# Distributions

Spice.ai Enterprise provides multiple runtime distributions optimized for different workloads. All distributions are available in Enterprise; some are restricted or nightly-only in open source.

{% hint style="info" %}
The Spice runtime is **64-bit only**.
{% endhint %}

## Supported Platforms

| Platform | Architecture            | Minimum CPU Features                     |
| -------- | ----------------------- | ---------------------------------------- |
| Linux    | x86\_64                 | AVX2, FMA, BMI1/2, LZCNT, POPCNT         |
| Linux    | aarch64 (arm64)         | NEON, FP16 (FEAT\_FP16), FHM (FEAT\_FHM) |
| macOS    | aarch64 (Apple Silicon) | Native                                   |

## Distribution Availability

| Distribution        | Open Source      | Spice Cloud | Enterprise |
| ------------------- | ---------------- | ----------- | ---------- |
| Default (Data + AI) | ✅                | ✅           | ✅          |
| Data-only           | Nightly only     | ✅           | ✅          |
| NAS (SMB + NFS)     | Nightly only     | —           | ✅          |
| Metal (macOS)       | ✅                | ✅           | ✅          |
| CUDA (Linux)        | Nightly only     | ✅           | ✅          |
| Allocator variants  | Nightly only     | ✅           | ✅          |
| ODBC connector      | Local build only | ✅           | ✅          |

## Default Distribution

Includes all standard data connectors, embedded data accelerators (Spice Cayenne, DuckDB, SQLite), AI/ML model inference (LLMs, embeddings), search capabilities (vector and BM-25 full-text search), and the default memory allocator (snmalloc).

## Data-Only Distribution

Excludes AI/ML model support. Provides a smaller binary size and reduced attack surface for workloads that only need data federation and acceleration.

## NAS Distribution

Adds SMB and NFS data connector support. **Enterprise-only for production use.**

## GPU-Accelerated Distributions

### Metal (macOS)

GPU-accelerated AI/ML inference on Apple Silicon.

### CUDA (Linux)

CUDA GPU-accelerated model inference. Supported compute capabilities:

| Compute Capability | GPUs               |
| ------------------ | ------------------ |
| 80                 | A100, A30          |
| 86                 | RTX 30xx, A40, A10 |
| 87                 | Jetson Orin        |
| 89                 | RTX 40xx, L40, L4  |
| 90                 | H100, H200         |

Enterprise CUDA images are available from GitHub Container Registry:

```bash
docker pull ghcr.io/spicehq/spiceai-enterprise:latest-cuda
```

## Allocator Variants

Different memory allocators can significantly impact performance depending on workload characteristics. Enterprise provides production-ready allocator variant images.

### snmalloc (Default)

The default allocator, optimized for concurrent workloads. Reduces memory usage 10-20% compared to jemalloc/mimalloc.

### jemalloc

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

```bash
docker pull ghcr.io/spicehq/spiceai-enterprise:latest-jemalloc
```

### mimalloc

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

```bash
docker pull ghcr.io/spicehq/spiceai-enterprise:latest-mimalloc
```

### System Allocator

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

```bash
docker pull ghcr.io/spicehq/spiceai-enterprise:latest-sysalloc
```

## Choosing a Distribution

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


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