gpustack vs llm-app

Common questions

What is the difference between gpustack and llm-app?

gpustack: A GPU cluster manager for high-performance AI model serving (vLLM, SGLang) and on-demand SSH-accessible GPU instances.. llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data.. See the comparison table for live GitHub stats and shared categories.

When should I choose gpustack over llm-app?

Choose gpustack over llm-app when gpustack is primarily Python; llm-app is Jupyter Notebook; License: gpustack is Apache-2.0, llm-app is MIT; Tags unique to gpustack: ascend, cuda, deepseek, distributed-inference; Also covers Inference & Serving.

When should I choose llm-app over gpustack?

Choose llm-app over gpustack when llm-app is primarily Jupyter Notebook; gpustack is Python; License: llm-app is MIT, gpustack is Apache-2.0; Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others.; Tags unique to llm-app: chatbot, hugging-face, llm, retrieval-augmented-generation; Also covers Data & Retrieval; - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs.

When should I avoid gpustack?

Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

When should I avoid llm-app?

- You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app. - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app.

Is gpustack or llm-app more popular on GitHub?

llm-app has more GitHub stars (59,068 vs 5,301). Stars measure visibility, not whether either tool fits your constraints.

Are gpustack and llm-app open source?

Yes - both are open-source projects on GitHub (gpustack: Apache-2.0, llm-app: MIT).

Where can I find alternatives to gpustack or llm-app?

GraphCanon lists graph-backed alternatives at gpustack alternatives and llm-app alternatives (gpustack markdown twin, llm-app 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, gpustack or llm-app?

gpustack: Very active. llm-app: 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 gpustack and llm-app?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: gpustack trust report; llm-app trust report.