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Everything / Models and research / Llama

Trend in Models and research · tag llama · through Sep 2026

Llama Cooling

On TutorHero's Everything Index, Llama is cooling on GitHub: 0.34 of every 10,000 new public repos over the last three months (296 a month), +167% vs a year ago. The 12-month forecast says rising (+36%). By the end of 2032, lines in the same state ended between 0.01x and 2.5x of where they started (median 0.54x).

Per 10k new repos0.34296 new repos a month
Year over year+167%3 months: -12%
Next 12 months+36%80% band +15% to 4x
2032, median of history0.54x90% of past cases: 0.01x to 2.5x
Attention1.41%of new stars, -50% in a year
Jev 2032 callnot read yetonly top trends are sent to Jev
Share on X

Since 2019, and the range to 2032

0.010.030.10.31320192020202120222023202420252026202720282029203020312032Range to 2032 (history of similar lines)Stable Diffusion releasedChatGPT launchesGPT-4Llama 2, open weightsModel Context ProtocolDeepSeek-R1Claude Code previewHigh 0.84Median 0.18Low 0.00

New repos per 10,000 (3-month average, log scale)12-month forecastRange to 2032: middle half and 90% of past similar lines

The range is not a forecast of this line: it is what GitHub lines in the same state (more than doubled its share of new repos in a year) did 1 to 5 years later, 2019 to 2026, applied to today's level. Past 5 years it is stretched, not measured. Checked out of time (learned before 2022, scored after), 71% of outcomes landed inside the 90% range, so read it as wide. Open it in the Everything chart.

Week by week

Last week186 new reposOct 12 to Oct 18 · +225% against the field
Last 4 weeks▲ +54%278 new repos, against the 4 weeks before and the field
Wikipedia, 7 days3.8k views+6% against the 4 weeks before, all of Wikipedia the same way
AprMayJunJulAugSepOct

Wikipedia views a day, last 8 weeks

Aug 28Sep 4Sep 11Sep 18Sep 25Oct 2Oct 9Oct 16

New public repos with the llama tag each week (Monday to Sunday, UTC). The outlined bars, last week included, are still filling in, as tags are often added days after a repo is created, so their height will grow a little. "Against the field" divides the change by what the typical tag did, so a wave that lifts every tag does not count. Hover for the numbers.

Built vs talked about

Hacker News14 stories a month+27% share of HN vs a year ago · titles with "llama"
Wikipedia16.5k views a month-21% share of Wikipedia vs a year ago · Llama (language model)
Talk vs buildingTalked about more than builtHacker News +27% vs GitHub new repos +167% over the year, compared with the typical trend

Each line is its own share (of all new GitHub repos, all Hacker News stories, all English Wikipedia views, all new stars on the repos we track), shown as a share of its own peak, so the timing and shape compare even though the units differ. Hover for the counts. Tap a name to hide or show a line.

What it means

Studentslearning it, contributing, getting hired
  • Learn the ideas more than the name: Llama is cooling, -38% below its Jul 2026 high.
  • Start by reading multimodal-art-projection/YuE (+4.4k stars in 3 months) and sgl-project/sglang (+3.8k stars in 3 months).
  • People to follow: Ollama, Unsloth AI, Yaowei Zheng.
Founders and builderswhat to build next
  • Getting crowded: new repos +167% but attention -50%, so each new project competes harder for stars.
  • 29.1 new stars per new repo over 3 months, vs 8.50 for the typical trend: more demand per project than most fields.
  • The 12-month forecast for its share: +36% (Rising).
  • Talked about more than built: Hacker News +27% vs new repos +167% in a year, more talk per builder than the typical trend, so demand for builders may run ahead of supply.
Investorswhich fields deserve research time
  • History: of past GitHub lines that more than doubled its share of new repos in a year, 61% had a smaller share 3 to 5 years later and 8% at least doubled.
  • Attention: 1.41% of new stars on the repos we track, -50% in a year.
  • Hacker News: 14 stories a month, +27% share in a year; Wikipedia 16.5k views a month, -21%.
  • Not investment advice: this measures what people build on GitHub, not any company.
Developers choosing toolswhich tools to adopt
  • Most-starred tools here lately: multimodal-art-projection/YuE, sgl-project/sglang (vouched).
  • Check that a tool is still maintained before you adopt it: the field is shrinking.

