head to head · open source
llama_index vs kvcached
llama_index has 52,328 GitHub stars, 8,222 forks, 770 open issues and last shipped 2 days ago. kvcached has 1,506 stars, 181 forks, 105 open issues and last shipped 2 days ago. llama_index leads on adoption by 3,375% (52,328 vs 1,506 stars). llama_index is written in Python under MIT; kvcached is written in Python under Apache-2.0. llama_index has attracted 16% as many forks as stars, kvcached 12%. 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 | kvcached | |
|---|---|---|
| GitHub stars | ★ 52K | ★ 1.5K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-09-25 | 2026-09-25 |
| Forks | ⑂ 8.2K | ⑂ 181 |
| 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
pick kvcached if
- You want the kvcached feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Python
- You evaluated both and kvcached fits your workflow better
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 kvcached
kvcached is an Apache 2.0 Python library that gives LLM serving engines a virtual memory style, elastic KV cache, letting several models share one GPU's memory instead of partitioning it rigidly — it is built for ML infrastructure and platform engineers who serve LLMs on shared or capacity constrained GPUs.
read the full kvcached overview →
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Frequently asked questions
Is llama_index or kvcached more popular?
llama_index has 52,328 GitHub stars and kvcached has 1,506. llama_index has the larger community by that measure.
Are llama_index and kvcached free?
Both are open source. llama_index is licensed under MIT and kvcached under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and kvcached?
llama_index is written in Python and kvcached in Python. 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 kvcached?
Choose llama_index if you want the larger community (52,328 stars) or its MIT licence terms. Choose kvcached if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.