head to head · open source

llama_index vs gpu-hot

llama_index has 52,202 GitHub stars, 8,162 forks, 770 open issues and last shipped yesterday. gpu-hot has 1,636 stars, 83 forks, 8 open issues and last shipped 24 days ago. llama_index leads on adoption by 3,091% (52,202 vs 1,636 stars). llama_index is written in Python under MIT; gpu-hot is written in JavaScript under MIT. llama_index has attracted 16% as many forks as stars, gpu-hot 5%. llama_index was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (llm), so they are genuine substitutes rather than adjacent tools.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

llama_index ★ 52K gpu-hot ★ 1.6K category AI & Machine Learning

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Side by side

llama_index gpu-hot
GitHub stars ★ 52K ★ 1.6K
License MIT MIT
Written in Python JavaScript
Last push 2026-09-17 2026-08-25
Forks ⑂ 8.2K ⑂ 83
Self-hosting Yes Yes
Data ownership Your server Your server

pick llama_index if

  • You weight community size — 52K stars and counting
  • You want the MIT license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full llama_index profile →

pick gpu-hot if

  • You want the gpu-hot feature set and don't need the biggest community
  • You prefer the MIT license terms
  • Your stack matches JavaScript
  • You evaluated both and gpu-hot fits your workflow better

full gpu-hot profile →

About llama_index

LlamaIndex is an MIT licensed, open source Python framework for building agentic applications — retrieval augmented generation systems, agents and multi agent workflows — on top of private documents and data, and it is aimed at AI engineers and teams who need to connect large language models to their own sources of context.

read the full llama_index overview →

About gpu-hot

gpu hot is a self hosted, real time NVIDIA GPU monitoring dashboard that ships as a Docker image and serves a live browser UI on port 1312 for a single machine or an entire cluster of GPU servers.

read the full gpu-hot overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 246K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

Related comparisons

ollama vs llama-index ollama vs llama-cpp ollama vs vllm ollama vs gpt4all ollama vs localai llama-cpp vs vllm ollama vs pageindex ollama vs langfuse openclaw vs hermes-agent openclaw vs open-webui openclaw vs lobechat openclaw vs anythingllm openclaw vs cherry-studio openclaw vs nanobot openclaw vs jan openclaw vs librechat dify vs langchain dify vs ponytail langchain vs ponytail dify vs graphify langchain vs graphify ponytail vs graphify dify vs claude-mem dify vs ragflow

More Machine Learning Infrastructure projects

Compare either of these against the rest of the Machine Learning Infrastructure field.

llama_index vs Ollama llama_index vs llama.cpp llama_index vs vllm llama_index vs GPT4All llama_index vs LocalAI llama_index vs PageIndex llama_index vs Langfuse llama_index vs cognee llama_index vs taipy llama_index vs dagster llama_index vs zvec llama_index vs langchain4j

Frequently asked questions

Is llama_index or gpu-hot more popular?

llama_index has 52,202 GitHub stars and gpu-hot has 1,636. llama_index has the larger community by that measure.

Are llama_index and gpu-hot free?

Both are open source. llama_index is licensed under MIT and gpu-hot under MIT. Neither carries a licence fee.

What is the difference between llama_index and gpu-hot?

llama_index is written in Python and gpu-hot in JavaScript. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, llama_index or gpu-hot?

Choose llama_index if you want the larger community (52,202 stars) or its MIT licence terms. Choose gpu-hot if its feature set, stack or MIT licence fits better. Both are self-hostable.