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.

#317发布于 2026年9月10日·Open Weights·552B (16B active)
textimage1.0M ctxreasoning
API providers排行榜
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)
Coding (52)Mathematics (68)Hard Science (GPQA) (58)Agentic & Tool Use (48)Knowledge (MMLU) (46)Vision / Multimodal (50)

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
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各榜单得分

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
[![LLMPodium Rank](https://llmpodium.com/badge/deepseek-v4-1-flash/rank.svg)](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}
}

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