# llama.cpp v1.0.0: Stable API, Semver, and What Breaks > Source: > Published: 2026-11-14 07:07:59+00:00 llama.cpp, the C++ inference engine running underneath Ollama, LM Studio, GPT4All, and most of the local AI ecosystem, tagged [v1.0.0 on November 13](https://github.com/ggml-org/llama.cpp/releases) after 3.5 years of weekly churn and no stable API guarantees. The features matter less than the promise: semantic versioning now governs the public C API, and breaking changes arrive only with a MAJOR version bump. If you have ever had a llama.cpp update silently wreck your build on a Friday afternoon, that era is over. ## The Semver Contract Both libllama and libggml now follow explicit rules: a MAJOR bump signals a breaking change to the C API in `./include`, MINOR covers backward-compatible additions and new model support, PATCH is bug fixes only. That sounds obvious, but llama.cpp skipped this convention for three and a half years. The project moved so fast that semver would have felt like a straitjacket. Now the ecosystem is wide enough that unpredictable breaks are costing real engineering time downstream. The practical upside: enterprise vendors and Linux distros can now package libllama like they package libssl or libcurl — with a formal expectation that the next soname change will be announced, not discovered at compile time. ## What Breaks in v1.0.0 This release itself carries breaking changes — it is the final cleanup before the stability promise kicks in. Thirty-six C API symbols were removed. If your code calls any of them, it will not compile against v1.0.0. The most common ones developers will hit: - `llama_n_embd(model)` → use`llama_model_n_embd(model)` - `llama_n_ctx_train(model)` → use`llama_model_n_ctx_train(model)` - `llama_token_cls(vocab)` → use`llama_vocab_bos(vocab)` - `llama_set_warmup` → removed entirely, no replacement - `llama_set_embd_state_src` → renamed to`llama_set_ctx_state_src` - `--defrag-thold` CLI flag → gone The libllama shared library also changed its soname from `libllama.so.0` to `libllama.so.1`. Any dynamically linked binary or package that pins the old soname needs updating before the upgrade lands. [ComputingForGeeks has a tested upgrade walkthrough](https://computingforgeeks.com/llama-cpp-1-0-whats-new/) if you want step-by-step guidance. ## Who Needs to Act The affected surface area depends on how you use llama.cpp. **Command-line users** running llama-server or llama-cli can upgrade on their normal schedule — no source changes needed. **C API consumers**, meaning anyone who links libllama directly in custom code, Ollama internals, or llama-server wrappers, need to audit their symbol usage against the removed list before upgrading. **Python binding users** (llama-cpp-python) should wait until the binding package tags a compatible release rather than upgrading the underlying library directly. The practical migration checklist is short: search your codebase for the 36 removed symbols, swap in the current API equivalents, update any soname references, recompile, and run your tests. The [release notes on GitHub](https://github.com/ggml-org/llama.cpp/releases) list every removed symbol with its replacement. ## New Capabilities in v1.0.0 The breaking changes get the attention, but v1.0.0 also ships useful additions. OCP FP8 KV cache (`f8_e4m3` type, controlled via `-ctk`/`-ctv` flags) reduces memory usage for long conversations. A new host-memory MoE expert cache with configurable CPU share lets mixture-of-experts models run on machines without massive VRAM — think running Kimi-K3.1-Pro locally without a data-center GPU. Three new model architectures land: Kimi-K3.1-Pro, Ripple, and xing4_0. The server also gains an OpenAI-compatible `/v1/audio/speech` endpoint and security fixes for CORS, DNS rebinding, and HF_TOKEN scoping. ## What It Signals Georgi Gerganov pushed the first commit to llama.cpp in March 2023 to run Meta’s leaked Llama model on a MacBook with no GPU and no dependencies. It was a weekend project. It became the runtime underneath tools with [over seven million combined active users](https://mlq.ai/news/llamacpp-reaches-version-10-and-promises-a-stable-api-for-local-ai-apps/). In February 2026, the team joined Hugging Face full-time. v1.0.0 is not a feature release — it is an infrastructure signal. The local AI stack is maturing past the “fun experiment” phase into something you can build a product on. The next breaking change will announce itself. That is new.