GITFIND

open-weight adoption — tracked daily

THE OPEN MODEL INDEX

Which open-weight models are developers actually building with? Hugging Face weight downloads and GitHub velocity for DeepSeek, Llama, Qwen, Kimi, Mistral, and GLM — plus the runtime layer that runs them. Every number says what it is; nothing here is made up.

30-day pulls: 9.7Mmodels tracked: 8 + 3 runtimesleader: deepseek r1 5.0M/30dfastest riser: kimi k3 · 3d

§ 1 — weight downloads, daily

fig. 01

5.0M10.0Mapr 30 — 4.7M commitsmay 2 — 154k commitsmay 7 — 795k commitsmay 8 — 4.7M commitsmay 9 — 463k commitsmay 10 — 580k commitsmay 11 — 795k commitsmay 13 — 693k commitsmay 15 — 396k commitsmay 16 — 947k commitsmay 19 — 4.9M commitsmay 21 — 5.3M commitsmay 23 — 592k commitsmay 25 — 4.4M commitsmay 27 — 4.7M commitsmay 29 — 138k commitsmay 30 — 5.0M commitsmay 31 — 1.0M commitsjun 1 — 682k commitsjun 2 — 328k commitsjun 4 — 7.4M commitsjun 6 — 5.7M commitsjun 7 — 5.7M commitsjun 8 — 5.7M commitsjun 11 — 6.0M commitsjun 15 — 218k commitsjun 16 — 100.0k commitsjun 17 — 558k commitsjun 18 — 204k commitsjun 19 — 996k commitsjun 21 — 6.8M commitsjun 24 — 7.0M commitsjun 29 — 696k commitsjun 30 — 171k commitsjul 1 — 8.8M commitsjul 3 — 8.0M commitsjul 4 — 151k commitsjul 5 — 745k commitsjul 7 — 1.1M commitsjul 9 — 8.6M commitsjul 10 — 11.1M commitsjul 11 — 175k commitsjul 12 — 8.7M commitsjul 14 — 142k commitsjul 15 — 10.8M commitsjul 17 — 229k commitsjul 18 — 917k commitsjul 19 — 69.4k commitsjul 20 — 8.6M commitsjul 22 — 10.1M commitsjul 24 — 208k commitsjul 26 — 130k commitsjul 28 — 195k commitsjul 29 — 11.4M commitsjul 30 — 11.4M commitsjul 31 — 11.9M commitsaug 1 — 12.2M commitsaug 2 — 12.0M commitsaug 3 — 12.5M commitsaug 4 — 12.6M commitsaug 5 — 13.1M commitsaug 6 — 13.1M commitsaug 7 — 13.0M commitsaug 8 — 12.8M commitsaug 9 — 12.6M commitsaug 10 — 12.3M commitsaug 11 — 12.2M commitsaug 12 — 12.1M commitsaug 13 — 12.1M commitsaug 14 — 12.3M commitsaug 15 — 12.2M commitsaug 16 — 12.0M commitsaug 17 — 11.7M commitsaug 18 — 11.5M commitsaug 19 — 11.5M commitsaug 20 — 11.3M commitsaug 21 — 10.8M commitsaug 22 — 10.3M commitsaug 23 — 10.1M commitsaug 24 — 9.8M commitsaug 25 — 9.7M commits9.7Mapr 30may 19jun 4jun 21jul 10jul 24aug 5aug 15aug 25

hugging face trailing 30-day weight downloads per day, across all tracked models.

§ 2 — share of new downloads

fig. 02

52%29%11%
deepseek r1 52.2%kimi k3 28.8%deepseek v3 10.7%llama 3.3 70b 3.1%mistral small 3.1 1.9%kimi k2 1.7%glm 4.5 1.1%qwen3 235b 0.4%

share of the trailing 30-day window.

§ 3 — each model, same scale

fig. 03

deepseek r1

5.0M/30d · ▼ 43%

kimi k3

2.8M/30d · ▲ 97724%

deepseek v3

1.0M/30d · ▲ 31%

llama 3.3 70b

300k/30d · ▼ 64%

mistral small 3.1

186k/30d · ▲ 6%

kimi k2

164k/30d · ▼ 28%

glm 4.5

109k/30d · ▼ 23%

qwen3 235b

43.3k/30d · ▼ 49%

trailing 30-day weight downloads per day, averaged over 3-day buckets · all charts share one scale.

§ 4 — momentum, ranked

fig. 04

  • 01kimi k3fastest

    2.8M/30d · ▲ 97724% · 3d to double · 28.8%

  • 02deepseek v3

    1.0M/30d · ▲ 31% · 87d to double · 10.7%

  • 03mistral small 3.1

    186k/30d · ▲ 6% · 459d to double · 1.9%

  • 04glm 4.5

    109k/30d · ▼ 23% · — · 1.1%

  • 05kimi k2

    164k/30d · ▼ 28% · — · 1.7%

  • 06deepseek r1

    5.0M/30d · ▼ 43% · — · 52.2%

  • 07qwen3 235b

    43.3k/30d · ▼ 49% · — · 0.4%

  • 08llama 3.3 70b

    300k/30d · ▼ 64% · — · 3.1%

§ 5 — the runtime layer

fig. 05

fig. 05 — the runtime layer (what people run open models with)

toolstarsforkscontributors
ollama179k17.5k596
llama.cpp125k22.1k1.9k
vllm89.9k21.1k2.4k

runtimes don’t publish weight downloads — repo traction is the honest proxy here.

§ 6 — intelligence brief

fig. 06

$ tail -f /var/log/gitfind/models.log

09:41:02 8 open models + 3 runtimes tracked — hf trailing-30d downloads + github velocity, nothing fabricated

09:41:03 deepseek r1 leads the 30-day window at 5.0M

09:41:04 kimi k3 gained the most rate this month — +2.8M on the 30d window

09:41:05 kimi k3 is the fastest riser — doubling every 3 days at current pace

09:41:06 ollama leads the runtime layer at 179k★

09:41:07 router share coming when there’s a stable public source — we don’t scrape

09:41:08 █

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