Skip to main content

llama-cpp-bin

Pre-built llama.cpp server binaries as a py package. Install a wheel for your platform and run it.

Install

Pre-built wheels (recommended)

pip install --index-url https://vladlearns.github.io/llama-cpp-bin/whl/cpu llama-cpp-bin
pip install --index-url https://vladlearns.github.io/llama-cpp-bin/whl/cu124 llama-cpp-bin
pip install --index-url https://vladlearns.github.io/llama-cpp-bin/whl/cu131 llama-cpp-bin
pip install --index-url https://vladlearns.github.io/llama-cpp-bin/whl/rocm llama-cpp-bin
pip install --index-url https://vladlearns.github.io/llama-cpp-bin/whl/vulkan llama-cpp-bin

Pin to a specific version:

pip install --index-url https://vladlearns.github.io/llama-cpp-bin/whl/cu124 llama-cpp-bin==9095.0.0

PyPI (builds from source)

If no pre-built wheel matches your platform, pip falls back to building from the sdist on PyPI:

pip install llama-cpp-bin

You will need CMake, a c++ compiler, and the llama.cpp source submodule.

Dev

git clone --recurse-submodules https://github.com/vladlearns/llama-cpp-bin
cd llama-cpp-bin
CMAKE_ARGS="-DGGML_CUDA=ON" pip install -v .

Run

CLI:

llama-cpp-server -m your-model.gguf --port 8080

Python:

from llama_cpp_bin import run_server
proc = run_server("your-model.gguf", port=8080)
proc.wait()

Or get the binary path and run it yourself:

import llama_cpp_bin
import subprocess
binary = llama_cpp_bin.get_binary_path()
subprocess.Popen([binary, "--model", "your-model.gguf"])

Release files for llama-cpp-bin 10816.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for llama-cpp-bin 10816.0.0
File Size Uploaded
llama_cpp_bin-10816.0.0.tar.gz 36.8 MB Details

Release files / llama_cpp_bin-10816.0.0.tar.gz

Download URL llama_cpp_bin-10816.0.0.tar.gz
Size 36.8 MB
Tags Source
SHA-256 checksum
How to use checksums
bc0464166ad9e0b93a57ca257c266ab01d7fbdabd20390cecffcdd3e55a45bba
BLAKE2b-256 checksum
How to use checksums
21c7bcf300b8d45617c985f1854b6b1fe16a92ced659b974551b6a389d87da36
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 5, 2026.

Transparency log

Release history Release notifications | RSS feed

This release

10816.0.0 This release

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page