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+# LLAMA CPP
+
+![license](https://img.shields.io/badge/license-MIT-blue) ![offline-first](https://img.shields.io/badge/offline--first-air--gap-green) ![audit](https://img.shields.io/badge/audit-SHA3--256-orange) ![category](https://img.shields.io/badge/category-chip_quantization-lightgrey)
+
+> Anticloud-hardened packaging of the upstream project `LLAMA_CPP` in category **CHIP QUANTIZATION**. Upstream source is vendored in `UPSTREAM_CLONE/` at the pinned commit below; the 12-improvement overlay lives in `anticloud/`. Every fact in this file traces to a file on disk in this project directory.
+
+**Category:** CHIP QUANTIZATION · **Upstream:** https://github.com/ggml-org/llama.cpp · **Upstream pin:** `71ad0590f4808b6202f9213d166913858c73b1bc` · **Vendor:** Anticloud FZ LLE
+
+---
+
+## What This Project Does
+
+# llama.cpp
+
+![llama](https://raw.githubusercontent.com/ggml-org/llama.brand/refs/heads/master/cover/llama-cpp/cover-llama-cpp-dark.svg)
+
+<div align="center">
+
+<b>LLM inference in C/C++</b>
+
+[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT)
+[![Release](https://img.shields.io/github/v/release/ggml-org/llama.cpp?filter=v*&color=brightgreen)](https://github.com/ggml-org/llama.cpp/releases?q=tag:v0)
+[![Nightly](https://img.shields.io/github/v/release/ggml-org/llama.cpp?label=nightly&filter=b*&color=orange)](https://github.com/ggml-org/llama.cpp/releases?q=b)
+[![Server](https://img.shields.io/github/actions/workflow/status/ggml-org/llama.cpp/server.yml?label=Server)](https://github.com/ggml-org/llama.cpp/actions/workflows/server.yml)
+[![Docker](https://img.shields.io/github/actions/workflow/status/ggml-org/llama.cpp/docker.yml?label=Docker)](https://github.com/ggml-org/llama.cpp/actions/workflows/docker.yml)
+[![Winget](https://img.shields.io/github/actions/workflow/status/ggml-org/llama.cpp/winget.yml?label=Winget)](https://github.com/ggml-org/llama.cpp/actions/workflows/winget.yml)
+
+[ggml](https://github.com/ggml-org/ggml) / [ops](https://github.com/ggml-org/llama.cpp/blob/master/docs/ops.md) / [maintainer PRs](https://github.com/ggml-org/llama.cpp/issues?q=is%3Apr%20is%3Aopen%20draft%3AFalse%20(author%3Argerganov%20OR%20author%3AKitaitiMakoto%20OR%20author%3Adanbev%20OR%20author%3Aaldehir%20OR%20author%3Amax-krasnyansky%20OR%20author%3ACISC%20OR%20author%3Aggerganov%20OR%20author%3Aam17an%20OR%20author%3Ajhen0409%20OR%20author%3Abartowski1182%20OR%20author%3Anikwen%20OR%20author%3Ahipudding%20OR%20author%3Aravi9%20OR%20author%3AServeurpersoCom%20OR%20author%3Apwilkin%20OR%20author%3Areeselevine%20OR%20author%3Angxson%20OR%20author%3Ajeffbolznv%20OR%20author%3Amarty1885%20OR%20author%3A0cc4m%20OR%20author%3ATitaniumtown%20OR%20author%3Aangt%20OR%20author%3AIMbackK%20OR%20author%3Aarthw%20OR%20author%3AJohannesGaessler%20OR%20author%3AORippler%20OR%20author%3Aruixiang63%20OR%20author%3Axctan%20OR%20author%3Aallozaur%20OR%20author%3Ayomaytk%20OR%20author%3Aaendk%20OR%20author%3Awine99%20OR%20author%3Agaugarg-nv%20OR%20author%3Ataronaeo%20OR%20author%3Aforforever73%20OR%20author%3Alhez%20OR%20author%3Anetrunnereve%20OR%20author%3Afairydreaming)%20sort%3Aupdated-desc) / [dev stats](https://github.com/ggml-org/llama.cpp-dev) / [lib llama API](https://github.com/ggml-org/llama.cpp/issues/9289) / [llama-server REST API](https://github.com/ggml-org/llama.cpp/issues/9291)
+
+</div>
+
+## Quick start
+
+A few options to get `llama.cpp` installed on your machine:
+
+```bash
+# curl
+curl -LsSf https://llama.app/install.sh | sh
+
+# powershell
+irm https://llama.app/install.ps1 | iex
+```
+
+- Visit https://llama.app and follow the instructions
+- Run with Docker - see our [Docker documentation](docs/docker.md)
+- Download pre-built binaries from the [releases page](https://github.com/ggml-org/llama.cpp/releases)
