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deepseek-v4.1IMAGE

Signal65 评测:1017 默认档追平原版最高档,错误少 45%

Signal65 称 V4.1-Flash-1017 在默认推理档就达到原版最高档分数,加权错误少 45%,每正确答案输出 token 从 347,031 降到 20,829;单台 8×B300 撑 312 个并发 agent,正确任务成本 $0.15。

Signal65
@Signal_651 天前收录原推发布于 2026.10.27
Signal65 评测:1017 默认档追平原版最高档,错误少 45%(第 1 张,共 2 张)
Signal65 评测:1017 默认档追平原版最高档,错误少 45%(第 2 张,共 2 张)
Signal65 @Signal_65原推发布于 2026.10.27
在 X 上打开原推

Enterprises that passed on @deepseek_ai V4.1-Flash because it needed max reasoning effort to score well should look at the October refresh. DeepSeek-V4.1-Flash-1017 reaches the original's max-effort score at its default effort, sustains more concurrent agents on one node than any other model above a 4,000 PINNACLE Model Score, and lands on the open-weight cost frontier. In our testing: ➡️ At default effort the 1017 build makes 45% fewer weighted errors than the original V4.1-Flash at the same setting, and matches the original's max-effort result with 94% fewer output tokens per correct answer (20,829 against 347,031) in 27 median rounds instead of 43.5 ➡️ Against the July V4-Flash-0731 it makes 33% fewer weighted errors, with fabrication on the 128K corpus down from 7.0% to 2.1% ➡️ On one 8× NVIDIA B300 node it holds 312 concurrent agents at 10 tok/s each, the most of any row above 4,000 on the board, which puts a correct task at $0.15 and 516 correct tasks per node-hour; Productivity #2 of 41 open-weight rows ➡️ That price lands it on the open-weight cost frontier, the cheapest open-weight correct task above 4,000, 28% less than Qwen3.8-Flash-Next for 84% of its score, and below GPT-6 Sol medium at a higher score Hosted rows are a separate question: Claude Haiku 5.5 and GPT-6 Luna remain cheaper than every open-weight row on the overall frontier. For an enterprise committed to open weights, DeepSeek-1017 is the new price for a correct task at this level of capability. Live on the Model Score and cost views at http://pinnacle.signal65.com

x.com/signal_65/status/2114838229279297700采集于 2026.10.27 12:08