DeepSeek-V4.1-Flash 在代码竞赛中排名上升

DeepSeek-V4.1-Flash by @deepseek_ai just landed ~#14 overall in Code Arena: WebDev with 1620 pts (Au...

DeepSeek-V4.1-Flash by @deepseek_ai just landed ~ #14 overall in Code Arena: WebDev with 1620 pts (AutoEval)! Among open models, DeepSeek-V4.1-Flash landed at ~ #4 within 11 pts of Qwen3.8-Flash-Next. This release is a significant improvement compared to DeepSeek-V4 variants: +38 pts vs. V4-Flash (High) at #20 (1582 pts) +40 pts vs. V4-Pro (High) #21 (1580 pts) DeepSeek-V4.1-Flash is within 5 pts of the models ranked #11 – #13 , while costing substantially less (priced per million input/output tokens): ~ #14 DeepSeek-V4.1-Flash: $0.30/ $1.20 #13 Hy4 Preview: $0.83/ $2.50 #12 Grok-4.6 High: $2/ $6 #11 Muse Spark 1.3 xHigh: $1.25/ $4.25 Note: this is an early AutoEval score, in which a Reward Model trained on Arena’s human preference data casts automatic votes in place of live votes. We’ll continue to see how scores converge as more live human votes come in. Congrats to the @deepseek_ai team on this contribution to the open source ecosystem! DeepSeek @deepseek_ai 🚀 Introducing DeepSeek-V4.1-Flash: smarter, faster, more efficient. 🔹 Introducing the smallest model in our new architecture family, with native visual understanding. 🔹 Designed for greater capability, faster inference, higher throughput, and scaling to larger models. 1/6 🔗 View Quoted Tweet 💬 12 🔄 13 ❤️ 177 👀 13227 📊 26 ⚡