Comparisons · Last reviewed
All of these run language models on hardware you control; they differ in what they treat as the hard problem. Ollama optimises for getting started, LM Studio for a desktop app, llama.cpp for speed and hardware reach, vLLM for serving many users from GPUs, and llamay for reusing computed state — a context you can fork, snapshot and restore. Each page below says where the other project is the better choice.
| Project | Licence | Shape | APIs | Read |
|---|---|---|---|---|
| Ollama | MIT | CLI, server, macOS app | OpenAI, Anthropic (subset), its own | Ollama vs llamay |
| LM Studio | Proprietary | Desktop app, headless daemon | OpenAI, Anthropic, its own REST | LM Studio vs llamay |
| llama.cpp | MIT | Engine, CLI, llama-server | OpenAI, Anthropic | llama.cpp vs llamay |
| vLLM | Apache-2.0 | Python GPU server | OpenAI, Anthropic | vLLM vs llamay |
| Jan, GPT4All, LocalAI, KoboldCpp, mlx-lm, textgen | Open source (see each) | Apps and servers | Varies | Ollama alternatives |
| llamay | Proprietary, free to run | One binary, apps, Studio | OpenAI, Anthropic, Ollama | Documentation |
Every statement about another project links to that project's own documentation, repository or licence, and anything we could not confirm there is left out. We do not publish speed comparisons with other engines except where we ran them ourselves on the same file and machine, and we say where llamay loses. Each page carries the date it was last reviewed.
New to the vocabulary? The glossary defines GGUF, quantisation, the KV cache, prefix caching and OpenAI-compatible servers.
Ollama to get started quickly, LM Studio for a desktop app, llama.cpp for the most speed and hardware support, vLLM to serve many users from GPUs, and llamay when long prompts should be computed once and forked, saved or moved.
No. llamay is proprietary software from Kosa8 Labs, free to download and run on your own machine. Ollama, llama.cpp and vLLM are open source; LM Studio is proprietary.
It treats a model's context as an object: forked copy-on-write, snapshotted to a file and restored on another machine. It also reads Ollama's model store and serves OpenAI, Anthropic and Ollama APIs from one binary.
Every statement above about another project is taken from that project's own documentation, repository or licence, read on 31 October 2026. Anything we could not confirm there is left out. If one of these has changed, write to [email protected] and we will correct the page.
Last reviewed .