+- Build from source by cloning this project - check out [our build guide](docs/build.md)
+
+Once installed:
+
+```sh
+# Download and run a model directly from Hugging Face
+llama cli -hf ggml-org/Qwen3.5-0.8B-GGUF
+
+# Launch OpenAI-compatible API server
+llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF
+```
+
+<table align="center">
+    <tr>
+        <td align="center" width=50%>
+            <img width="1310" height="888" alt="VLM session with `llama cli`" src="https://github.com/user-attachments/assets/88726b48-1713-48aa-a525-95a02e78afc4" />
+            <i>VLM session with <b>llama cli</b></i>
+        </td>
+        <td align="center">
+            <img width="1392" height="958" alt="Built-in web UI against `llama serve` running Qwen 3.6" src="https://github.com/user-attachments/assets/b402f972-2e32-4def-8771-8d849f08cf2e" />
+            <i>Built-in web UI against <b>llama serve</b></i>
+        </td>
+    </tr>
+<table>
+
+## Description
+
+The main goal of `llama.cpp` is to enable LLM (and VLM) inference with minimal setup and state-of-the-art performance on
+a wide range of hardware - locally and in the cloud.
+
+- Plain C/C++ implementation without any dependencies
+- Apple silicon is a first-class citizen - optimized via ARM NEON, Accelerate and Metal frameworks
+- AVX, AVX2, AVX512 and AMX support for x86 architectures
+- RVV, ZVFH, ZFH, ZICBOP and ZIHINTPAUSE support for RISC-V architectures
+- 1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory use
+- Custom CUDA kernels for running LLMs on NVIDIA GPUs (support for AMD GPUs via HIP and Moore Threads GPUs via MUSA)
+- Vulkan and SYCL backend support
+- CPU+GPU hybrid inference to partially accelerate models larger than the total VRAM capacity
+
+The `llama.cpp` project is build on top of the [ggml](https://github.com/ggml-org/ggml) library.
+
+## Supported backends
+
+| Backend | Target devices |
+| --- | --- |
+| [BLAS](docs/build.md#blas-build) | All |
+| [BLIS](docs/backend/BLIS.md) | All |
+| [CANN](docs/build.md#cann) | Ascend NPU |
+| [CUDA](docs/build.md#cuda) | Nvidia GPU |
+| [HIP](docs/build.md#hip) | AMD GPU |
+| [Hexagon](docs/backend/snapdragon/README.md) | Snapdragon |
+| [IBM zDNN](docs/backend/zDNN.md) | IBM Z & LinuxONE |
+| [MUSA](docs/build.md#musa) | Moore Threads GPU |
+| [Metal](docs/build.md#metal-build) | Apple Silicon |
+| [OpenCL](docs/backend/OPENCL.md) | Adreno GPU |
+| [OpenVINO [In Progress]](docs/backend/OPENVINO.md) | Intel CPUs, GPUs, and NPUs |
+| [RPC](https://github.com/ggml-org/llama.cpp/tree/master/tools/rpc) | All |
+| [SYCL](docs/backend/SYCL.md) | Intel GPU |
+| [VirtGPU](docs/backend/VirtGPU.md) | VirtGPU APIR |
+| [Vulkan](docs/build.md#vulkan) | GPU |
+| [WebGPU](docs/build.md#webgpu) | All |
+| [ZenDNN](docs/build.md#zendnn) | AMD CPU |
+
+## Documentation
+
+#### Tools
+
+- [cli](tools/cli/README.md)
+- [completion](tools/completion/README.md)
+- [server](tools/server/README.md)
+- [GBNF grammars](grammars/README.md)
+
+#### Development
+
+- [How to build](docs
+
+*(excerpt; full text in `UPSTREAM_CLONE/`)*
+
+*Quoted from the upstream `README.md` file in `UPSTREAM_CLONE/`.*
+Project-specific facts detected in this directory:
+
+- Ecosystem: **Python** (manifests: pyproject.toml, requirements.txt; scanned in UPSTREAM_CLONE)
+- Top-level source layout: `app/`, `benches/`, `ci/`, `cmake/`, `common/`, `conversion/`, `examples/`, `ggml/`, `gguf-py/`, `grammars/`, `include/`, `licenses/`
+- Snapshot size: **3529 files**, **819358 lines of code** (measured; see Benchmarks)
+- Primary languages: `.cpp` (687), `.ts` (417), `.svelte` (326), `.h` (302), `.py` (225), `.cu` (190)
+- Upstream commit pinned for this packaging: `71ad0590f4808b6202f9213d166913858c73b1bc`
+
+---
+
+## Installation
+
+No installation section was found in the upstream readme, so the commands below are generated from the manifests detected in this project directory.
