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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

41
general
55
coding
62
reasoning
50
science
50
agents
0
multimodal

Rankings

Dominio#PosiciónPuntuaciónFuente
Capacidad agéntica135
31.0
LS
Ranking de codificación185
55.0
AA
Ranking general154
61.0
AA
Ciencia208
53.0
AA

Puntuaciones de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Agents

t2-bench80.3%Aut.
Terminal-Bench 2.0Stanford × Laude Institute (2026)46.4%Aut.
MCP-Universe45.9%Aut.
BrowseCompOpenAI (2025)40.1%Aut.
MCP-Mark38.0%Aut.
Terminal-Bench37.7%Aut.
Toolathlon35.2%Aut.

Biology

GPQANYU + Cohere + Anthropic (2023)79.9%Aut.

Code

Aider-Polyglot74.5%Aut.
LiveCodeBench74.1%Aut.
SWE-Bench Verified67.8%Aut.
SWE-bench Multilingual57.9%Aut.

Factuality

SimpleQA97.1%Aut.

Finance

MMLU-Pro85.0%Aut.

Math

AIME 202589.3%Aut.
HMMT 202583.6%Aut.
IMO-AnswerBench78.3%Aut.
CodeForces0.71 / 3000Aut.
Humanity's Last Exam19.8%Aut.

Reasoning

BrowseComp-zh47.9%Aut.

Índices de evaluación AA

(Artificial Analysis)
Math Index(Artificial Analysis)
59.0
Intelligence Index(Artificial Analysis)
25.1
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.8
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.8
Gpqa(NYU + Cohere + Anthropic (2023))
0.8
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.6
Aime 25(MAA (Mathematical Association of America))
0.6
Ifbench(Google Research (2023))
0.5
Lcr(Artificial Analysis)
0.4
Scicode(UIUC + Argonne National Lab (2024))
0.4
Terminalbench Hard(Stanford × Laude Institute (2026))
0.3
Hle(Center for AI Safety + Scale AI (2025))
0.1

Puntuaciones por categoría LLM Stats

(LLM Stats (zeroeval))
Language
80
Legal
80
Math
80
Physics
80
Finance
80
Healthcare
80
Biology
80
Chemistry
80
Reasoning
70
Frontend Development
70
General
70
Code
70
Search
60
Agents
50
Tool Calling
50
Vision
40

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$0.1345 / 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

2 proveedores

Más barato: DeepSeekMás caro: EmpirioLabs AI
ProveedorEntradaSalida
1DeepSeekPRINCIPAL
$0.28
$0.42
2EmpirioLabs AI
$0.57
$1.71

Comparar precios entre diferentes proveedores de API para este modelo.

Fuentes externas