Laguna-XS-2.1-APEX-GGUF

Laguna-XS-2.1 GGUF

Imatrix quants of poolside/Laguna-XS-2.1 — a 33B MoE coder with 3B active parameters and a 262k context.

Eight tiers in two families: UDX spends its bits on the tensors every token touches, APEX trades some of that for a smaller file.

Which one to pick

Use the active bpw column, not file size.

This model routes 8 of its 256 experts per token, so the expert weights — about 97% of the file — only contribute 8/256 of their precision to any given token. Attention and the shared expert are used on every token. Active bpw measures what the model actually runs at; file bpw measures what it costs on disk.

That's why UDX-IQ4_XS (16.95 GB) runs at 6.88 active bpw while APEX-I-Compact-v2D-lite (15.84 GB) runs at 4.87 — nearly the same download, a meaningfully different model.

• Best quality that still fits 24 GB VRAM — UDX-Q4_K_XL
• Best quality per GB — UDX-IQ4_XS
• Smallest usable — APEX-I-Mini-v2D-lite
• Near-lossless — UDX-Q6_K

Run it

llama-server -m Laguna-XS-2.1-UDX-Q4_K_XL.gguf --jinja -ngl 99 -fa on

Needs llama.cpp release b10087 or newer (the base model card still says Laguna support is unmerged upstream — it landed in #25165 on 2026-07-22).

Context is 262,144. To go higher:

--ctx-size 1048576 --rope-scaling yarn --rope-scale 128 --yarn-orig-ctx 8192

Speculative decoding: poolside ship a separate DFlash drafter, but it currently needs poolside's llama.cpp fork for both the drafter and the server. These files work normally without it.

Notes

Imatrix by bartowski, computed on Laguna-XS-2.1 itself (437k tokens). Applied to every tier here.

APEX tiers replay mudler's per-layer maps, with attention lifted on the 10 global-attention layers — the ones carrying long-range context, since the other 30 use a 512-token sliding window.

UDX tiers are named that way on purpose. Unsloth never published a UD ladder for this model; these follow the same allocation policy but were not built by Unsloth and shouldn't be read as their release.

Every file was verified by checksum after upload — see sha256sums.txt.