Head to head · Coding · updated Oct 17, 2026
LiteLLM vs vLLM
LiteLLM scores 92 to vLLM's 80 on public evidence for LLM APIs & model routers, and they rank #2 and #3 there. Both are free to start. Numbers below are the same public signals the ranking uses, recomputed nightly — nothing here is sponsored.
LiteLLM
Open-source Python SDK and proxy that calls 100+ LLM providers through the OpenAI format.
+ Self-hosted gateway with spend tracking, virtual keys, and fallbacks across providers.
− Huge dependency surface and frequent releases that occasionally break provider mappings.
vLLM
High-throughput LLM serving engine with PagedAttention and an OpenAI-compatible server.
+ Serves many concurrent requests on GPUs far faster than llama.cpp-based tools.
− Linux and NVIDIA-centric; painful on Mac or consumer hardware.
Side by side
public evidence| LiteLLM | vLLM | |
|---|---|---|
| Evidence score / 100 | 92 | 80 |
| GitHub stars | 61,411 | 93,962 |
| Hacker News stories, 30d | 6 | 0 |
| Release-feed mentions, 30d | 0 | 6 |
| Last activity | 0 days ago | 0 days ago |
| Pricing | Open source · Free; enterprise proxy paid | Open source · Free |
| Platforms | cli, api, linux | linux, cli, api |
| Maker | BerriAI | vLLM Project |
Which one?
Pick LiteLLM if
- you want the stronger public evidence (92 vs 80)
Best for teams standardising LLM access behind one proxy.
Pick vLLM if
Serves many concurrent requests on GPUs far faster than llama.cpp-based tools.
Best for self-hosting models for production traffic.