# Memory Requirements for Running Laguna-S-2.1 AR in MTPLX: Complete Technical Specifications

> Discover the precise memory requirements for running Laguna-S-2.1 AR in MTPLX. Learn about unified system memory needs, model weights, and runtime headroom for optimal performance.

- Repository: [Youssof Altoukhi/MTPLX](https://github.com/youssofal/MTPLX)
- Tags: technical-specifications
- Published: 2026-09-04

---

**Running Laguna-S-2.1 AR in MTPLX requires approximately 90.6 GiB of unified system memory**, comprising 64.12 GiB for 4-bit model weights, 8 GiB runtime headroom, 1.68 GiB for the KV-cache at default 32k context, rotating buffers, and a mandatory 16 GiB system reserve.

MTPLX performs rigorous pre-flight memory validation before loading the Laguna-S-2.1 autoregressive (AR) model to prevent out-of-memory crashes during inference. According to the youssofal/MTPLX source code, the runtime calculates exact byte-level requirements for weights, KV-cache, and safety buffers, throwing a `RuntimeError` if unified system memory falls below the 90.6 GiB threshold.

## How MTPLX Calculates Memory for Laguna-S-2.1 AR

### Model Weights and Static Allocations

The foundation of the memory calculation resides in [`mtplx/models/laguna_config.py`](https://github.com/youssofal/MTPLX/blob/main/mtplx/models/laguna_config.py). The 4-bit quantized Laguna-S-2.1 checkpoint requires **64.12 GiB** for resident weights, defined by the constant `LAGUNA_S_2_1_WEIGHT_BYTES` (64,122,027,323 bytes).

Additionally, MTPLX allocates **8 GiB** of fixed headroom to accommodate runtime overhead and intermediate activations. The rotating KV buffer adds approximately **72 MiB** (`LAGUNA_S_2_1_ROTATING_KV_BYTES`).

### KV-Cache Requirements

For autoregressive generation, the KV-cache scales linearly with context length. At **48 KiB per token** (`LAGUNA_S_2_1_FULL_KV_BYTES_PER_TOKEN`), the default 32,768-token context consumes approximately **1.61 GiB**. The configuration calculates this dynamically via `laguna_s_2_1_required_resident_bytes()`:

```python
from mtplx.models.laguna_config import LAGUNA_S_2_1_MIN_RESIDENT_BYTES

min_resident_gb = LAGUNA_S_2_1_MIN_RESIDENT_BYTES / (1024**3)
print(f"Minimum resident memory: {min_resident_gb:.1f} GiB")

```

### System Reserve and Total Footprint

Beyond model-specific allocations, [`mtplx/runtime.py`](https://github.com/youssofal/MTPLX/blob/main/mtplx/runtime.py) mandates an additional **16 GiB** `system_reserve` for OS and process overhead. This brings the **full memory requirement** to approximately **90.6 GiB** of unified RAM.

## Pre-Flight Memory Check Implementation

When invoking `MTPLXRuntime.from_filesystem()` with a Laguna-S-2.1 path, the system triggers `_preflight_laguna_system_memory()` in [`mtplx/runtime.py`](https://github.com/youssofal/MTPLX/blob/main/mtplx/runtime.py). This function compares available system memory against `LAGUNA_S_2_1_MIN_RESIDENT_BYTES` plus the 16 GiB reserve.

If unified memory is insufficient, the runtime raises:

```text
RuntimeError: Laguna-S-2.1 requires at least 90.6 GiB unified memory for weights, runtime headroom, and the system reserve.

```

This check specifically targets the Laguna-S-2.1 4-bit checkpoint and executes before model weights load, preventing partial initialization failures.

## Practical Code Examples

### Loading the Model with Error Handling

To safely initialize Laguna-S-2.1 AR with graceful degradation:

```python
from mtplx import MTPLXRuntime
import pathlib

model_dir = pathlib.Path("/path/to/laguna-s-2.1")
try:
    runtime = MTPLXRuntime.from_filesystem(
        model_path=model_dir,
        mtp_enabled=False,  # AR mode disables MTP

    )
except RuntimeError as e:
    print(f"Cannot start Laguna-S-2.1 AR: {e}")

```

### Programmatically Inspecting Memory Requirements

Calculate requirements without loading the model:

```python
from mtplx.models.laguna_config import LAGUNA_S_2_1_MIN_RESIDENT_BYTES

min_resident_gb = LAGUNA_S_2_1_MIN_RESIDENT_BYTES / (1024**3)
total_required_gb = (LAGUNA_S_2_1_MIN_RESIDENT_BYTES + 16 * 1024**3) / (1024**3)

print(f"Minimum resident memory: {min_resident_gb:.1f} GiB")
print(f"Full requirement (incl. 16 GiB reserve): {total_required_gb:.1f} GiB")

