Faiss.NET

High-performance C#/.NET bindings for Faiss.

Faiss.NET gives you near-native performance with clean, idiomatic C# wrappers while staying as close as possible to the original Faiss API.

• Faiss v1.15.0
• .NET 9.0

Important

This library is under active development. Core indexes and functionality are usable, but the API may still evolve and not every feature is complete yet.

Development Roadmap

About ~90% is done. I am reworking the class hierarchy to make the api as elegant as possible. This includes preventing most of the footguns there are with faiss, including making the compiler enforce all the rules.

• Adding bindings for distances_c.h
• Improving class hierarchy and generic constraints design to further prevent footguns (~ September 2026)
• Adding more tests (~ Oktober 2026)
• Adding examples (~ Oktober 2026)
• v1.0 Release 🚀 (~ November 2026)

Features

• Thin, "bare-metal" bindings with minimal overhead
• Extensions on top bindings for excellent DX
• Cross-platform support (Windows, Linux, macOS all x64 & arm64)
• Strongly-typed wrappers + generic factory for all Faiss indexes
• GPU acceleration (CUDA & ROCm)
• Human written (no AI slop)
• It just works™

Table of Contents

• Installation
• Usage
• Supported Platforms
• License

Installation

Prerequisites

Windows

winget install --id Microsoft.VCRedist.2015+.x64 --silent

Linux

sudo apt-get install -y libopenblas0 libgomp1

macOS

brew install libomp

NuGet Package

Pick either the CPU only or the CPU + GPU support NuGet, do not mix on the same platform, it would cause undefined behavior.

CPU only

dotnet add package Faiss.NET.Native

CPU+GPU

CUDA

dotnet add package Faiss.NET.Native.Gpu.Cuda # Linux only
dotnet add package Faiss.NET.Native.Windows
dotnet add package Faiss.NET.Native.MacOS

ROCm

dotnet add package Faiss.NET.Native.Gpu.Rocm # Linux x64 only
dotnet add package Faiss.NET.Native.Windows
dotnet add package Faiss.NET.Native.MacOS

Usage

All examples assume using Faiss.Cpu.Extensions; plus the relevant type namespaces.

Quick start

using Faiss.Cpu.Indexes.Flat;

using var index = new IndexFlatL2(dimensions: 4);
index.Add([1, 2, 3, 4]);

using var result = index.Search([1, 2, 3, 4], k: 1);
var label = result.Labels[0]; // 0
var distance = result.Distances[0]; // 0f

Indexes

Embeddings - RAG

using Faiss.Cpu.Extensions;
using Faiss.Cpu.Indexes.Approximate;
using Faiss.Cpu.Indexes.Mapped;
using Faiss.Cpu.Search;
using Faiss.Cpu.Search.Parameters;
using Faiss.Cpu.Selectors;
using Faiss.Models;

var index = new IndexHNSW(dimensions: 4, metricType: MetricType.InnerProduct); // We don't need using here because takeOwnership below
using var mappedIndex = new IndexIDMap<IndexHNSW>(index, takeOwnership: true); // disposes index as soon as mappedIndex is disposed

mappedIndex.Add([new[] { 1f, 2f, 3f, 4f }, new[] { 2f, 3f, 4f, 1f }, new[] { 3f, 4f, 1f, 2f }, new[] { 4f, 1f, 2f, 3f }], [4, 3, 2, 1]);

var queryNeighborsCount = 2; // K
var searchResult = mappedIndex.SearchWithParams(new [] {1f, 1f, 2f, 3f}, queryNeighborsCount, new SearchParameters(new IDSelectorRange(2, 4)));
QueryResults queryResult = searchResult.GetQueryResults(0);

for (int i = 0; i < searchResult.K; i++)
{
    float distance = queryResult.Distances[i];
    long label     = queryResult.Labels[i];

    Console.WriteLine($"Rank {i}: label={label}, dist={distance}");
}

Serialization/Deserialization

using Faiss.Cpu.Extensions;
using Faiss.Cpu.Indexes.Approximate;
using Faiss.Cpu.Indexes.Mapped;
using Faiss.Cpu.Search;
using Faiss.Cpu.Search.Parameters;
using Faiss.Cpu.Selectors;
using Faiss.Models;

var index = new IndexHNSW(dimensions: 4, metricType: MetricType.InnerProduct); // We don't need using here because takeOwnership below
using var mappedIndex = new IndexIDMap<IndexHNSW>(index, takeOwnership: true); // disposes index as soon as mappedIndex is disposed

mappedIndex.Add([new[] { 1f, 2f, 3f, 4f }, new[] { 2f, 3f, 4f, 1f }, new[] { 3f, 4f, 1f, 2f }, new[] { 4f, 1f, 2f, 3f }], [4, 3, 2, 1]);

var queryNeighborsCount = 2; // K
var searchResult = mappedIndex.SearchWithParams(new [] {1f, 1f, 2f, 3f}, queryNeighborsCount, new SearchParameters(new IDSelectorRange(2, 4)));
QueryResults queryResult = searchResult.GetQueryResults(0);

for (int i = 0; i < searchResult.K; i++)
{
    float distance = queryResult.Distances[i];
    long label     = queryResult.Labels[i];

    Console.WriteLine($"Rank {i}: label={label}, dist={distance}");
}

Factory — approximate indexes

The factory string mirrors the upstream Faiss API: HNSW32, IVF256,Flat, PQ8x12, and so on.

using Faiss.Cpu.Factory;
using Faiss.Cpu.Indexes;
using Faiss.Models;

using var index = IndexFactory.Create<GenericIndex>("HNSW32", dimensions: 128, MetricType.L2);
index.Add(vectors);

using var result = index.Search(query, k: 5);

Need custom IDs instead of sequential 0..N? Wrap any index with IndexIDMap<T> and pass your own IDs to Add.

GPU acceleration

using Faiss.Gpu;
using Faiss.Gpu.Resources;

using var gpu = new GpuResourcesProvider();
using var gpuIndex = GpuIndexProvider.TransferToGpu(gpu, cpuIndex, deviceId: 0);

gpuIndex.Search(query, k: 10);

using var backOnCpu = GpuIndexProvider.TransferToCpu(gpuIndex);

See FaissNET.Examples for serialization, scalar quantization, IVF tuning, and more.

Supported Platforms

Platform	x64	arm64
Windows	✅	✅
Linux	✅	✅
macOS	✅	✅

GPU Acceleration

Backend	Platform	x64	arm64
CUDA	Linux	✅	✅
ROCm	Linux	✅	❌

Supported CUDA GPUs

Compute Capability	Architecture	Example GPUs
75	Turing	RTX 20-series, Tesla T4
80	Ampere	A100
86	Ampere	RTX 30-series, A40, A10, A16, A30
89	Ada Lovelace	RTX 40-series, L40, L40S, L4
90	Hopper	H100, H200
120	Blackwell	RTX 50-series, B100, B200, GB200

Supported ROCm GPUs

GFX Architecture	Architecture	Example GPUs
gfx90a	CDNA2	AMD Instinct MI210, MI250, MI250X
gfx942	CDNA3	AMD Instinct MI300A, MI300X, MI325X
gfx950	CDNA4	AMD Instinct MI355X, MI350 series
gfx1030 / 1031 / 1032	RDNA2	Radeon RX 6600–6900 series
gfx1100 / 1101 / 1102	RDNA3	Radeon RX 7700–7900 series
gfx1200 / 1201	RDNA4	Radeon RX 9060 series and RX 9070 series

License

See the LICENSE file for details.

Faiss.NET is not affiliated with Meta or the original Faiss project.