You can deploy this model and start earning money today!

AtomicChat/
Laguna-XS-2.1-MLX-6bit

Name: Laguna-XS-2.1-MLX-6bit
Availability: InStock

poolside/Laguna-XS-2.1

quantized

openmdw-1.1

6-bit

Views

No views yet

Base model: poolside/Laguna-XS-2.1

Laguna XS 2.1, self-quantized to MLX by Atomic Chat. Built straight from Poolside's original weights with a per-tensor importance matrix, so this is not a repack of somebody else's files. Runs fully offline.

Highlights

33.4B parameters: the weights this repo quantizes.
Context length: 262,144 tokens (256K), as published by Poolside.
40 layers: Mixture-of-Experts, hybrid sliding-window (512) and global attention.
Full imatrix ladder: every quant is calibrated with an importance matrix.
Mixed SWA and global attention layout: Laguna XS 2.1 uses sigmoid gating with per-layer rotary scales, enabling mixed SWA (Sliding Window Attention) and global attention layers in a 3:1 ratio (across 40 total layers).
KV cache in FP8: KV cache quantized to FP8, reducing memory per token.
Native reasoning support: Interleaved thinking between tool calls with support for enabling and disabling thinking per-request.

[!NOTE] These MLXs are self-quantized from the original weights, not a repack. The importance matrix keeps low-bit quants closer to the full-precision model.

Model Overview

Property	Value
Base model	`poolside/Laguna-XS-2.1`
Parameters	33.4B
Layers	40
Experts	256 routed (top-8)
Sliding window	512 tokens
Context length	262,144 tokens (256K)
Vocabulary	100,352
Modalities	Text
Architecture	Mixture-of-Experts, 256 experts (top-8), hybrid sliding-window (512) and global attention, 48 attention heads over 8 KV heads, `LagunaForCausalLM`
This repo	MLX weights

Scores are Poolside's published results for the base poolside/Laguna-XS-2.1, not our own measurements. Quantization preserves the large majority of this; Q4_K_M and up stay close to full precision.

Get started

Atomic Chat: search AtomicChat/Laguna-XS-2.1-MLX-6bit and hit Use this model.
mlx-lm: mlx_lm.generate --model AtomicChat/Laguna-XS-2.1-MLX-6bit --prompt "Hello" --max-tokens 512
Server: mlx_lm.server --model AtomicChat/Laguna-XS-2.1-MLX-6bit --port 8080

Best practices

Parameter	Value
temperature	1.0
top_p	1
top_k	20
min_p	0.0

Poolside's recommended sampling configuration for poolside/Laguna-XS-2.1.

How these were made

Download poolside/Laguna-XS-2.1 (original weights).
Convert and quantize with mlx_lm.convert on our pipeline.

License

Original model by Poolside, released under the OpenMDW-1.1 license. Full terms: OpenMDW-1.1. Quantized by Atomic Chat.

AtomicChat/Laguna-XS-2.1-MLX-6bit