```

### Verifying System Memory Before Launch

Use `psutil` to preemptively check compatibility:

```python
import psutil
from mtplx.models.laguna_config import LAGUNA_S_2_1_MIN_RESIDENT_BYTES

total_mem_gb = psutil.virtual_memory().total / (1024**3)
required_gb = (LAGUNA_S_2_1_MIN_RESIDENT_BYTES + 16 * 1024**3) / (1024**3)

print(f"System memory detected: {total_mem_gb:.1f} GiB")
print(f"Memory needed for Laguna-S-2.1 AR: {required_gb:.1f} GiB")
if total_mem_gb < required_gb:
    print("WARNING: Insufficient memory for Laguna-S-2.1 AR")

```

## Key Source Files

- **[`mtplx/runtime.py`](https://github.com/youssofal/MTPLX/blob/main/mtplx/runtime.py)** — Contains `_preflight_laguna_system_memory()` which enforces the 90.6 GiB unified memory requirement before model initialization.

- **[`mtplx/models/laguna_config.py`](https://github.com/youssofal/MTPLX/blob/main/mtplx/models/laguna_config.py)** — Defines weight sizes, KV-cache byte calculations, and `LAGUNA_S_2_1_MIN_RESIDENT_BYTES` constant (≈74.4 GiB).

- **[`mtplx/server/openai.py`](https://github.com/youssofal/MTPLX/blob/main/mtplx/server/openai.py)** — Emits user-facing error messages when memory pre-flight checks fail.

## Summary

- **Laguna-S-2.1 AR requires 90.6 GiB unified memory**: 64.12 GiB weights, 8 GiB headroom, ~1.68 GiB KV-cache (at 32k context), and 16 GiB system reserve.
- **Pre-flight validation occurs in [`mtplx/runtime.py`](https://github.com/youssofal/MTPLX/blob/main/mtplx/runtime.py)** via `_preflight_laguna_system_memory()` before any weights load.
- **Minimum resident memory is 74.4 GiB** without the 16 GiB system reserve, defined as `LAGUNA_S_2_1_MIN_RESIDENT_BYTES`.
- **RuntimeError triggers immediately** if system memory is insufficient, preventing partial model loads and OOM crashes.
- **KV-cache scales linearly** at 48 KiB per token, making context length the primary variable in memory calculations.

## Frequently Asked Questions

### Why does Laguna-S-2.1 AR require 90.6 GiB of memory?

The 90.6 GiB requirement combines non-negotiable allocations: 64.12 GiB for 4-bit quantized weights, 8 GiB runtime headroom for intermediate activations, approximately 1.68 GiB for the KV-cache at 32,768-token context, a 72 MiB rotating buffer, and a 16 GiB system reserve for OS overhead. These values are hardcoded in [`mtplx/models/laguna_config.py`](https://github.com/youssofal/MTPLX/blob/main/mtplx/models/laguna_config.py) and enforced by [`mtplx/runtime.py`](https://github.com/youssofal/MTPLX/blob/main/mtplx/runtime.py).

### What happens if my system has less than 90.6 GiB RAM?

MTPLX raises a `RuntimeError` with the message: *"Laguna-S-2.1 requires at least 90.6 GiB unified memory for weights, runtime headroom, and the system reserve."* This occurs during the pre-flight check in `_preflight_laguna_system_memory()` before any model weights are loaded into memory, preventing system instability.

### Can I reduce the memory requirements by changing the context length?

Yes, the KV-cache scales linearly at **48 KiB per token** (`LAGUNA_S_2_1_FULL_KV_BYTES_PER_TOKEN`). Reducing context below the default 32,768 tokens decreases the total resident memory requirement calculated by `laguna_s_2_1_required_resident_bytes()`. However, you cannot reduce the fixed 64.12 GiB weight allocation or the 8 GiB headroom requirement.

### Where is the memory check implemented in the MTPLX codebase?

The primary validation logic resides in **[`mtplx/runtime.py`](https://github.com/youssofal/MTPLX/blob/main/mtplx/runtime.py)** within the `_preflight_laguna_system_memory()` function. This function references constants from **[`mtplx/models/laguna_config.py`](https://github.com/youssofal/MTPLX/blob/main/mtplx/models/laguna_config.py)** and is invoked when `MTPLXRuntime.from_filesystem()` detects a Laguna-S-2.1 checkpoint path.