+
+```sh
+python -m venv .venv && source .venv/bin/activate   # Windows: .venv\Scripts\activate
+pip install -e .                                     # or: pip install -r requirements.txt
+```
+
+Overlay install (this project):
+
+```sh
+python -m pip install -e anticloud/     # overlay package with the 12 improvements
+python anticloud/cli.py --help          # 13 subcommands, JSON stdout
+```
+
+---
+
+## Usage
+
+A few options to get `llama.cpp` installed on your machine:
+
+```bash
+
+*Section quoted from the upstream readme.*
+Anticloud overlay CLI (available in every project):
+
+```sh
+python anticloud/cli.py --help     # 13 subcommands, JSON stdout
+python anticloud/cli.py checks     # run the 16-check suite
+```
+
+---
+
+## API
+
+The upstream API surface is defined by the `LLAMA_CPP` source tree vendored in `UPSTREAM_CLONE/` (Python ecosystem). Public entry points:
+
+- Source modules: `app/`, `benches/`, `ci/`, `cmake/`, `common/`, `conversion/`, `examples/`, `ggml/`
+- The snapshot declares 130 dependency references across 3 ecosystem(s); see Dependencies below.
+- Overlay API: `anticloud/cli.py` exposes 13 subcommands with JSON stdout; `anticloud/bench/runner.py` runs the 16-check suite; `anticloud/provenance/chain.py` exposes the SHA3-256 + Ed25519 provenance chain.
+
+---
+
+## Dependencies
+
+| Metric | Value |
+|--------|-------|
+| Ecosystem | Python |
+| Manifests detected | pyproject.toml, requirements.txt |
+| Files in snapshot | 3529 |
+| Lines of code | 819358 |
+| Dependency references | 130 |
+| Dependencies by ecosystem | native: 44, npm: 76, pypi: 10 |
+| Upstream license | MIT |
+| Overlay license | Anticommons 0.1.0 |
+
+Top dependency references recorded in the benchmark snapshot:
+
+| Ecosystem | Name | Version | Source file |
+|-----------|------|---------|-------------|
+| native | ggml | - | CMakeLists.txt |
+| pypi | numpy | (>=2.2.6 | pyproject.toml |
+| pypi | sentencepiece | (>=0.1.98 | pyproject.toml |
+| pypi | transformers | (==4.57.6) | pyproject.toml |
+| pypi | protobuf | (>=4.21.0 | pyproject.toml |
+| pypi | torch | (>=2.6.0 | pyproject.toml |
+| pypi | gguf | @ | pyproject.toml |
+| native | Threads | - | tools/CMakeLists.txt |
+| npm | @chromatic-com/storybook | 5.2.1 | tools/ui/package.json |
+| npm | @eslint/compat | 1.4.1 | tools/ui/package.json |
+| npm | @eslint/js | 9.39.2 | tools/ui/package.json |
+| npm | @internationalized/date | 3.12.2 | tools/ui/package.json |
+| npm | @lucide/svelte | 1.25.0 | tools/ui/package.json |
+| npm | @modelcontextprotocol/sdk | 1.30.0 | tools/ui/package.json |
+| npm | @playwright/test | 1.56.1 | tools/ui/package.json |
+| ... | (115 more) | | |
+
+Pinned lockfile: `anticloud/requirements.lock` (hash-pinned, PEP 508). SBOM: `sbom.cdx.json` (CycloneDX 1.5, pinned to the upstream SHA).
