quantcpp

Python bindings for quant.cpp -- a minimal C inference engine for local LLMs with KV cache compression.

Installation

pip install quantcpp

Pre-built wheels are published for Linux (x86_64, aarch64), macOS (Intel + Apple Silicon), and Windows (x64). On other platforms pip falls back to the source distribution and compiles quant.h automatically using your system C compiler — no external dependencies.

From source (dev tree)

cd quant.cpp/bindings/python
pip install .          # build + install
pip install -e .       # editable / development install

To point at a pre-built library instead:

export QUANTCPP_LIB=/path/to/libquant.dylib
pip install .

Requirements

Python >= 3.8
A C compiler (cc, gcc, or clang)
The quant.cpp repository (for quant.h)

Usage

Quick start (auto-download)

from quantcpp import Model

m = Model.from_pretrained("Phi-3.5-mini")  # ~2.4 GB, downloaded once and cached
print(m.ask("What is 2+2?"))

from_pretrained accepts any name from quantcpp.available_models(). Phi-3.5-mini is the recommended default — 3.8B params with the smallest vocab (32K) in the registry, which makes the per-token lm_head matmul the fastest of any model we ship. Other ready-to-use names:

SmolLM2-1.7B — lightweight all-rounder (1.7 GB, vocab 49K)
Llama-3.2-1B — smallest download (750 MB) but slower at inference
SmolLM2-135M — 138 MB demo model, low quality
Qwen3.5-0.8B

You can also load any local GGUF file directly:

m = Model("model.gguf")
print(m.ask("What is 2+2?"))

Streaming generation

for token in m.generate("Once upon a time"):
    print(token, end="", flush=True)

Multi-turn chat with KV cache reuse

m = Model.from_pretrained("Phi-3.5-mini")
history = ""
while True:
    user = input("\nYou: ")
    history += f"<|user|>\n{user}<|end|>\n<|assistant|>\n"
    print("AI: ", end="", flush=True)
    reply = ""
    for tok in m.chat(history):
        print(tok, end="", flush=True)
        reply += tok
    history += reply + "<|end|>\n"

m.chat() reuses the KV cache across turns — turn N's prefill cost is O(new tokens), not O(history). Catch quantcpp.ChatContextOverflow if the conversation exceeds the model's context window.

Context manager

with Model.from_pretrained("Phi-3.5-mini") as m:
    print(m.ask("Explain gravity in one sentence"))

Configuration

m = Model(
    "model.gguf",
    temperature=0.5,      # Lower = more deterministic
    top_p=0.9,            # Nucleus sampling
    max_tokens=512,       # Max tokens per generation
    n_threads=8,          # CPU threads
    kv_compress=2,        # 0=off, 1=4-bit K+V, 2=delta+3-bit
)

Convenience loader

from quantcpp import load

m = load("model.gguf", kv_compress=2)
print(m.ask("Hello!"))

API Reference

`Model(path, *, temperature=0.7, top_p=0.9, max_tokens=256, n_threads=4, kv_compress=1)`

Load a GGUF model file and create an inference context.

path -- Path to a .gguf model file.
temperature -- Sampling temperature (0.0 = greedy).
top_p -- Nucleus sampling threshold.
max_tokens -- Maximum tokens per generation.
n_threads -- CPU thread count.
kv_compress -- KV cache compression mode (0=off, 1=4-bit, 2=delta+3-bit).

`Model.from_pretrained(name) -> Model`

Download a registered model from HuggingFace (cached at ~/.cache/quantcpp/) and return an open Model. See quantcpp.available_models() for the registry.

`Model.ask(prompt) -> str`

Generate a complete response. Returns the full text.

`Model.generate(prompt) -> Iterator[str]`

Stream tokens one at a time. Yields individual token strings.

`Model.chat(prompt) -> Iterator[str]`

Stream tokens with KV cache reuse across calls — turn N pays only for the new bytes since turn N-1. Pass prompt=None (or call Model.reset_chat()) to start a fresh session. Raises quantcpp.ChatContextOverflow when the history exceeds the model's context window (the C side has already auto-reset by then).

