Runtime comparison
ExLlamaV2 vs KoboldCpp
ExLlamaV2 is a MIT-licensed runtime for Linux · Windows running on CUDA · ROCm; KoboldCpp is AGPL-3.0-licensed for Linux · macOS · Windows on CUDA · CPU · Vulkan · ROCm. KoboldCpp rates easier to set up (4/5 vs 3/5 in our sourced ratings). Pick ExLlamaV2 for maximum control over how the model runs; pick KoboldCpp for people who want a desktop app and no terminal.
| Spec | ExLlamaV2 | KoboldCpp |
|---|---|---|
| License | MIT | AGPL-3.0 |
| Operating systems | Linux · Windows | Linux · macOS · Windows |
| GPU backends | CUDA · ROCm | CUDA · CPU · Vulkan · ROCm |
| Install | pip / source | binary / source |
| Ease of use | 3/5 | 4/5 |
| Quant formats | exl2, gptq | gguf |
| Engine | exllamav2 | llama.cpp |
| GitHub stars | 4,581 | 10,973 |
| Latest version | v0.3.2 | v1.116.1 |
| Graphical app (GUI) | No | Yes |
| Server mode | No | Yes |
| OpenAI-compatible API | No | Yes |
| CPU offload | No | Yes |
| 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 →KoboldCpp
Best for people who want a desktop app and no terminal. Ships a graphical app, runs on CUDA · CPU · Vulkan · ROCm.
Full KoboldCpp 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); KoboldCpp github.com/LostRuins/koboldcpp (as of 2026-07-08).