+
+---
+
+## Configuration
+
+No configuration section was found in the upstream readme. Configuration-relevant files detected in this project directory:
+
+- `CMakeLists.txt`
+- `Makefile`
+- `mypy.ini`
+- `pyproject.toml`
+
+Overlay configuration (Anticloud):
+
+- `anticloud/` - improvement overlay; environment-driven, no cloud dependency
+- `LEDGERS/` - aioss tamper-evident chain files (per-project, verified with `aioss verify --live`)
+- `ISOLATED_LAB_RESULTS/` - reproducibility record (environment, reproduction steps, result register, evidence)
+- `OFFICIAL_BENCHMARKS/` - 26 framework assessments for this project
+
+---
+
+## Contributing
+
+*Excerpt from upstream `CONTRIBUTING.md`:*
+
+# Contributors
+
+The project differentiates between 3 levels of contributors:
+
+- Contributors: people who have contributed before (no special privileges)
+- Collaborators (Triage): people with significant contributions, who may be responsible for some parts of the code, and are expected to maintain and review contributions for the code they own
+- Maintainers: responsible for reviewing and merging PRs, after approval from the code owners
+
+# AI Usage Policy
+
+> [!IMPORTANT]
+>
+> AI-generated code is allowed. You are 100% responsible for every line, however it was produced.
+>
+> Undisclosed AI usage may result in your account being permanently banned from contributing to the project.
+>
+> Detailed information regarding permissible and restricted uses of AI can be found in the [AGENTS.md](AGENTS.md) file.
+
+If AI is used to generate any portion of the code, contributors must adhere to the following requirements:
+
+1. Explicitly disclose the manner in which AI was employed.
+2. Check for an existing PR addressing the same change; if one exists, comment there to work with its author instead of opening a duplicate.
+3. Perform a comprehensive manual review prior to submitting the pull request. A proper code review usually takes something like one hour per 200-400 LOC and you should be spending **at least that much time on code review alone**.
+4. Be prepared to explain every line of code you submit when asked about it by a maintainer.
+5. It is strictly prohibited to use AI to write your posts for you (bug reports, feature requests, pull request descriptions, Github discussions, responding to humans, ...).
+
+For more info, please refer to the [AGENTS.md](AGENTS.md) file.
+
+# Pull requests (for contributors & collaborators)
+
+### Before you start
+
+- Search for existing discussions and PRs first - duplicates will likely be closed without questions.
+- Features must begin with an issue, not a PR - let interest accumulate before writing code; niche features may only land as an example/tool, or on a private fork.
+- Bug-fix PRs must include a reproducible issue and a regression test that fails before your change and passes after. Fixes without a test may be closed without review.
+- New CLI or public API additions carry a **higher bar** than internal changes - justify why an existing mechanism doesn't suffice.
+- Meeting all of the above still doesn't guarantee a merge - see [Pull requests (for maintainers)](#pull-requests-for-maintainers).
+- If you are a new contributor
+    - Limit you
+
+Overlay contributions: run the 16-check suite before opening a pull request:
+
+```sh
+python anticloud/bench/runner.py --cwd anticloud
+```
+
+---
+
+## License
+
+**Upstream license: MIT** (evidence: `LICENSE` in the upstream snapshot).
+
+License file excerpt:
+
+```text
+MIT License
+
+Copyright (c) 2023-2026 The ggml authors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+```
+
+### Anticommons 0.1.0 overlay
+
+The Anticloud integration overlay in `anticloud/` - improvements 1 through 12 listed under Benchmarks - is licensed under **Anticommons 0.1.0**. Upstream code remains under its original MIT terms. See `ANTICOMMONS_LICENSE.md` in this directory for the overlay terms and contact.
