Laguna-S-2.1 Memory Requirements in MTPLX: Complete Hardware Guide

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, an additional 2.4 GiB for KV-cache at default 32k context, and a mandatory 16 GiB system reserve.

The youssofal/MTPLX repository enforces these requirements through a strict pre-flight validation system that executes before loading the autoregressive checkpoint. This prevents runtime out-of-memory failures by calculating exact resident memory needs for model weights, rotating KV-cache, and per-token allocation overhead.

Understanding the Laguna-S-2.1 Memory Footprint

MTPLX calculates memory requirements deterministically using constants defined in mtplx/models/laguna_config.py. The total splits into static and dynamic components based on the requested context length.

Model Weights and Fixed Overhead

The base memory consumption begins with the quantized weights and fixed runtime buffers. According to laguna_config.py, the Laguna-S-2.1 4-bit checkpoint allocates:

• LAGUNA_S_2_1_WEIGHT_BYTES: 64,122,027,323 bytes (≈ 64.12 GiB) for the frozen parameters
• Fixed headroom: 8 GiB reserved for activation spikes and temporary tensors
• LAGUNA_S_2_1_ROTATING_KV_BYTES: 75,497,472 bytes (≈ 0.07 GiB) for the rotating KV-cache buffer

These static allocations sum to approximately 72.19 GiB before accounting for variable context length.

Context-Dependent KV Cache Allocation

The autoregressive model allocates additional memory proportional to the sequence length. The calculation uses:

• LAGUNA_S_2_1_FULL_KV_BYTES_PER_TOKEN: 49,152 bytes (48 KiB) per token
• LAGUNA_S_2_1_DEFAULT_CONTEXT: 32,768 tokens

At the default 32k context, the KV-cache requires approximately 1.61 GiB. The configuration exposes this through the laguna_s_2_1_required_resident_bytes() function, which computes:

def laguna_s_2_1_required_resident_bytes(context_tokens: int) -> int:
    return (
        LAGUNA_S_2_1_WEIGHT_BYTES
        + 8 * 1024**3                                 # 8 GiB extra headroom

        + LAGUNA_S_2_1_ROTATING_KV_BYTES
        + max(1, int(context_tokens)) * LAGUNA_S_2_1_FULL_KV_BYTES_PER_TOKEN
    )

For the default configuration, this yields LAGUNA_S_2_1_MIN_RESIDENT_BYTES ≈ 74.4 GiB.

The MTPLX Pre-Flight Memory Check

Before initializing the model, MTPLX executes _preflight_laguna_system_memory within mtplx/runtime.py. This function aggregates the resident memory requirement with a non-negotiable system reserve:

# mtplx/runtime.py

system_reserve = 16 * 1024**3      # 16 GiB

required = LAGUNA_S_2_1_MIN_RESIDENT_BYTES + system_reserve

If the host's unified memory falls below the 90.6 GiB threshold, the runtime raises a RuntimeError (surfaced through mtplx/server/openai.py) with the message:

“Laguna‑S‑2.1 requires at least 90.6 GiB unified memory for weights, runtime headroom, and the system reserve.”

Code Examples for Memory Management

Loading with Exception Handling

When initializing the runtime, wrap the loader to catch insufficient memory conditions before they crash the process:

from mtplx import MTPLXRuntime, load_model
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 does not need MTP

    )
except RuntimeError as e:
    print("Cannot start Laguna‑S‑2.1 AR:", e)

The RuntimeError originates directly from _preflight_laguna_system_memory when your hardware cannot satisfy the calculated requirement.

Querying Requirements Programmatically

Inspect the constants directly to determine hardware compatibility before attempting allocation:

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")

This outputs the 74.4 GiB resident floor and 90.6 GiB total requirement without initializing the model.

Validating System Memory Before Launch

Use psutil to compare available RAM against MTPLX requirements programmatically:

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")

Executing this validation prevents unnecessary runtime exceptions by ensuring your environment meets the 90.6 GiB threshold defined in the MTPLX source.

Summary

• Laguna-S-2.1 requires 74.4 GiB of minimum resident memory for weights, 8 GiB headroom, and default context KV-cache.
• MTPLX adds a 16 GiB system reserve, raising the total requirement to 90.6 GiB of unified RAM.
• The pre-flight check lives in mtplx/runtime.py → _preflight_laguna_system_memory and enforces this threshold before model loading.
• Memory scales linearly with context length at 48 KiB per token beyond the base allocation.
• Insufficient memory triggers a descriptive RuntimeError referencing the 90.6 GiB requirement.

Frequently Asked Questions

How much RAM is strictly necessary to run Laguna-S-2.1 in MTPLX?

You need approximately 90.6 GiB of unified system memory to pass the initialization check. This breaks down into 64.12 GiB for 4-bit weights, 8 GiB runtime headroom, roughly 2.4 GiB for KV-cache at 32k context (including rotating buffers), and a mandatory 16 GiB system reserve hardcoded in mtplx/runtime.py.

Can I run Laguna-S-2.1 with less than 90.6 GiB by reducing context length?

While the KV-cache component scales down at 48 KiB per token, the validation in _preflight_laguna_system_memory currently enforces the full 90.6 GiB requirement regardless of your requested context window. The 74.4 GiB base plus 16 GiB reserve represents the static floor for all Laguna-S-2.1 instances.

What error message appears if my system lacks sufficient memory?

MTPLX raises a RuntimeError with the exact text: “Laguna‑S‑2.1 requires at least 90.6 GiB unified memory for weights, runtime headroom, and the system reserve.” This originates from mtplx/runtime.py and propagates through mtplx/server/openai.py to the user interface.

Where are the memory constants defined in the MTPLX source?

All size calculations reference mtplx/models/laguna_config.py, which defines LAGUNA_S_2_1_WEIGHT_BYTES, LAGUNA_S_2_1_FULL_KV_BYTES_PER_TOKEN, and the laguna_s_2_1_required_resident_bytes() helper. The enforcement logic resides in mtplx/runtime.py within the _preflight_laguna_system_memory function.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}