Hands-on gripes with DeepSeek V4.1-Flash-1017: hallucinations, speed, harness dependence
Five hands-on complaints: hallucinations still need a second model to check; fewer tokens doesn't mean faster; quality depends heavily on the harness; multi-file refactors need a stronger planner; Search+Fetch starts charging per call Nov 1.
a few things i don’t like about DeepSeek V4.1-Flash-1017 so far: 1. hallucinations are still the biggest issue. i wouldn’t trust it to approve its own architectural changes without a second model checking the work. 2. “faster” is a bit misleading. the model can finish tasks with fewer tokens, but that doesn’t always mean higher tokens/sec, and in some tests 1017 actually feels slower. 3. the quality still depends heavily on the harness. DeepSeek specifically optimized 1017 for a few environments, which means the same model may not feel equally good everywhere. 4. complex multi-file refactors are still where i’m most cautious. it can implement fast, but once the task crosses architectural boundaries i want a stronger planner involved. 5. the new Search + Fetch stack is useful, but it’s another dependency that will start charging per call on November 1. cheap, yes: free, no. 1017 is clearly better. but it still works best for me as a very fast worker, not the final authority.
This post quotes another post: “DeepSeek V4.1-Flash-1017: first hands-on observations”