Anbeeld/beellama.cpp

KVarN, KV cache precision tail, low-bit quants in llama.cpp for longer context of better precision in the same VRAM

C++

1.2k

101

0

MIT License

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How fast Anbeeld/beellama.cpp is gaining stars, and where it lands on Trendshift and GitHub Trending

Activity and trending

Stars, forks and merged pull requests each day or month, lined up with the repository's rank on Trendshift Trending

Sep 7 – Nov 6, 2026

Stars +156 in 61 days

16

Forks +28 in 61 days

3

Merged PRs 7 in 61 days

5

Trendshift Trendingwhere the repository ranked each day it made the top 25

Not in the Trendshift top 25 in this period

Sep 7Sep 15Sep 23Oct 1Oct 9Oct 17Oct 25Nov 2

Stars, forks, merged pull requests and Trendshift Trending rank, by day
Day	Stars gained	Forks gained	Merged PRs
Mon, Sep 7, 2026	+16	+3	0
Tue, Sep 8, 2026	+5	+1	0
Wed, Sep 9, 2026	+7	+0	0
Thu, Sep 10, 2026	+7	+0	0
Fri, Sep 11, 2026	+3	+0	1
Sat, Sep 12, 2026	+3	+3	5
Sun, Sep 13, 2026	+5	+1	0
Mon, Sep 14, 2026	+4	+1	0
Tue, Sep 15, 2026	+5	+1	0
Wed, Sep 16, 2026	+2	+1	0
Thu, Sep 17, 2026	+2	+2	0
Fri, Sep 18, 2026	+3	+0	0
Sat, Sep 19, 2026	+5	+0	0
Sun, Sep 20, 2026	+3	+0	0
Mon, Sep 21, 2026	+3	+0	0
Tue, Sep 22, 2026	+9	+0	0
Wed, Sep 23, 2026	+3	+1	0
Thu, Sep 24, 2026	+3	+1	0
Fri, Sep 25, 2026	+0	+1	0
Sat, Sep 26, 2026	+3	+1	0
Sun, Sep 27, 2026	+4	+0	0
Mon, Sep 28, 2026	+3	+1	0
Tue, Sep 29, 2026	+5	+0	0
Wed, Sep 30, 2026	+6	+0	0
Thu, Oct 1, 2026	+2	+0	0
Fri, Oct 2, 2026	+1	+0	0
Sat, Oct 3, 2026	+2	+0	0
Sun, Oct 4, 2026	+1	+0	0
Mon, Oct 5, 2026	+1	+0	0
Tue, Oct 6, 2026	+2	+0	0
Wed, Oct 7, 2026	+0	+0	0
Thu, Oct 8, 2026	+0	+0	0
Fri, Oct 9, 2026	+1	+0	0
Sat, Oct 10, 2026	+0	+0	0
Sun, Oct 11, 2026	+2	+2	0
Mon, Oct 12, 2026	+2	+0	1
Tue, Oct 13, 2026	+0	+0	0
Wed, Oct 14, 2026	+3	+0	0
Thu, Oct 15, 2026	+2	+1	0
Fri, Oct 16, 2026	+5	+0	0
Sat, Oct 17, 2026	+0	+0	0
Sun, Oct 18, 2026	+1	+0	0
Mon, Oct 19, 2026	+2	+0	0
Tue, Oct 20, 2026	+1	+0	0
Wed, Oct 21, 2026	+0	+0	0
Thu, Oct 22, 2026	+2	+0	0
Fri, Oct 23, 2026	+0	+0	0
Sat, Oct 24, 2026	+3	+0	0
Sun, Oct 25, 2026	+3	+1	0
Mon, Oct 26, 2026	+0	+1	0
Tue, Oct 27, 2026	+0	+1	0
Wed, Oct 28, 2026	+1	+0	0
Thu, Oct 29, 2026	+1	+1	0
Fri, Oct 30, 2026	+0	+0	0
Sat, Oct 31, 2026	+0	+1	0
Sun, Nov 1, 2026	+2	+0	0
Mon, Nov 2, 2026	+0	+1	0
Tue, Nov 3, 2026	+2	+0	0
Wed, Nov 4, 2026	+0	+0	0
Thu, Nov 5, 2026	+3	+1	0
Fri, Nov 6, 2026	+2	+0	0
Total	+156	+28	7

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Mentions and achievements

Where people are talking about Anbeeld/beellama.cpp, and every badge it has earned

Oct 21 post
- Just finished my first KVarN eval on AIME26 using BeeLlama v0.4.7! I used @liquidai's LFM2.5-2.6B BF16 as the model. In hindsight, I would say it seems to be quite tolerant of KV cache quantization,…
  Read full on X, posted by @Anbeeld
  @Anbeeld · x.com
Sep 281 post
- X account claims high t/s setup, but thin on details
  Read full on Reddit
  r/LocalLLaMA
7 days earlier
Sep 212 posts
- My own Qwen3.8-27B quants for a 16GB card: 70 t/s at 32K, usable out to 252K
  Read full on Reddit
  r/unsloth
- My own Qwen3.8-27B quants for a 16GB card: 70 t/s at 32K, usable out to 252K
  Read full on Reddit
  r/Qwen_AI
Sep 151 post
- Currently using Qwen 3.8 27B with a 512k KVarN6 KV cache, implementing fixes based on an audit from a frontier model. It holds up well and flattens decoding speed scaling with context quite a bit…
  Read full on X, posted by @Anbeeld
  @Anbeeld · x.com
Sep 101 post
- Running Vision Qwen 3.8 27B on a 16GB Card, the config (45tks).
  Read full on Reddit
  r/LocalLLaMA
10 days earlier
Aug 311 post
- Quality is why KVarN exists. kvarn5/kvarn4 = 5-bit K / 4-bit V vs turbo3's 3.125-bit, plus the last 1024 tokens stored exact. Anbeeld's own matrix: kvarn5/kvarn4@1024 lands within ~3% of q8_0 quality…
  Read full on X, posted by @fntAInhead
  @fntAInhead · x.com
Aug 262 posts
- Anyone interested in fixing tensor split in llama.cpp on Windows? @ggerganov @huggingface @UnslothAI @danielhanchen I have these guys constantly ruining fun on 2x3090: ggml-cuda/ggml-cuda.cu:117:…
  Read full on X, posted by @Anbeeld
  @Anbeeld · x.com
- How to improve KV cache quantization? Use less quantization. KV Cache Precision Tail: keeping just the newest [x] tokens in full precision, available in BeeLlama. Qwen 3.6 27B median KLD, tail 0 →…
  Read full on X, posted by @Anbeeld
  @Anbeeld · x.com
Aug 211 post
- On Qwen, KVarN shifts the whole ladder. Median KLD at the matched tail 128: q4_0: 0.001206 kvarn4: 0.001111 q5_0: 0.000970 kvarn5: 0.000927 q6_0: 0.000913 kvarn6: 0.000889 q8_0: 0.000901 kvarn6…
  Read full on X, posted by @Anbeeld
  @Anbeeld · x.com

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902107

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