DeepSeek V4.1 Flash 1017 上线 Helmcode 并对比 Opus 5.5

Helmcode @helmcode原推发布于 2026.10.20

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🐳 @deepseek_ai V4.1 Flash 1017 is now on Helmcode too. Same size, same architecture. DeepSeek focused on getting more out of what the model already had, and the gains are impressive. From DeepSeek's model card: → Terminal-Bench 4.0: 31.2 → 42.3 → ProgramBench: 20.3 → 29.1 → Automation-Bench: 54.8 → 60.5 → DeepSWE v1.1: 74.2 → 77.0 Artificial Analysis points the same way. Its Intelligence Index goes from 39 to 45, and the average cost per evaluated task drops from $0.49 to $0.26 on its test suite. Around 47% less. We also wanted to see what it does with a real project, so we ran two tests on design and video! 1/ Signal / Noise. Same creative brief for DeepSeek V4.1 Flash 1017 and Claude Opus 5.5: design and build a website from scratch. Both got to a good result. Pretty impressive advance from DeepSeek, to be honest. You have a video comparing both solutions. 2/ A motion graphics piece about what happens when machines begin to dream. Built entirely in code, with no video generation model. Opus 5.5 level on video too for a piece of cost. Improvement from 1017 is savage! Haven't tried it? Give it a full project, let it use tools and check what it built, how long it took and what it consumed. You can use it with flat rate, zero-prompt retention and EU servers at Helmcode :) Full write-up and the video: https://helmcode.com/posts/deepseek-v41-flash-1017-whats-new Both websites, screen by screen: https://helmcode.com/design-challenge/001