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Derp Learning

Derp Learning

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Используем ИИ строго не по назначению. Заметки про ИИ, IT, компьютерные игры, и всякие инженерные интересности.

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📈 Analytical overview of Telegram channel Derp Learning

Channel Derp Learning (@derplearning) in the Russian language segment is an active participant. Currently, the community unites 13 846 subscribers, ranking 8 952 in the Technologies & Applications category and 46 870 in the Russia region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 13 846 subscribers.

According to the latest data from 26 August, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 69 over the last 30 days and by 3 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 33.62%. Within the first 24 hours after publication, content typically collects 16.00% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 4 656 views. Within the first day, a publication typically gains 2 215 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 77.
  • Thematic interests: Content is focused on key topics such as git, wan, gpu, sparse, вайбкодинг.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
Используем ИИ строго не по назначению. Заметки про ИИ, IT, компьютерные игры, и всякие инженерные интересности.

Thanks to the high frequency of updates (latest data received on 27 August, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

13 846
Subscribers
+324 hours
-67 days
+6930 days
Attracting Subscribers
August '26
August '26
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in 5 channels
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+204
in 11 channels
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June '26
+219
in 8 channels
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May '26
+317
in 11 channels
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April '26
+308
in 13 channels
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March '26
+496
in 12 channels
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February '26
+318
in 15 channels
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January '26
+163
in 12 channels
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December '25
+128
in 9 channels
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November '25
+155
in 5 channels
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October '25
+117
in 2 channels
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September '25
+222
in 16 channels
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August '25
+201
in 6 channels
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July '25
+301
in 11 channels
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June '25
+333
in 21 channels
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May '25
+179
in 2 channels
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April '25
+270
in 9 channels
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March '25
+331
in 5 channels
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February '25
+306
in 8 channels
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January '25
+137
in 2 channels
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December '24
+158
in 3 channels
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November '24
+212
in 16 channels
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October '24
+250
in 11 channels
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September '24
+250
in 7 channels
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August '24
+236
in 6 channels
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July '24
+286
in 6 channels
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June '24
+247
in 7 channels
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May '24
+349
in 4 channels
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April '24
+672
in 16 channels
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March '24
+377
in 3 channels
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February '24
+580
in 19 channels
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January '24
+558
in 6 channels
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December '23
+621
in 18 channels
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November '23
+265
in 10 channels
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October '23
+334
in 14 channels
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+148
in 0 channels
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+146
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March '23
+256
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February '23
+421
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January '23
+442
in 0 channels
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December '22
+535
in 0 channels
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November '22
+378
in 0 channels
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October '22
+308
in 0 channels
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September '22
+277
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+351
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July '22
+577
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June '22
+437
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+435
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April '22
+438
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March '22
+325
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February '22
+1 206
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January '22
+3 742
in 0 channels
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December '21
+1 359
in 0 channels
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November '21
+522
in 0 channels
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October '21
+459
in 0 channels
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September '21
+118
in 0 channels
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August '21
+216
in 0 channels
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July '21
+80
in 0 channels
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June '21
+313
in 0 channels
Date
Subscriber Growth
Mentions
Channels
27 August+1
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25 August+5
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11 August+8
10 August+8
09 August+1
08 August+8
07 August+8
06 August+5
05 August+8
04 August+4
03 August+3
02 August+4
01 August+6
Channel Posts

2
GLM-5.3-flash (320b): выходит Qwen-3.8-flash-next:+1
GLM-5.3-flash (320b): выходит Qwen-3.8-flash-next:
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3
Не успел выйти Qwen3.8-flash-next, Unsloth уже грузит кванты :D https://huggingface.co/unsloth/Qwen3.8-Flash-Next-GGUF
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Hugging face у нас дома (в Поднебесной) тизерит новый qwen3.8-next-flash. X
Hugging face у нас дома (в Поднебесной) тизерит новый qwen3.8-next-flash. X
2 047
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9
Полгода работы прошли не зря! У нас (Keenable) публичный запуск. Новый сайт: https://keenable.ai/ Новый бенч: https://keenabl
Полгода работы прошли не зря! У нас (Keenable) публичный запуск. Новый сайт: https://keenable.ai/ Новый бенч: https://keenableai.github.io/needle/ Твит: https://x.com/styskin/status/2092265673041084505 Пост про бенч будет на неделе. Ещё будет одна прикольная штука, которая называется Web Query Language.
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Еще интересный подход - взять драфтер токенов не из самого чекпоинта, а DFlash2 отсюда - Qwen3.8-27B-DFlash2-GGUF Для этого придется собрать llama.cpp: git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp git fetch origin pull/27342/head:pr-27342 git switch pr-27342 # NVIDIA CUDA cmake -B build -DCMAKE_BUILD_TYPE=Release -DGGML_CUDA=ON cmake --build build -j # Apple Silicon cmake -B build -DCMAKE_BUILD_TYPE=Release -DGGML_METAL=ON cmake --build build -j Зато потом получаем 36.77 t/s с контекстом 100535 -> 52.15 t/s / 95k ctx llama-server.exe -m "Qwen3.8-27B-UD-Q3_K_XL.gguf" -md "Qwen3.8-27B-DFlash2-Q4_K_M.gguf" --alias qwen38 --port 8080 --ctx-size 95536 -ngl 99 -ngld 99 -fa on --cache-type-k q4_0 --cache-type-v q4_0 --jinja --reasoning-effort medium --no-context-shift --cache-reuse 256 --spec-type draft-dflash --spec-draft-n-max 3 -b 2048 -ub 512 --temp 1.0 --top-p 0.95 --top-k 20 --min-p 0.0 --tools all --parallel 1
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thanks, 🧢
thanks, 🧢
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люблю когда есть свобода выбора
люблю когда есть свобода выбора
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Наконец дошли руки поковырять Qwen 3.8-27b Как говорится, мое увожение. На мои 16гб комфортно влез Qwen3.8-27B-UD-Q3_K_XL от unsloth --ctx-size 100535 -ngl 99 -fa on --cache-type-k q4_0 --cache-type-v q4_0 --jinja --reasoning-effort medium --no-context-shift --cache-reuse 256 --spec-type draft-mtp --spec-draft-n-max 1 -b 2048 -ub 512 --temp 1.0 --top-p 0.95 --top-k 20 --min-p 0.0 --tools all выдает 36.77 t/s с контекстом 100535 Еще есть интересный дистилл Qwen3.8-2.4T-A95B -> Qwen 3.5 9b С Qwen3.8-9B-Q8_0 и конфигом --ctx-size 262144 -ngl 99 -fa on --cache-type-k q8_0 --cache-type-v q8_0 --jinja --reasoning-effort low --no-context-shift --cache-reuse 256 --spec-type draft-mtp --spec-draft-n-max 3 -b 2048 -ub 512 --temp 1.0 --top-p 0.95 --top-k 20 --min-p 0.0 --tools all выдает 85+ t/s с контекстом 262144 В llama.cpp ui / aider ваншотят игры вроде scorched earth, но 9b модель чаще спотыкается. Можно гонять и через claude code/codex, но codex использует новый более сырой апи и одним своим системным промтом сжирает 20к+ токенов :D llama.cpp тут
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Таким должен был быть трейлер Red Alert 2 Ладно, забирайте эту вашу оперативку x автор: https://www.douyin.com, lyxw1327
Таким должен был быть трейлер Red Alert 2 Ладно, забирайте эту вашу оперативку x автор: https://www.douyin.com, lyxw1327
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