Runtime comparison
ExLlamaV2 vs vLLM
ExLlamaV2 is a MIT-licensed runtime for Linux · Windows running on CUDA · ROCm; vLLM is Apache-2.0-licensed for Linux on CUDA · ROCm. ExLlamaV2 rates easier to set up (3/5 vs 2/5 in our sourced ratings). Pick ExLlamaV2 for maximum control over how the model runs; pick vLLM for serving many requests at once.
| Spec | ExLlamaV2 | vLLM |
|---|---|---|
| License | MIT | Apache-2.0 |
| Operating systems | Linux · Windows | Linux |
| GPU backends | CUDA · ROCm | CUDA · ROCm |
| Install | pip / source | pip / source |
| Ease of use | 3/5 | 2/5 |
| Quant formats | exl2, gptq | awq, gptq |
| Engine | exllamav2 | vllm |
| GitHub stars | 4,581 | 85,770 |
| Latest version | v0.3.2 | v0.24.0 |
| Graphical app (GUI) | No | No |
| Server mode | No | Yes |
| OpenAI-compatible API | No | Yes |
| CPU offload | No | No |
| Multi-GPU | Yes | Yes |
| Speculative decoding | Yes | Yes |
| LoRA support | Yes | Yes |
| KV-cache quantization | Yes | Yes |
Which should you use?
ExLlamaV2
Best for maximum control over how the model runs. Command line and server, runs on CUDA · ROCm.
Full ExLlamaV2 guide →vLLM
Best for serving many requests at once. Command line and server, runs on CUDA · ROCm.
Full vLLM guide →Neither runtime changes whether a model fits — that is your memory and quantization. Check your hardware first, then pick the runtime.
Sources: ExLlamaV2 github.com/turboderp-org/exllamav2 (as of 2026-07-08); vLLM github.com/vllm-project/vllm (as of 2026-07-08).