DeepSeek
DeepSeek V4.1 Flash开源
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 评分方法.
API deployment
Compare hosts & latency
Throughput, TTFT and cache pricing across Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock and Azure.
GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
各榜单得分
分类能力得分
基准测试分项
模型详细参数
发布日期
2026年9月10日
参数量
552B (16B active)
开源协议
Open Weights
上下文窗口
1,000,000 tokens
输入价格
$0.3/M
输出价格
$1.2/M
输出速度
214 t/s
首Token延迟
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
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