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DeepSeek V4.1 Flash

DeepSeek · DeepSeek series · released 10 Sep 2026 · as of 13 Nov, 20:12 UTC

62
02550751000 = all negative · 50 = neutral · 100 = all positive

Positive

Reddit reads DeepSeek V4.1 Flash as positive: an index of 62 from 203 opinions in 121 threads last 7 days, its whole 95% interval, 58–66, above neutral. That is 3rd of the 25 models with a full read. 5 points colder than the previous 7 days, within noise.

The share praising is highest for cost, 90% of 50 opinions; opinion on speed is split. On benchmarks: 28th of 128 on Arena text, 46th of 107 on the intelligence index.

Per day

The last 14 UTC days. Each day's own index at its value, with its 95% interval.

  1. Sat 31 Oct52
  2. Sun 1 Nov34
  3. Mon 2 Nov43
  4. Tue 3 Nov40
  5. Wed 4 Nov35
  6. Thu 5 Nov45
  7. Fri 6 Nov31
  8. Sat 7 Nov27
  9. Sun 8 Nov20
  10. Mon 9 Nov27
  11. Tue 10 Nov39
  12. Wed 11 Nov24
  13. Thu 12 Nov31
  14. Fri 13 Nov35 so far

None of the 3 full-read days this week stands apart from the rest of the week: each is within noise.

Is DeepSeek V4.1 Flash getting worse?

This measures opinion, not capability: whether Reddit's view of DeepSeek V4.1 Flash moved, not whether the model changed. Reddit's view has not moved by more than noise: 62 in the last 7 days against 67 in the 7 before, a gap of 5.0 points inside its 95% margin of ±5.0; a smaller shift can't be ruled out.

Praised and criticised

Share of the opinions on each topic that praise it. Tagged by a language model; topics never feed the index.

  1. Costmostly praised50
  2. Follow-throughsplit40
  3. Codingmostly praised35
  4. Intelligencesplit32
  5. Speedsplit31

Reddit and the benchmarks

Its rank on each list, bottom to top. Outside numbers sit beside Reddit and never feed its index. Hover a name for the value and its source.

  1. #3 of 25 with a full read
  2. #28 of 128 on Arena
  3. #23 of 94 on Arena
  4. #46 of 107 at Artificial Analysis
  5. #34 of 96 at Epoch

$0.028 in / $0.405 out per million tokens · 1.05M context · reasoning mode · OpenRouter, 17 Oct

Per subreddit

The model's index within each subreddit, from 10 opinions; faded below 30 opinions, 20 threads or 20 accounts.

  1. r/DeepSeek84
  2. r/LocalLLaMA42
  3. r/LocalLLM18
  4. r/ClaudeCode13

Threads behind the opinions

The 20 threads with the most opinions about this model. A thread's index reads the opinions in it, not the post, and shows from 10 opinions.

ThreadSubredditOpinionsIndex
DeepSeek V4.1 flash (1017) VS Gemini 3.1 pro and 3.8 flashr/DeepSeek9–
How would you compare Opus 5.5 to Deepseek Flash 4.1r/ClaudeCode8–
Same prompt, DeepSeek V4.1 Flash vs Qwen 3.8 FN: 94 tok/s vs 350 tok/sr/LocalLLaMA8–
i think these usa lab probably crack something look at the number dont forget aai updated 3 times in last months and still 65 and deepseek is around 33 . what happended recently, deepseek was 2 point behind in the 2025 now its more then 30 point behindin 5 commentsr/DeepSeek5–
Is DeepSeek V4.1 Flash getting upgrades? It built this walkable 3D yacht from one prompt for about $1.20r/DeepSeek5–
DeepSeek V4.1 Flash for penetration test with 7 agents 125M tokens cost me about $1 dollarin 4 commentsr/DeepSeek4–
12 hour unattended evaluation of DeepSeek 4.1 Flash 1017r/LocalLLaMA4–
DeepSeek V4.1 Flash failed after 1 hour — GPT-6 Astra finished in 7 minutes. Can fine-tuning help?r/opencodeCLI4–
How are you using DeepSeek-V4.1-Flash? [Claude Code user]r/DeepSeek4–
Is ArtificialAnalysis biased against open weight models?in 4 commentsr/LocalLLaMA4–
Deepseek v4.1 flash is now good enough to undertake huge engineering tasks autonomouslyr/DeepSeek4–
DeepSeek v4.1 Flash is PEAKr/DeepSeek4–
DSv4.1 Flash is absolutely destroying GPT 6.1 Terra for coding and video generationin 3 commentsr/DeepSeek3–
Deepseek 4.1 flash drew this for me, what do you think?in 3 commentsr/DeepSeek3–
Uncensored models are awesomer/LocalLLaMA3–
Cut tokens by ~70% for DeepSeek v4.1 Flash (Re-post)r/DeepSeek3–
Deepseek 4.1 is unusablein 3 commentsr/DeepSeek3–
Early testing Ember v Deepseek flash v4.1 1017r/DeepSeek3–
RustingStrata vs llama.cpp, DeepSeek-V4.1-Flash Q2 (249 GB) on a single RTX 3060 12 GB with 30 GB RAMr/LocalLLaMA3–
DeepSeek V4.1 Flash used REA to reverse-engineer a 1984 DOS game and rebuild it for Chrome, for $0.68r/DeepSeek3–

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