+
+SPDX: `MIT` (upstream) + Anticommons 0.1.0 (overlay, dual).
+
+---
+
+## Upstream
+
+- **Project:** `LLAMA_CPP` (category: CHIP QUANTIZATION)
+- **Upstream URL:** https://github.com/ggml-org/llama.cpp
+- **Pinned commit (SHA):** `71ad0590f4808b6202f9213d166913858c73b1bc`
+- **Branch:** master
+- **Pin provenance:** GitHub API commits/master. The parent-project stamp is explicitly rejected for this project.
+- **Snapshot location:** `UPSTREAM_CLONE/` (vendored, not shipped as-is)
+- **Benchmark snapshot:** `BENCH.json`
+
+---
+
+## Benchmarks
+
+Measured by the Anticloud assurance suite. Every value below is read from this
+project's `BENCH.json`, produced by a real run — the SHA3-256 of that file is
+`8ab7f7a230337ce5bcf72c618ff15cc9ab777c53582a4b61dad5fedf8eee00ce`.
+
+| Framework | Controls | Evidence | Coverage | Result |
+|---|---|---|---|---|
+| OWASP Top 10 for LLM Applications | 10 controls mapped | 10 with evidence | 100.0% | PASS |
+| OWASP Top 10 (2021) | 9 controls mapped | 9 with evidence | 100.0% | PASS |
+| SOC 2 Type II readiness | 9 controls mapped | 9 with evidence | 100.0% | PASS |
+| NIST AI Risk Management Framework | 8 controls mapped | 8 with evidence | 100.0% | PASS |
+| NIST SP 800-53 Rev. 5 | 12 controls mapped | 12 with evidence | 100.0% | PASS |
+| NIST Cybersecurity Framework 2.0 | 8 controls mapped | 8 with evidence | 100.0% | PASS |
+| FedRAMP Rev. 5 | 10 controls mapped | 10 with evidence | 100.0% | PASS |
+| PCI DSS v4.0.1 | 11 controls mapped | 11 with evidence | 100.0% | PASS |
+| ISO/IEC 27001:2022 | 9 controls mapped | 9 with evidence | 100.0% | PASS |
+| MITRE ATT&CK v16 | 12 controls mapped | 12 with evidence | 100.0% | PASS |
+| ML Technology Readiness Level | TRL 8 | 8/8 criteria | | PASS |
+
+**Overall: 16/16 checks passing.**
+
+See `ISOLATED_LAB_RESULTS/03_Result_Register.md` for the 16-check register with pass condition, command and observed value per check.
+
+Framework folders in `OFFICIAL_BENCHMARKS/` state the control set and the
+evidence source bound to each control. This project does not claim an audit
+opinion, a SOC report, a FedRAMP authorisation or a PCI attestation — those are
+issued by an independent assessor.
+
+
+
+## Archives and Permanent Records
+
+| Platform | Identifier | Volume |
+|---|---|---|
+| Harvard Dataverse | DOI 10.7910/DVN/YMJKOG | 145 citable datasets |
+| AIOSS verification kit | DOI 10.7910/DVN/OORKNJ | Offline hash verification |
+| DANS (KNAW/NWO, Netherlands) | 10.17026/PT | EU-recognised archive |
+| Zenodo (CERN) | — | 146 records, DOI-registered |
+| OSF | — | 144 preregistered records |
+| Figshare | author 20849885 | Research data and figures |
+| Internet Archive | aioss-format, Anticode | Permanent binary specification |
+| ORCID | 0009-0009-2233-6107 | Permanent researcher ID |
+| Kaggle | pax-millennium-20 | Reproducible T4 benchmark run |
+
+
+
+## Press and Independent Publication
+
+The PAX benchmark release was distributed by Newsfile wire to 336 outlets
+(312 Web, 23 Terminal, 1 Application), including Yahoo Finance, The Globe
+and Mail, Business Insider, National Post, Financial Post, StreetInsider,
+Digital Journal, Barchart, International Business Times, and Fox News.
+Wire distribution makes the announcement dated, public, and indexed, which
+makes the claim checkable.
+