head to head · open source

vllm vs pegainfer

vllm has 92,028 GitHub stars, 22,335 forks, 7,953 open issues and last shipped yesterday. pegainfer has 704 stars, 107 forks, 89 open issues and last shipped yesterday. vllm leads on adoption by 12,972% (92,028 vs 704 stars). vllm is written in Python under Apache-2.0; pegainfer is written in Rust under Apache-2.0. vllm has attracted 24% as many forks as stars, pegainfer 15%. pegainfer was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 6 topic tags (cuda, deepseek, inference, kimi), 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.

vllm ★ 92K pegainfer ★ 704 category AI & Machine Learning

← all 8884 open source comparisons

Side by side

vllm pegainfer
GitHub stars ★ 92K ★ 704
License Apache-2.0 Apache-2.0
Written in Python Rust
Last push 2026-09-17 2026-09-17
Forks ⑂ 22K ⑂ 107
Self-hosting Yes Yes
Data ownership Your server Your server

pick vllm if

  • You weight community size — 92K stars and counting
  • You want the Apache-2.0 license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full vllm profile →

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

full pegainfer profile →

About vllm

vLLM is a high throughput, memory efficient Python library for LLM inference and serving, built for ML engineers and platform teams who need to run open weight models on their own hardware at production scale.

read the full vllm overview →

About pegainfer

PegaInfer is a pure Rust and CUDA large language model inference engine that serves models ranging from Qwen3 to Kimi K2 behind an OpenAI compatible API, with no PyTorch or Python runtime in the default serving path.

read the full pegainfer overview →

More in AI & Machine Learning

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

Related comparisons

ollama vs vllm llama-cpp vs vllm ollama vs llama-cpp ollama vs gpt4all ollama vs llama-index ollama vs localai 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.

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

Frequently asked questions

Is vllm or pegainfer more popular?

vllm has 92,028 GitHub stars and pegainfer has 704. vllm has the larger community by that measure.

Are vllm and pegainfer free?

Both are open source. vllm is licensed under Apache-2.0 and pegainfer under Apache-2.0. Neither carries a licence fee.

What is the difference between vllm and pegainfer?

vllm 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, vllm or pegainfer?

Choose vllm if you want the larger community (92,028 stars) or its Apache-2.0 licence terms. Choose pegainfer if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.