DeepSeek V3.2 (Non-reasoning)
DeepSeekDeepSeekOpen WeightMIT · Uso Comercial
Descripción
DeepSeek-V3.2 is a 685B-parameter MoE model that harmonizes high computational efficiency with superior reasoning and agent performance. It introduces DeepSeek Sparse Attention (DSA) for efficient long-context processing, a scalable reinforcement learning post-training framework, and large-scale agentic task synthesis covering 1,800+ environments. V3.2 achieves GPT-5-level performance across reasoning, coding, and agentic benchmarks, with gold-medal results from its Speciale variant on IMO, IOI, ICPC World Finals, and CMO 2025.
Fecha de lanzamiento
2025-12-01
Parámetros
685.0B
Longitud del contexto
164K
Modalidades
text
Radar de capacidades
36
general
59
coding
62
reasoning
55
science
50
agents
0
multimodal
Rankings
| Dominio | #Posición | Puntuación | Fuente |
|---|---|---|---|
| Capacidad agéntica | 94 | 36.0 | LS |
| Ranking de codificación | 270 | 55.0 | AA |
| Ranking general | 198 | 55.0 | AA |
| Ciencia | 306 | 46.0 | AA |
Puntuaciones de benchmarks (LLM Stats)
(LLM Stats (zeroeval))Agents
t2-bench
80.3%Aut.
MCP-Universe
45.9%Aut.
MCP-Mark
38.0%Aut.
Toolathlon
35.2%Aut.
Factuality
SimpleQA
97.1%Aut.
General
Aider-Polyglot
74.5%Aut.
Language
MMLU-Pro
85.0%Aut.
Math
AIME 2025
89.3%Aut.
HMMT 2025
83.6%Aut.
IMO-AnswerBench
78.3%Aut.
CodeForces
0.71 / 3000Aut.
Reasoning
GPQANYU + Cohere + Anthropic (2023)
79.9%Aut.
LiveCodeBench
74.1%Aut.
SWE-Bench Verified
67.8%Aut.
SWE-bench Multilingual
57.9%Aut.
BrowseComp-zh
47.9%Aut.
Terminal-Bench 2.0Stanford × Laude Institute (2026)
46.4%Aut.
BrowseCompOpenAI (2025)
40.1%Aut.
Terminal-Bench
37.7%Aut.
Humanity's Last Exam
19.8%Aut.
Índices de evaluación AA
(Artificial Analysis)Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))83.7
Tau2(Sierra + U Toronto + Vector Institute (2025))78.9
Gpqa(NYU + Cohere + Anthropic (2023))75.1
Livecodebench(UC Berkeley + MIT + Cornell (2024))59.3
Math Index(Artificial Analysis)59.0
Aime 25(MAA (Mathematical Association of America))59.0
Ifbench(Google Research (2023))49.0
Lcr(Artificial Analysis)45.7
Terminalbench Hard(Stanford × Laude Institute (2026))32.6
Intelligence Index(Artificial Analysis)16.0
Hle(Center for AI Safety + Scale AI (2025))11.2
Puntuaciones por categoría LLM Stats
(LLM Stats (zeroeval))Language80
Legal80
Math80
Physics80
Finance80
Healthcare80
Biology80
Chemistry80
Reasoning70
Frontend Development70
General70
Code70
Search60
Agents50
Tool Calling50
Vision40
Precios
Precio de entrada$0.28 / 1M tokens
Precio de salida$0.42 / 1M tokens
Precio mixto (3:1)$0.315 / 1M tokens
Precio de lectura caché$0.028 / 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
13 proveedores
Más barato: DeepInfraMás caro: Vercel AI Gateway
ProveedorEntradaSalida
1DeepInfraMás barato
$0
$0
2TokenGo
$0.2174
$0.326
3NovitaAI
$0.269
$0.4
4DeepSeekPRINCIPAL
$0.28
$0.42
5NanoGPT
$0.28
$0.42
6OpenRouter
$0.28
$0.42
7ZenMux
$0.28
$0.43
8Kilo Gateway
$0.28
$0.42
9Merge Gateway
$0.28
$0.4
10Ofox
$0.29
$0.43
11TensorX
$0.3
$0.5
12EmpirioLabs AI
$0.57
$1.71
13Vercel AI Gateway
$0.62
$1.85
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