Pick LiteLLM if
platform teams who already pay model vendors and want keys, budgets, and fallbacks in one proxy.
Read the LiteLLM pageLiteLLM vs vLLM
Our take
Pick LiteLLM if platform teams who already pay model vendors and want keys, budgets, and fallbacks in one proxy. Pick vLLM if platform and inference engineers who already have a GPU (or a kube cluster) and need an OpenAI-shaped endpoint. Skip LiteLLM if people who want a local chat app (Ollama) or traces-first observability (Langfuse). Skip vLLM if someone who wants a local ChatGPT window (Ollama, Jan) and will not
vLLM
high-throughput LLM serving engine
Best for
LiteLLM One proxy in front of many model APIs
vLLM Serving tokens at production QPS
Free plan
LiteLLM $0 · , “free forever” on the page. You still pay upstream model APIs
vLLM $0 · apache-2.0. You pay the GPU, electricity, and (if you use them) model licenses
Lowest paid
LiteLLM Not published by the vendor
vLLM Not published by the vendor
Coding agent
LiteLLM Playground / Models / Agents / MCP / Guardrails
vLLM
Runs where
LiteLLM Local; you host it
vLLM Web, desktop; hosted
Watch out
LiteLLM $0 is the proxy, not the tokens
vLLM The GPU is the bill
Last checked
LiteLLM 2026-10-19 · litellm.ai/pricing
vLLM 2026-10-20 · github.com/vllm-project/vllm
Which one, then?
Pick vLLM if
platform and inference engineers who already have a GPU (or a kube cluster) and need an OpenAI-shaped endpoint.
Read the vLLM page