head to head · open source
llama_index vs pegainfer
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. pegainfer has 731 stars, 121 forks, 89 open issues and last shipped yesterday. llama_index leads on adoption by 7,120% (52,779 vs 731 stars). llama_index is written in Python under MIT; pegainfer is written in Rust under Apache-2.0. llama_index has attracted 16% as many forks as stars, pegainfer 17%. pegainfer 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 | pegainfer | |
|---|---|---|
| GitHub stars | ★ 53K | ★ 731 |
| License | MIT | Apache-2.0 |
| Written in | Python | Rust |
| Last push | 2026-10-26 | 2026-11-02 |
| Forks | ⑂ 8.5K | ⑂ 121 |
| 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 pegainfer if
- You want the pegainfer feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Rust
- You evaluated both and pegainfer 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 pegainfer
Quickstart · Performance · Models · Architecture · API · Development PegaInfer serves LLMs through an OpenAI compatible API. Each model owns its scheduler, state, and kernels; serving and KV infrastructure are shared. No PyTorch or Python runtime. Quickstart Prebuilt binary · Qwen3 on Linux The Qwen3 only release bundles CUDA 13 and cuBLAS. It requires Linux x86 64 , an NVIDIA GPU with compute capability 8.x–12.x , driver 580+ , glibc 2.35+ , and OpenSSL 3 . Model weights are downloaded separately. Download Qwen3 4B into models/Qwen3 4B , then start the server: The server…
read the full pegainfer overview →
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Frequently asked questions
Is llama_index or pegainfer more popular?
llama_index has 52,779 GitHub stars and pegainfer has 731. llama_index has the larger community by that measure.
Are llama_index and pegainfer free?
Both are open source. llama_index is licensed under MIT and pegainfer under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and pegainfer?
llama_index is written in Python and pegainfer in Rust. 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 pegainfer?
Choose llama_index if you want the larger community (52,779 stars) or its MIT licence terms. Choose pegainfer if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.