Community quantization · Apple Silicon

Laguna-S-2.1-Uncensored-oQ4e

Name: Laguna-S-2.1-Uncensored-oQ4e
Availability: InStock

An independent mixed-precision MLX edition for local software development and agentic coding on Apple Silicon.

118B / ~8B activeMixture of Experts

oQ4eMixed precision

63.017 GiB13 MLX shards

128 GB testedM4 Max · macOS

01 / 15

About This Release

Laguna-S-2.1-Uncensored-oQ4e is an independent MLX oQ level 4 enhanced quantization of SC117/Laguna-S-2.1-Uncensored. The original ancestor is poolside/Laguna-S-2.1.

The release targets local software-development and agentic-coding workloads on Apple Silicon while retaining the direct source's uncensored behavior and native thinking configuration.

Source behavior: inherited from the SC117 derivative; no new behavior edit was performed by AmixDigital.
Published artifact: 13 MLX Safetensors shards produced through the oMLX graphical interface.
Optional acceleration: DFlash is paired at runtime and is not merged into these weights.

Notice

Important Notices

This is a community quantization, not an official release by Poolside or SC117.
No independent benchmark suite or long-context evaluation has been completed for this release.
Only the documented 128 GB test environment has been validated; minimum memory is unmeasured.
No DFlash draft weights are included.

Upstream results are not quantization results. Refusal and divergence measurements reported by SC117 were not rerun here and must not be attributed to these MLX artifacts.

Audience warning

Uncensored Behavior and Safety

The direct source reduces refusal behavior through an upstream Abliterix-based modification. It may generate harmful, explicit, biased, illegal, misleading, or otherwise unsafe content. This release is not suitable for all audiences.

02 / 15

Model Details

Architecture	Laguna Mixture-of-Experts, text-to-text
Parameters	118B total; approximately 8B active per token upstream
Layers	48
Experts	256 routed + 1 shared, top-10 routing
Context	Configured up to 1,048,576 tokens; not long-context tested here
Quantization	oQ level 4 enhanced, MLX affine mixed precision
Weights	63.017 GiB · 13 shards
State	Quantized target weights; optional draft distributed separately

Repository Files

The table groups related files while covering every functional artifact in this repository.

File	Purpose	Required by	Notes
`model-00001-of-00013.safetensors` … `model-00013-of-00013.safetensors`	Quantized target weights	MLX runtime	13 shards · 63.017 GiB
`model.safetensors.index.json`	Tensor-to-shard index	MLX loader · Hugging Face	Includes verified conceptual parameter metadata
`config.json`	Architecture and quantization configuration	MLX · oMLX	Laguna custom code · affine mixed precision
`configuration_laguna.py` · `modeling_laguna.py`	Custom Laguna implementation	Custom-code loaders	Carry Apache-2.0 notices
`tokenizer.json` · `tokenizer_config.json` · `special_tokens_map.json`	Tokenizer data and settings	Prompt encoding and decoding	Inherited from the direct source
`chat_template.jinja`	Chat, thinking, and tool-message formatting	Conversational inference	Native thinking remains enabled by default
`generation_config.json`	Generation defaults and companion reference	oMLX runtime	DFlash remains external and optional
`oq_imatrix_report.json`	Machine-readable calibration evidence	Quantization audit	Personal cache path redacted; limitations retained
`LICENSE` · `LICENSE-APACHE-2.0`	Redistribution terms	Recipients and redistributors	OpenMDW-1.1 materials · Apache-2.0-noticed code
`README.md` · `.gitattributes`	Model card and Hub storage rules	Hugging Face Hub	English Lumen card · LFS tracking

03 / 15

Provenance and Lineage

Published artifact: this repository's MLX oQ4e quantized target weights, prepared by AmixDigital.
Direct source: SC117/Laguna-S-2.1-Uncensored at revision 0e9c665.
Original ancestor: poolside/Laguna-S-2.1 at revision 00af5a5.

The optional DFlash draft is a runtime companion—not an ancestor, source checkpoint, or component of the published weights.

04 / 15

Transformation Details

Upstream modification. SC117 describes the direct source as an Abliterix Trial 16 behavior edit of Poolside's BF16 model, including a LoRA merge, MoE router adjustments, and restoration of the default thinking template. This work was not performed by AmixDigital.

MLX quantization. The published artifacts were created through the graphical interface of oMLX 0.5.4. No CLI quantization command was used.

Quantization	MLX affine mixed precision; 4-bit group-size-64 default with 5-, 6-, and 8-bit overrides
Effective storage	Approximately 4.605 bits per conceptual parameter, calculated from 67,664,427,590 weight bytes and 117,561,977,600 parameters
Stored dtypes	BF16 tensor values and U32 packed quantization data in Safetensors
Precision overrides	386 configured tensor overrides: 105 at 5-bit, 1 at 6-bit, and 280 at 8-bit; 245 use group size 64 and 141 use group size 128
Highest-precision tensors	`lm_head` and `model.embed_tokens` are configured at 8-bit, group size 64
Calibration preset	`oqe_code_multilingual`
Collection	1,024 processed samples · sequence length 512
Expert coverage	36,084 / 36,096 routes activated · 12 zero-count experts
Report status	`coverage_sufficient: false` · `collection_sufficient: false`

Calibration limitation: the imatrix did not activate every expert route. The maintainer reports that oMLX used a quantized proxy because the BF16 source did not fit in available unified memory.

