
Gpqa(NYU + Cohere + Anthropic (2023))0.8
Livecodebench(UC Berkeley + MIT + Cornell (2024))0.8
Aime 25(MAA (Mathematical Association of America))0.8
Lcr(Artificial Analysis)0.6
Scicode(UIUC + Argonne National Lab (2024))0.4
Ifbench(Google Research (2023))0.4
Tau2(Sierra + U Toronto + Vector Institute (2025))0.4
Terminalbench Hard(Stanford × Laude Institute (2026))0.2
Hle(Center for AI Safety + Scale AI (2025))0.2
Puntuaciones por categoría LLM Stats
(LLM Stats (zeroeval))Language90
Factuality90
Legal80
Physics80
Finance80
Healthcare80
Biology80
Chemistry80
Math70
Reasoning60
General60
Code50
Frontend Development40
Search20
Vision20
Agents10
Precios
Precio de entrada$1.35 / 1M tokens
Precio de salida$4.2 / 1M tokens
Precio mixto (3:1)$2.063 / 1M tokens
Precio de lectura caché$0.35 / 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: NanoGPTMás caro: Azure
ProveedorEntradaSalida
1NanoGPTMás barato
$0.4
$1.7
2OpenRouter
$0.5
$2.15
3Alibaba (China)
$0.574
$2.294
4TensorX
$0.66
$2.6
5Jiekou.AI
$0.7
$2.5
6NovitaAI
$0.7
$2.5
7Kilo Gateway
$0.7
$2.5
8DeepSeekPRINCIPAL
$1.35
$4.2
9Azure Cognitive Services
$1.35
$5.4
10Azure
$1.35
$5.4
Comparar precios entre diferentes proveedores de API para este modelo.