`Model.close()`

Release resources. Called automatically via with or garbage collection.

`Model.path -> str`

The path to the loaded model file (read-only property).

Library search order

The package looks for the compiled shared library in this order:

QUANTCPP_LIB environment variable
Installed alongside the Python package (normal pip install)
build/ relative to the project root (development)
System library path

Running tests

cd bindings/python
python -m pytest tests/

Metadata

Release files for quantcpp 0.13.0

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

Source distribution (sdist)

Source distribution for quantcpp 0.13.0
File	Size	Uploaded
quantcpp-0.13.0.tar.gz	319.3 kB	Apr 12, 2026	Details

Built distributions (wheels)

Table of built distributions (wheels) for quantcpp 0.13.0
File	Interpreter	ABI	Platform	Reset
quantcpp-0.13.0-cp313-cp313-musllinux_1_2_x86_64.whl 277.6 kB Apr 12, 2026	CPython 3.13	CPython 3.13	Linux musl 1.2+ x86-64	Details
quantcpp-0.13.0-cp313-cp313-musllinux_1_2_aarch64.whl 274.0 kB Apr 12, 2026	CPython 3.13	CPython 3.13	Linux musl 1.2+ ARM64	Details
quantcpp-0.13.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 276.1 kB Apr 12, 2026	CPython 3.13	CPython 3.13	Linux glibc 2.17+ x86-64	Details
quantcpp-0.13.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 273.4 kB Apr 12, 2026	CPython 3.13	CPython 3.13	Linux glibc 2.17+ ARM64	Details
quantcpp-0.13.0-cp313-cp313-macosx_11_0_arm64.whl 284.7 kB Apr 12, 2026	CPython 3.13	CPython 3.13	macOS 11.0+ ARM64	Details
quantcpp-0.13.0-cp312-cp312-musllinux_1_2_x86_64.whl 277.6 kB Apr 12, 2026	CPython 3.12	CPython 3.12	Linux musl 1.2+ x86-64	Details
quantcpp-0.13.0-cp312-cp312-musllinux_1_2_aarch64.whl 274.0 kB Apr 12, 2026	CPython 3.12	CPython 3.12	Linux musl 1.2+ ARM64	Details
quantcpp-0.13.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 276.1 kB Apr 12, 2026	CPython 3.12	CPython 3.12	Linux glibc 2.17+ x86-64	Details
quantcpp-0.13.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 273.4 kB Apr 12, 2026	CPython 3.12	CPython 3.12	Linux glibc 2.17+ ARM64	Details
quantcpp-0.13.0-cp312-cp312-macosx_11_0_arm64.whl 284.7 kB Apr 12, 2026	CPython 3.12	CPython 3.12	macOS 11.0+ ARM64	Details
quantcpp-0.13.0-cp311-cp311-musllinux_1_2_x86_64.whl 277.6 kB Apr 12, 2026	CPython 3.11	CPython 3.11	Linux musl 1.2+ x86-64	Details
quantcpp-0.13.0-cp311-cp311-musllinux_1_2_aarch64.whl 274.0 kB Apr 12, 2026	CPython 3.11	CPython 3.11	Linux musl 1.2+ ARM64	Details
quantcpp-0.13.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 276.1 kB Apr 12, 2026	CPython 3.11	CPython 3.11	Linux glibc 2.17+ x86-64	Details
quantcpp-0.13.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 273.4 kB Apr 12, 2026	CPython 3.11	CPython 3.11	Linux glibc 2.17+ ARM64	Details
quantcpp-0.13.0-cp311-cp311-macosx_11_0_arm64.whl 284.7 kB Apr 12, 2026	CPython 3.11	CPython 3.11	macOS 11.0+ ARM64	Details
quantcpp-0.13.0-cp310-cp310-musllinux_1_2_x86_64.whl 277.6 kB Apr 12, 2026	CPython 3.10	CPython 3.10	Linux musl 1.2+ x86-64	Details
quantcpp-0.13.0-cp310-cp310-musllinux_1_2_aarch64.whl 274.0 kB Apr 12, 2026	CPython 3.10	CPython 3.10	Linux musl 1.2+ ARM64	Details
quantcpp-0.13.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 276.1 kB Apr 12, 2026	CPython 3.10	CPython 3.10	Linux glibc 2.17+ x86-64	Details
quantcpp-0.13.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 273.4 kB Apr 12, 2026	CPython 3.10	CPython 3.10	Linux glibc 2.17+ ARM64	Details
quantcpp-0.13.0-cp310-cp310-macosx_11_0_arm64.whl 284.7 kB Apr 12, 2026	CPython 3.10	CPython 3.10	macOS 11.0+ ARM64	Details
quantcpp-0.13.0-cp39-cp39-musllinux_1_2_x86_64.whl 277.6 kB Apr 12, 2026	CPython 3.9	CPython 3.9	Linux musl 1.2+ x86-64	Details
quantcpp-0.13.0-cp39-cp39-musllinux_1_2_aarch64.whl 274.0 kB Apr 12, 2026	CPython 3.9	CPython 3.9	Linux musl 1.2+ ARM64	Details
quantcpp-0.13.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 276.1 kB Apr 12, 2026	CPython 3.9	CPython 3.9	Linux glibc 2.17+ x86-64	Details
quantcpp-0.13.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl 273.4 kB Apr 12, 2026	CPython 3.9	CPython 3.9	Linux glibc 2.17+ ARM64	Details
quantcpp-0.13.0-cp39-cp39-macosx_11_0_arm64.whl 284.7 kB Apr 12, 2026	CPython 3.9	CPython 3.9	macOS 11.0+ ARM64	Details

