llama.cpp vs LocalAI
Short answer
llama.cpp: Lightweight C/C++ engine that runs quantized open models on CPU or GPU, with an OpenAI-compatible server. LocalAI: OpenAI-compatible API for LLMs, vision, voice and images on any hardware. Both are in our Local model runtimes category.
Choose llama.cpp if you want: larger community (132k vs 49.8k GitHub stars).
Choose LocalAI if you want: simpler deploy (one container vs a multi-container stack).
llama.cpp and LocalAI publish no official RAM figure, so we cannot compare hosting cost directly.
Last updated · computed from each project's official docs and live GitHub data · sources
llama.cpp vs LocalAI side by side
| llama.cpp | LocalAI | |
|---|---|---|
| Category | Local model runtimes | Local model runtimes |
| What it is | Lightweight C/C++ engine that runs quantized open models on CPU or GPU, with an OpenAI-compatible server. | OpenAI-compatible API for LLMs, vision, voice and images on any hardware. |
| License | MIT | MIT |
| License type | Permissive | Permissive |
| License conditions | Permissive. Internal and commercial use allowed. Individual models have their own licenses. | Permissive. Internal and commercial use allowed. Models keep their own licenses. |
| Status | Active | Active |
| GitHub stars | 132k | 49.8k |
| Last commit | Oct 22, 2026 | Oct 21, 2026 |
| Latest release | v0.7.0 | v4.11.0 |
| Minimum hardware | Not published | Not published |
| Recommended hardware | Not published | Not published |
| RAM measured by us | 437 MiB idle, 489 MiB working (our test, vbuild 11804 (c7fc50941), Oct 22, 2026) | Not tested yet |
| GPU | Optional. Runs on CPU (AVX/AVX2/AVX512/AMX, ARM NEON) and supports CPU+GPU hybrid inference for models larger than VRAM. Docker images exist for CUDA, ROCm, SYCL, Vulkan, MUSA and OpenVINO. | Optional. Images exist for NVIDIA CUDA 12/13, AMD ROCm, Intel oneAPI and CPU-only. |
| Est. server cost | from €11.99/mo (based on our test, not official) | Not estimated |
| Deploy method | Docker (or install script / prebuilt binaries) | Docker |
| Known gotchas | 3 listed | 1 listed |
| Telemetry | Not documented | Not documented |
| Calls home by default | Not documented | Not documented |
| SSO (OIDC / SAML / LDAP) | Not documented | Free (OIDC free) |
| Audit log | Not documented | Not documented |
| RBAC | Not documented | Yes, free |
| Details | Full llama.cpp guide → | Full LocalAI guide → |
Key differences
- Deploy: llama.cpp: Docker (or install script / prebuilt binaries) · multi-container stack. LocalAI: Docker · single container.
- GitHub stars: llama.cpp: 132k. LocalAI: 49.8k.
- Last commit: llama.cpp: Oct 22, 2026. LocalAI: Oct 21, 2026.
- Latest release: llama.cpp: v0.7.0 (Oct 15, 2026). LocalAI: v4.11.0 (Oct 2, 2026).
Same for both: Category: Local model runtimes; License: MIT (Permissive); Official hardware: not published; GPU: optional / see notes; Est. server cost: not estimated (no official RAM figure); Status: Active.
llama.cpp vs LocalAI: FAQ
llama.cpp or LocalAI: which should a small business choose?
Choose llama.cpp if you want: larger community (132k vs 49.8k GitHub stars). Choose LocalAI if you want: simpler deploy (one container vs a multi-container stack). llama.cpp and LocalAI publish no official RAM figure, so we cannot compare hosting cost directly.
Which is cheaper to self-host, llama.cpp or LocalAI?
llama.cpp: not estimated (no official RAM figure). LocalAI: not estimated (no official RAM figure). Our estimate is the cheapest Hetzner Cloud plan that meets each project's official RAM and vCPU figure; it covers the server only.
How much hardware do llama.cpp and LocalAI need?
llama.cpp: not published. LocalAI: not published.
What is the license difference between llama.cpp and LocalAI?
llama.cpp: MIT (Permissive). Permissive. Internal and commercial use allowed. Individual models have their own licenses. LocalAI: MIT (Permissive). Permissive. Internal and commercial use allowed. Models keep their own licenses. This is a summary, not legal advice.
Is llama.cpp or LocalAI more actively maintained?
llama.cpp: Active, last commit Oct 22, 2026. LocalAI: Active, last commit Oct 21, 2026. GitHub data refreshed Oct 22, 2026.
Which is easier to deploy, llama.cpp or LocalAI?
llama.cpp installs via Docker (or install script / prebuilt binaries) (multi-container stack); LocalAI via Docker (single container). llama.cpp lists 3 known gotchas and LocalAI lists 1; see each app page.
Related
Sources
- llama.cpp GitHub repository: github.com/ggml-org/llama.cpp
- llama.cpp documentation: github.com/ggml-org/llama.cpp/blob/master/docs/docker.md
- llama.cpp license: github.com/ggml-org/llama.cpp/blob/master/LICENSE
- llama.cpp hardware requirements: github.com/ggml-org/llama.cpp#description
- llama.cpp deploy instructions: github.com/ggml-org/llama.cpp/blob/master/tools/server/README.md#docker
- LocalAI GitHub repository: github.com/mudler/LocalAI
- LocalAI documentation, LocalAI hardware requirements, LocalAI deploy instructions: github.com/mudler/LocalAI#readme
- LocalAI license: github.com/mudler/LocalAI/blob/master/LICENSE
- Hetzner Cloud pricing used for cost estimates (read 2026-10-22): www.hetzner.com/cloud/regular-performance
- GitHub REST API (stars, commits, releases): docs.github.com/en/rest
Every value is generated from the same verified data as the app pages. Spotted something wrong? Tell us.