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DeepSeek V3.1 (Non-reasoning)

DeepSeekDeepSeek오픈 웨이트MIT · 상업적 사용 가능

설명

DeepSeek-V3.1 is a hybrid model supporting both thinking and non-thinking modes through different chat templates. Built on DeepSeek-V3.1-Base with a two-phase long context extension (32K phase: 630B tokens, 128K phase: 209B tokens), it features 671B total parameters with 37B activated. Key improvements include smarter tool calling through post-training optimization, higher thinking efficiency achieving comparable quality to DeepSeek-R1-0528 while responding more quickly, and UE8M0 FP8 scale data format for model weights and activations. The model excels in both reasoning tasks (thinking mode) and practical applications (non-thinking mode), with particularly strong performance in code agent tasks, math competitions, and search-based problem solving.

출시일
2025-08-21
파라미터
671.0B
컨텍스트 길이
164K
모달리티
text

능력 레이더

34
general
58
coding
54
reasoning
53
science
30
agents
0
multimodal

랭킹

도메인#순위점수소스
코딩 랭킹295
51.0
AA
종합 랭킹325
41.0
AA
과학348
42.0
AA

벤치마크 점수 (LLM Stats)

(LLM Stats (zeroeval))

Factuality

SimpleQA93.4%자체 보고

General

Aider-Polyglot68.4%자체 보고

Language

MMLU-Redux91.8%자체 보고
MMLU-Pro83.7%자체 보고

Math

CodeForces0.70 / 3000자체 보고
AIME 202466.3%자체 보고
AIME 202549.8%자체 보고
HMMT 202533.5%자체 보고

Reasoning

GPQANYU + Cohere + Anthropic (2023)74.9%자체 보고
SWE-Bench Verified66.0%자체 보고
LiveCodeBench56.4%자체 보고
SWE-bench Multilingual54.5%자체 보고
BrowseComp-zh49.2%자체 보고
Terminal-Bench31.3%자체 보고
BrowseCompOpenAI (2025)30.0%자체 보고
Humanity's Last Exam15.9%자체 보고

AA 평가 지수

(Artificial Analysis)
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
83.3
Gpqa(NYU + Cohere + Anthropic (2023))
73.5
Livecodebench(UC Berkeley + MIT + Cornell (2024))
57.7
Math Index(Artificial Analysis)
49.7
Aime 25(MAA (Mathematical Association of America))
49.7
Lcr(Artificial Analysis)
47.0
Ifbench(Google Research (2023))
37.8
Tau2(Sierra + U Toronto + Vector Institute (2025))
34.8
Terminalbench Hard(Stanford × Laude Institute (2026))
24.2
Intelligence Index(Artificial Analysis)
13.7
Hle(Center for AI Safety + Scale AI (2025))
6.7

LLM Stats 카테고리 점수

(LLM Stats (zeroeval))
Language
90
Factuality
90
Legal
80
Finance
80
Healthcare
80
Physics
70
Frontend Development
70
Biology
70
Chemistry
70
Math
60
Reasoning
60
General
60
Code
60
Search
40
Agents
30
Vision
20

가격

입력 가격$0.56 / 1M 토큰
출력 가격$1.68 / 1M 토큰
혼합 가격 (3:1)$0.84 / 1M 토큰
캐시 읽기 가격$0.13 / 1M 토큰

속도

토큰/초0.0
첫 토큰 지연0.00s
첫 응답 지연0.00s

공급자 가격 순위

공급자 가격 순위

3개 공급자

최저가: DeepInfra최고가: Alibaba (China)
공급자입력출력
1DeepInfra최저가
$0
$0
2DeepSeek주요
$0.56
$1.68
3Alibaba (China)
$0.574
$1.721

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