jan vs vllm

Common questions

What is the difference between jan and vllm?

jan: Jan is an open source alternative to ChatGPT that runs 100% offline on your computer.. vllm: A high-throughput and memory-efficient inference and serving engine for LLMs. See the comparison table for live GitHub stats and shared categories.

When should I choose jan over vllm?

Choose jan over vllm when jan is primarily TypeScript; vllm is Python; License: jan is Other, vllm is Apache-2.0; Requirements: Min 8 GB RAM; For macOS, 8GB RAM is required for 3B models, 16GB for 7B models, and 32GB for 13B models.; Windows users need version 10 or higher with GPU support for NVIDIA, AMD, or Intel Arc.; Linux users can run Jan on most distributions, with GPU acceleration available.; Both projects focus on serving LLMs locally but with optimizations for speed and cost-efficiency; Tags unique to jan: chatgpt, llamacpp, llm, localai; Also covers AI Agents; Use Jan when you need a self-hosted chatbot solution that can operate entirely offline on your local machine.

When should I choose vllm over jan?

Choose vllm over jan when vllm is primarily Python; jan is TypeScript; License: vllm is Apache-2.0, jan is Other; Requirements: Min 8 GB RAM; Installation can be done via uv pip install vllm or building from source for development purposes.; Both projects focus on serving LLMs locally but with optimizations for speed and cost-efficiency; Tags unique to vllm: amd, blackwell, cuda, deepseek; Also covers Inference & Serving; When you need a high-throughput and memory-efficient inference engine for large language models, especially if you are working with a variety of hardware configurations including AMD, CUDA, and TPU.

When should I avoid jan?

Do not use Jan if you require a cloud-based chatbot service with real-time updates and maintenance. Avoid Jan if your system does not meet the minimum hardware requirements, such as 8GB RAM for smaller models and up to 32GB for larger models. Jan may not be the best choice if you need a chatbot with extensive pre-trained models or continuous learning capabilities, as it operates offline and does not have access to the latest updates.

When should I avoid vllm?

If your project strictly requires a specific competitor's ecosystem or features that are not covered by vLLM, such as specialized model serving capabilities not supported by vLLM. When the project's hardware setup is incompatible with the supported hardware configurations of vLLM, such as certain non-supported GPU models or configurations.

Is jan or vllm more popular on GitHub?

vllm has more GitHub stars (92,075 vs 44,518). Stars measure visibility, not whether either tool fits your constraints.

Are jan and vllm open source?

Yes - both are open-source projects on GitHub (jan: Other, vllm: Apache-2.0).

Where can I find alternatives to jan or vllm?

GraphCanon lists graph-backed alternatives at jan alternatives and vllm alternatives (jan markdown twin, vllm markdown twin), ranked by typed relationship edges rather than popularity votes.

Is there a machine-readable version of this comparison?

Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

Which is better maintained, jan or vllm?

jan: Very active. vllm: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

Where are the full trust reports for jan and vllm?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: jan trust report; vllm trust report.