head to head · open source
llama_index vs gpu-hot
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. gpu-hot has 1,642 stars, 86 forks, 8 open issues and last shipped 2 months ago. llama_index leads on adoption by 3,114% (52,779 vs 1,642 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.
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Side by side
| llama_index | gpu-hot | |
|---|---|---|
| GitHub stars | ★ 53K | ★ 1.6K |
| License | MIT | MIT |
| Written in | Python | JavaScript |
| Last push | 2026-10-26 | 2026-08-25 |
| Forks | ⑂ 8.5K | ⑂ 86 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick llama_index if
- You weight community size — 53K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
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
About llama_index
🗂️ LlamaIndex (OSS Framework) 🦙 [!NOTE] The current focus of LlamaIndex is to build the best AI powered engine for document parsing and extraction. LlamaParse is our enterprise platform for agentic OCR, parsing, extraction, indexing and more. LiteParse represents our efforts to build the best free, fast, cheap text parser in the market. ParseBench and ExtractBench represent our commitment towards open benchmarking for parsing and extraction. The company itself has undergone an evolution since when this OSS framework first launched 3 years ago in 2023. Since the early days, the framework has consisted of a…
read the full llama_index overview →
About gpu-hot
GPU Hot Real time NVIDIA GPU monitoring dashboard. Lightweight, web based, and self hosted. Usage Monitor a single machine or an entire cluster with the same Docker image. Single machine: Multiple machines: Open Older GPUs: Add e NVIDIA SMI=true if metrics don't appear. Process monitoring: Add init pid=host to see process names. Note: This allows the container to access host process information. From source: Requirements: Docker + NVIDIA Container Toolkit Features Real time metrics (sub second) Automatic multi GPU detection Process monitoring (PID, memory usage) Historical charts (utilization, temperature…
read the full gpu-hot overview →
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Frequently asked questions
Is llama_index or gpu-hot more popular?
llama_index has 52,779 GitHub stars and gpu-hot has 1,642. 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 (52,779 stars) or its MIT licence terms. Choose gpu-hot if its feature set, stack or MIT licence fits better. Both are self-hostable.