DeepSeek
DeepSeek V4.1 Flash오픈소스
DeepSeek V4.1 Flash is an open-weights MoE reasoning model with 552B total (16B active) parameters, 1.0M context, and chain-of-thought problem solving.
Intelligence
54.5 #317
AAQI 40.0
Output speed
214.4 t/s
TTFT 1.21 s · ITL 4.7 ms/tok
Blended price (3:1)
$0.18 /1M
In $0.3/M · Out $1.2/M
Context
1.0M
≈ 2,500 A4 pages · max out 32768
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
DeepSeek V4.1 Flash
Claude Mythos Preview (#1)
Average (68)
Radar axes are approximated from category scores where direct benchmark measurements are missing — see 평가 방법.
API deployment
Compare hosts & latency
Throughput, TTFT and cache pricing across Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock and Azure.
GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
출처별 점수
카테고리별 점수
벤치마크 결과
모델 상세 정보
출시일
2026년 9월 10일
파라미터 수
552B (16B active)
라이선스
Open Weights
컨텍스트 창
1,000,000 tokens
입력 가격
$0.3/M
출력 가격
$1.2/M
출력 속도
214 t/s
첫 토큰 생성 시간
1.21 s
Estimated monthly bill
Estimated monthly spend
$0.00
Calculating savings vs GPT-4o...
Cite & embed
GitHub Markdown badge
[](https://llmpodium.com/models/deepseek-v4-1-flash)BibTeX
@misc{llmpodium2026deepseekv41flash,
title = {Benchmark Analysis and Intelligence Evaluation of DeepSeek V4.1 Flash},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/deepseek-v4-1-flash}
}More from DeepSeek
대체 모델
성능, 가격 및 벤치마크 점수를 기반으로 한 DeepSeek V4.1 Flash의 주요 대체 모델.