Spice Runtime Distributions

The Spice open source project provides multiple distribution variants to support different use cases and deployment scenarios.

note

The Spice runtime is 64-bit only. 32-bit platforms are not supported.

Image Channels

Channel	Image	Description
DockerHub	spiceai/spiceai	Official release images
GitHub Container Registry	ghcr.io/spiceai/spiceai	Official release images
GitHub Container Registry (Nightly)	ghcr.io/spiceai/spiceai-nightly	Nightly builds with additional variants
AWS Marketplace	—	Enterprise image
Azure Marketplace	—	Enterprise image (coming soon)
Spice Cloud Platform	—	Uses Enterprise image
Spice.ai Enterprise	—	Uses Enterprise image

note

Some variant distributions are only available in nightly images (data) or exclusively through the Spice Cloud Platform and Spice.ai Enterprise (NAS, CUDA, allocator variants).

Supported Platforms and Hardware Requirements

Platform	Architecture	Minimum CPU Features	Build Prerequisites
Linux	x86_64	AVX2, FMA, BMI1/2, LZCNT, POPCNT	—
Linux	aarch64 (arm64)	NEON, FP16 (FEAT_FP16), FHM (FEAT_FHM)	clang, lld
macOS	aarch64 (Apple Silicon)	Native (build host)	—
Windows	x86_64 (MSVC)	—	MSVC toolchain

note

Windows support is CLI (spice) only. The runtime daemon (spiced) is not supported on Windows natively — use WSL instead.

Distribution Availability

Distribution / Variant	Image Tag	Open Source	Spice Cloud	Enterprise
Default (Data + AI)	latest	✅	✅	✅
Data-only	latest-data	Nightly only	✅	✅
NAS (SMB + NFS)	—	Local build only	❌	✅
Metal (macOS)	—	Local build only	✅	✅
CUDA (Linux)	latest-cuda	Local build only	✅	✅
Allocator variants	latest-{jemalloc,mimalloc,sysalloc}	Local build only	✅	✅
ODBC connector	—	Local build only	✅	✅

Default Distribution

The default distribution includes all features including AI/ML model support. This is the recommended distribution for most users.

Included Features:

• All standard data connectors (PostgreSQL, MySQL, DuckDB, SQLite, ClickHouse, etc.)
• Embedded data accelerators (Spice Cayenne, DuckDB, SQLite)
• AI/ML model inference (LLMs, embeddings)
• Search capabilities (Vector and BM-25 Full-Text-Search)
• Default memory allocator (snmalloc)

note

The PostgreSQL data accelerator is only available in nightly builds. The PostgreSQL data connector is included in all distributions.

Installation:

curl https://install.spiceai.org | /bin/bash

Docker:

docker pull ghcr.io/spiceai/spiceai:latest
# or
docker pull spiceai/spiceai:latest

Data Distribution

The data distribution excludes AI/ML model support, resulting in a smaller binary size and reduced attack surface. Use this when data federation and acceleration capabilities are needed without AI features.

note

Open Source: Available in nightly builds only. Cloud Platform & Enterprise: Production-ready data distribution available.

Included Features:

• All data connectors
• All data accelerators
• Default memory allocator (snmalloc)

Excluded Features:

• AI/ML model inference
• LLM support
• Embedding models

Docker (Nightly):

docker pull ghcr.io/spiceai/spiceai-nightly:latest-data

Local Build:

make install-data-only

GPU-Accelerated Distributions

Metal (macOS)

For macOS systems with Apple Silicon, the Metal distribution enables GPU-accelerated AI/ML inference.

Included Features:

• All default features
• Metal GPU acceleration for model inference

Local Build:

make install-metal

CUDA (Linux)

For Linux systems with NVIDIA GPUs, CUDA distributions enable GPU-accelerated AI/ML inference. Multiple CUDA compute capability versions are available.

note

CUDA distributions are available with the Spice Cloud Platform and Spice.ai Enterprise. Open source users can build locally for development and testing.

Included Features:

• All default features
• CUDA GPU acceleration for model inference

Supported Compute Capabilities:

• 80 (A100, A30)
• 86 (RTX 30xx, A40, A10)
• 87 (Jetson Orin)
• 89 (RTX 40xx, L40, L4)
• 90 (H100, H200)

Local Build:

CUDA_COMPUTE_CAP=89 make install-cuda

NAS Distribution

The NAS (Network Attached Storage) distribution adds support for SMB and NFS data connectors, enabling federated queries against data stored on network file shares.

note

The NAS distribution is available with Spice.ai Enterprise. Open source users can build locally for development and testing.

Included Features:

• All default features
• SMB data connector
• NFS data connector

Local Build:

make install-nas

Allocator Variants

Different memory allocators can significantly impact performance depending on workload characteristics.

note

Allocator variants are available with the Spice Cloud Platform and Spice.ai Enterprise. Open source users can build locally for development and testing.

snmalloc (Default)

The default allocator, optimized for concurrent workloads.

jemalloc

Alternative allocator that may perform better for certain memory allocation patterns.

mimalloc

Microsoft's mimalloc allocator, designed for performance and security.

System Allocator

Uses the system's default allocator (glibc malloc on Linux).

Platform Support

Platform	Default	Data	NAS	Metal	CUDA
Linux x86_64	✅	Nightly	Enterprise only	❌	Cloud/Enterprise
Linux aarch64	✅	Nightly	Enterprise only	❌	❌
macOS aarch64 (Apple Silicon)	✅	Nightly	Enterprise only	✅	❌
Windows (WSL)	✅	Nightly	Enterprise only	❌	Cloud/Enterprise
Windows (Native)	❌	Enterprise only	Enterprise only	❌	Enterprise only

note

Native Windows support for the Spice runtime is available with the Spice Cloud Platform and Spice.ai Enterprise. Open source users on Windows should use Windows Subsystem for Linux (WSL).

Choosing a Distribution

Use Case	Recommended Distribution
General purpose with AI capabilities	Default
Data federation only, minimal footprint	Data (nightly)
Network attached storage (SMB/NFS)	NAS
macOS with GPU acceleration	Metal
Linux with NVIDIA GPU	CUDA
Memory allocation benchmarking	Allocator variants

Additional Connectors

Some connectors require additional dependencies and are available with the Spice Cloud Platform and Spice.ai Enterprise:

• ODBC - Connect to any ODBC-compatible data source

These can be built locally for development and testing:

make install-odbc

Platform-Specific Notes

Linux arm64

• FP16 (FEAT_FP16) is required because the gemm matrix multiplication library (used by the Candle ML framework) contains half-precision ARM inline assembly that requires the fullfp16 CPU feature. This is supported on AWS Graviton2+, Ampere Altra, Apple M-series (via Linux VM), and most ARMv8.2-A+ processors.
• lld is required as the linker because the spiced debug binary is large enough to exceed GNU ld's ±128 MiB branch range for R_AARCH64_CALL26 relocations. lld automatically inserts range extension thunks.
• Install prerequisites on Ubuntu/Debian: sudo apt-get install -y clang lld

Linux x86_64

• Release builds target AVX2+ for optimized SIMD performance, covering Intel Haswell (2013+) and AMD Excavator (2015+) processors, including all current AWS x86_64 instance families (C6/C7/C8).

Building Custom Distributions

Custom distributions with specific feature combinations can be built:

# Build with specific features
SPICED_CUSTOM_FEATURES="duckdb,postgres,sqlite,models" make build-runtime

# Build with non-default features added to defaults
SPICED_NON_DEFAULT_FEATURES="odbc" make install

See the project Makefile for all available build targets and options.