05 / 15

Requirements and Compatibility

macOS	26.5.2 · tested
Apple Silicon	MacBook Pro, M4 Max, 16-core CPU · tested
Unified memory	128 GB · tested and recommended
Observed memory	Approximately 70 GB or less · maintainer observation, not instrumented
oMLX	0.5.4 · tested
`mlx-lm`	0.31.3 · installed in test environment
`mlx-vlm`	0.6.3 · installed in test environment
MLX core	Exact version not recorded

Minimum unified memory has not been measured. Disk size alone is not a safe minimum-memory estimate.

06 / 15

Usage

Verified oMLX workflow

Add the obtained model directory to oMLX 0.5.4.
Load the model on a compatible Apple Silicon Mac.
Keep thinking enabled when the task benefits from reasoning.
Run a short software-development prompt before increasing context or enabling optional acceleration.

The maintainer's smoke test requested a landing-page implementation. The model loaded successfully, produced a coherent result, and exposed thinking behavior.

Prompting, Thinking and Tool Use

The chat template defaults enable_thinking to true. Thinking was observed, but tool calling was not tested on this quantization.

07 / 15

Acceleration and Companion Models

This target can be paired with the separately distributed poolside/Laguna-S-2.1-DFlash draft. DFlash proposes token blocks that the target verifies; it does not replace or modify the target weights.

Open the DFlash companion repository →

Obtain the official draft repository separately.
Enable DFlash in the target's oMLX settings.
Select the draft directory and reload the target.

Runtime pairing was completed in oMLX 0.5.4. Throughput, acceptance rate, equivalence, and long-context behavior were not measured; no acceleration factor is claimed.

08 / 15

Evaluation and Performance

No independent benchmark suite has been completed for this release.

Check	Result	Limit
Model load	Successful	One Mac configuration
Generation	Coherent landing page	Single qualitative prompt
Thinking	Observed	No structured evaluation
Tool calling	Not tested	Inherited configuration only
Long context	Not tested	Configured maximum unvalidated
DFlash	Runtime pairing completed	Speed and acceptance unmeasured

Benchmarks from Poolside or SC117 describe their own artifacts and must not be interpreted as measurements of this quantization.

09 / 15

Intended Uses

Local software development and code-oriented assistance on compatible Apple Silicon Macs.
Agentic-coding experiments with human review and constrained tool permissions.
General text generation where unvalidated general-purpose quality is understood.

10 / 15

Out-of-Scope Uses

Unsupervised high-stakes medical, legal, financial, employment, safety, or infrastructure decisions.
Autonomous destructive tool execution without sandboxing, review, and recovery controls.
Uses that violate law, rights, license terms, or platform policies.
Claims of Windows, Linux, CUDA, GGUF, vLLM, or server-GPU compatibility.

11 / 15

Risks, Biases and Limitations

Uncensored output may be harmful, explicit, biased, fabricated, or unsafe.
Quantization may add variance or degradation beyond upstream limitations.
Twelve of 36,096 expert routes were not activated during calibration.
Quality, tool use, long context, minimum memory, and general stability remain unmeasured.
Custom model code requires security review before remote-code execution.

12 / 15

Recommendations and Mitigations

Evaluate the exact model and prompts before deployment.
Keep human review for code changes, tool use, and consequential outputs.
Sandbox generated code and restrict credentials and filesystem access.
Apply access controls and content filtering where necessary.
Start with short contexts and monitor memory pressure on untested hardware.

13 / 15

License and Responsible Use

The published Model Materials are distributed under the OpenMDW-1.1 License. The complete inherited agreement is included as LICENSE. Redistribution must retain the agreement and applicable copyright and origin notices.

The redistributed Python implementation files also carry Apache-2.0 notices. A complete copy is included as LICENSE-APACHE-2.0.

Users remain responsible for third-party rights, applicable law, and determining whether the model and its outputs are appropriate for a particular use. AmixDigital and the maintainers are not responsible for illegal, abusive, or otherwise unauthorized uses of the model or its outputs.

14 / 15

Acknowledgements

Poolside for the original Laguna S 2.1 and official DFlash companion.
SC117 for the direct uncensored source and behavior-edit provenance.
Abliterix contributors for the upstream behavior-edit method.
oMLX contributors for MLX serving and oQ quantization tooling.

15 / 15

Model Card Contact

Contact AmixDigital on Hugging Face or open a discussion in this model repository to report an error or propose a correction.

AmixDigital/Laguna-S-2.1-Uncensored-oQ4e