LangGraph vs LiteLLM
Side-by-side comparison built from DeepYard's structured catalog. Content updated Aug 21, 2026.
Direct Answer
LangGraph suits teams needing open-source access, typescript focus, and 40,209 GitHub stars in current listing data. LiteLLM suits teams needing open-source access, api gateway focus, and 56,974 GitHub stars in current listing data. This summary reflects catalog metadata only for decision support, not independent testing.
What this comparison weighs
- Pricing and free-tier availability
- License model and deployment fit
- GitHub adoption and contributor depth
- Catalog tags, integrations, and supported workflows
| Metric | LangGraph | LiteLLM |
|---|---|---|
| GitHub Stars | 40.2K | 57.0K |
| Contributors | 278 | 376 |
| Last Commit | Aug 22, 2026 | Aug 22, 2026 |
| Open Issues | 708 | 4989 |
| License | open-source | open-source |
| Pricing | open-source | open-source |
| Free Tier | Yes | Yes |
| Category | frameworks | frameworks |
| Trending | No | No |
Choose LangGraph if you need
- • LangGraph stands out for Typescript workflows that are not listed for LiteLLM.
- • LangGraph is the stronger pick when Graph matters because that capability is listed only on its profile.
- • LangGraph is the cleaner fit if you specifically need Graph workflows from the catalog tags.
Choose LiteLLM if you need
- • LiteLLM is the stronger pick when Api Gateway matters because that capability is listed only on its profile.
- • LiteLLM shows broader GitHub adoption with 56,974 stars versus 40,209 for LangGraph.
- • LiteLLM has a larger visible contributor base (376 vs 278).
Meaningful differences
- • Workflow emphasis: LangGraph highlights Typescript, while LiteLLM highlights Python.
- • GitHub adoption: LangGraph shows 40,209 stars versus 56,974 for LiteLLM.
- • Contributor count: LangGraph lists 278 contributors and LiteLLM lists 376.
Shared capabilities
- • Python
- • Open Source
Shared Tags
Only in LangGraph
Only in LiteLLM
Limitations and evidence
- • DeepYard compares structured public metadata; this is not an independent benchmark unless a test record is shown.
- • Signals such as stars, contributors, and last commit indicate public activity, not purchase fit or runtime quality.
- • Pricing and feature coverage reflect the stored listing snapshot and may lag vendor changes between refreshes.
About LangGraph
LangGraph is LangChain's framework for building stateful, multi-actor agent applications as graphs. Define agents as nodes and their interactions as edges, with built-in persistence, streaming, human-in-the-loop, and time-travel debugging. The standard for production agent orchestration in the LangChain ecosystem.
View full listingAbout LiteLLM
LiteLLM provides a unified OpenAI-compatible API for 200+ LLM providers (OpenAI, Anthropic, Google, Azure, AWS Bedrock, Ollama, and more). Use one interface to call any model, with built-in load balancing, fallbacks, spend tracking, and rate limiting. Essential infrastructure for multi-model agent systems.
View full listing