poolside / text-generation updated 4 days ago

Laguna-S-2.1-INT4

Name: Laguna-S-2.1-INT4
Author: poolside

Laguna S 2.1-INT4 is a 117.6B total parameter Mixture-of-Experts model with 8.5B activated parameters per token designed for agentic coding and long-horizon work on a local machine. It uses Sliding Window Attention with per-head gating in 36 out of 48 layers for fast inference and low KV cache requirements.

Params

117.6 B

Context

1,048,576

Downloads 30d

185 K

Likes

Licence: openmdw-1.1 Not gated SAFETENSORS View on Hugging Face ↗

Download history

tracking started — chart appears after 7 days of snapshots (1 recorded)

185 K downloads in the last 30 days

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

File	Quant	Size	Est. VRAM	Verdict on RTX 4090 · 24 GB
model.safetensors	i32	99.7 GB	127.8 GB	❌ Won’t fit
model.safetensors (bf16, full)	bf16 + 1024K ctx	99.7 GB	2,367.3 GB	❌ Won’t fit

Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Run it

copy-paste, exact tags checked against the Hub

~ · curl · api/v1

$ curl -s https://aimodelscomparison.com/api/v1/models/laguna-s-2-1-int4
{
  "hf_id": "poolside/Laguna-S-2.1-INT4",
  "params_b": 117.56,
  "context_length": 1048576,
  "license": { "id": "openmdw-1.1", "commercial": "unknown" },
  "downloads_30d": 185173,
  "vram_estimates": [
    { "quant": "i32", "gb": 127.8 }
  ],
  "updated_at": "2026-08-07T01:00:27Z"
}

est. VRAM —on RTX 4090 · 24 GBJSON API →

Specifications

Architecture: LagunaForCausalLM
Parameters: 117.6 B
Tensor type: I32
Context length: 1,048,576
Vocabulary: 100,352
Layers / heads: 48 / 48
Licence: openmdw-1.1
First seen on the Hub: 2026-07-02
Training datasets: undisclosed
Added to our catalog: 2026-08-07

Appears in

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