Total release size: 7.2 MB

Release files / quantcpp-0.13.0.tar.gz

Download URL	quantcpp-0.13.0.tar.gz
Size	319.3 kB
Tags	Source
SHA-256 checksum How to use checksums	`bafc334fcc6b9f528488e4ac2f465c0c9bbdd901ca3be689a41cc19286c8302f`
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Uploaded via	`twine/6.1.0 CPython/3.13.12`

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Publishing platform: GitHub Actions
Publishing repository: github.com/quantumaikr/quant.cpp
Publishing commit: github.com/quantumaikr/quant.cpp/tree/b60ce4ed44d0ca1cf152aa855a106cc5f2e616c6

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Publishing configuration: github.com/quantumaikr/quant.cpp/blob/b60ce4ed44d0ca1cf152aa855a106cc5f2e616c6/.github/workflows/publish.yml
Publishing logs: github.com/quantumaikr/quant.cpp/actions/runs/24305044206/attempts/1

Artifact

Subject: quantcpp-0.13.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
SHA-256 checksum: efeca4c37d69f32b22170e336fe72ab35bad72bebd975bf5d8acc8ade76c1a4d Verifying attestations

Release files / quantcpp-0.13.0-cp39-cp39-macosx_11_0_arm64.whl

Download URL	quantcpp-0.13.0-cp39-cp39-macosx_11_0_arm64.whl
Size	284.7 kB
Tags	CPython 3.9 macOS 11.0+ ARM64
SHA-256 checksum How to use checksums	`e87e1dd7f70cfab94f467f296077a806556d1d4dd0a6393a2fb81cb98d83ba2c`
BLAKE2b-256 checksum How to use checksums	`4e6fb41b4ed0a3a50ae52397b8f02939bfcb420e93dc34e09ed27f7f5d48ee57`
Upload date	Apr 12, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.13.12`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/quantumaikr/quant.cpp
Publishing commit: github.com/quantumaikr/quant.cpp/tree/b60ce4ed44d0ca1cf152aa855a106cc5f2e616c6

Workflow

Publishing configuration: github.com/quantumaikr/quant.cpp/blob/b60ce4ed44d0ca1cf152aa855a106cc5f2e616c6/.github/workflows/publish.yml
Publishing logs: github.com/quantumaikr/quant.cpp/actions/runs/24305044206/attempts/1

Artifact

Subject: quantcpp-0.13.0-cp39-cp39-macosx_11_0_arm64.whl
SHA-256 checksum: e87e1dd7f70cfab94f467f296077a806556d1d4dd0a6393a2fb81cb98d83ba2c Verifying attestations