Repos carrying it now

multimodal-art-projection/YuEYuE2: frontier music generation with symbolic planning, zero-shot covers, and agentic music editing.+4.4k stars in 3 months
sgl-project/sglangSGLang is a high-performance serving framework for large language models and multimodal models.+3.8k stars in 3 months · vouchedollama/ollamaGet up and running with Kimi, GLM, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.+2.7k stars in 3 months · vouchedvllm-project/vllmA high-throughput and memory-efficient inference and serving engine for LLMs+2.5k stars in 3 months · vouched
lyogavin/airllmAirLLM 2.8T LLM inference with single 4GB GPU+2.0k stars in 3 months · vouched
unslothai/unslothLocal UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4, MiniMax-H3, Gemma 4, FLUX and more.+1.9k stars in 3 months · vouched

People building it

OllamaRunning AI models locally with developer libraries and tools.Influence 93Unsloth AIRunning and training AI models locally with fine-tuning notebooks.Influence 87Yaowei ZhengEfficient fine-tuning frameworks for large language models.Influence 80Ettore Di GiacintoBuilds local AI tools and decentralized VPNs.Influence 84sgl-projectHigh-performance serving frameworks for large language and multimodal models.Influence 77Fish AudioOpen source text-to-speech and audio processing tools.Influence 68Haotian LiuCreated LLaVA, a visual instruction tuning model for GPT-4V level capabilities.Influence 61Meta LlamaOpen source Llama AI models and tools.Influence 60

More in Models and research

Machine learningSteady+72% in a year · 9.9k new repos a monthClaudeSteady11x in a year · 6.8k new repos a monthOpenAISteady+102% in a year · 3.0k new repos a monthPyTorchGrowing+133% in a year · 3.0k new repos a monthDeep learningCooling+20% in a year · 2.6k new repos a monthGeminiGrowing+128% in a year · 2.4k new repos a monthDeepSeekEmerging17x in a year · 2.3k new repos a monthChatGPTAccelerating+257% in a year · 1.3k new repos a monthQwenEmerging11x in a year · 951 new repos a monthTensorFlowFaded-6% in a year · 732 new repos a monthTransformersPeaking+69% in a year · 685 new repos a monthLoRAGrowing+233% in a year · 514 new repos a monthFine-tuningGrowing+79% in a year · 386 new repos a monthKerasFaded+11% in a year · 374 new repos a monthLLM trainingCooling-38% in a year · 29 new repos a month

Questions

Is Llama growing on GitHub?

Yes. Its share of all new public GitHub repos is +167% vs a year ago and -12% over the last three months (Sep 2026). Phase: Cooling.

How many new Llama repos are created each month?

About 296 new public repos a month carry the llama tag (three-month average to Sep 2026), or 0.34 of every 10,000 new repos.

What will Llama look like in 2032?

Nobody knows, and we say how much. Of past GitHub lines that more than doubled its share of new repos in a year, the middle half had between 0.14x and 1.27x of their share 3 to 5 years later, and 61% ended smaller.

Is Llama more talked about than built?

Talked about more than built. Over the year its share of Hacker News stories moved +27% while its share of new GitHub repos moved +167%. New repos grew faster than talk for most AI trends this year, so the label compares it with the typical trend: 1.7 times the talk per builder of the median trend.

Not investment advice. Measurements of what people build and star on GitHub, a statistical forecast, base rates and a model's reading of them. Nothing here is about any company's revenue, valuation or stock.