---

license: mit

base_model:

- zai-org/GLM-5.3-Flash

library_name: llama.cpp

tags:

- gguf

- layer-library

- multi-stage

- ik_llama.cpp

- dreamcatcher

- xautonomics

---

GLM-5.3-Flash-UD-IQ4_XS.LAYR.GGUF

A per-layer GGUF library of Unsloth's unsloth/GLM-5.3-Flash-GGUF (UD-IQ4_XS). These are the same quantized weights, sliced once into one file per transformer block plus the shared parts, so any contiguous layer window A, B) can be assembled at load time. It's built for [dreamcatcher, xAutonomics' fork of ik_llama.cpp, which serves a library either in a single process or split across hosts.

| | |

|---|---|

| base model | zai-org/GLM-5.3-Flash |

| source quant | unsloth/GLM-5.3-Flash-GGUF · UD-IQ4_XS · pinned revision 621d456e93 · 5 shards |

| architecture | glm5next · 46 blocks |

| files | 48 (embd, layer, nextn, output) · 146.5 GiB |

| integrity | manifest.json: blake2b-128 per whole file and per tensor |

| sliced with | layer_distribution.slice (the slicer commit is in the SLICER_COMMIT file); nothing was re-quantized |

Support status

Measured on the dreamcatcher tree (status as of c2f8b680; the linked document is authoritative):

glm5next — CUDA verified (library head/tail ring coherent, greedy,

7.6 tok/s, experts on CPU; library ≡ monolith 1383/1383 hashes). The

mono-vs-library runtime A/B is done — hidden states md5-identical mono vs

library (the STAGE_EMIT=hidden logits abort that blocked it is fixed,

meta#93). Vulkan: not measured for this architecture on the published tree

(the RDNA3.5 APU proof was the expert-server path with GLM-5.3-Flash experts,

not a local Vulkan run).

Only model files from huggingface.co/xautonomics are supported by dreamcatcher. Other GGUFs, including libraries you slice yourself, may load but are unsupported. Do not rename the files: the loader expects blk-NNNNN.gguf / parts-*.gguf / manifest.json exactly.

Layout

blk-00000.gguf … blk-00044.gguf   one transformer block each
parts-embd.gguf                          token embedding (every stage loads it)
parts-output.gguf                        output norm + head (every stage loads it)
parts-nextn-NNNNN.gguf                   NextN/MTP block(s)
manifest.json                            file list, sizes, per-file + per-tensor hashes, source provenance

A stage that serves layers [A, B) needs blk-A … blk-(B-1) plus the parts-* files and manifest.json.

Use

Single process (the whole model on one host):

llama-server --model-dir /models/GLM-5.3-Flash-UD-IQ4_XS.LAYR.GGUF

Multi-host ring (stages exchange hidden states over TCP; each host needs low-latency, direct node-to-node links — see the dreamcatcher README):

llama-stage-runner --role tail --listen 8081 --model-dir /models/GLM-5.3-Flash-UD-IQ4_XS.LAYR.GGUF --layers 24,46
llama-stage-runner --role head --connect <tail-host>:8081 --model-dir /models/GLM-5.3-Flash-UD-IQ4_XS.LAYR.GGUF --layers 0,24

Plan a split for your hosts (weights-only screen; the proof is a survived prefill), and verify the download before launching:

python3 -m layer_distribution.plan /models/GLM-5.3-Flash-UD-IQ4_XS.LAYR.GGUF/manifest.json --node a:16GiB:200GiB:8080 --node b:24GiB:200GiB:8081
python3 -c "from layer_distribution import verify; r = verify('/models/GLM-5.3-Flash-UD-IQ4_XS.LAYR.GGUF', '/models/GLM-5.3-Flash-UD-IQ4_XS.LAYR.GGUF/manifest.json'); print(r.passed, r.hash_verified)"

Provenance and license

Weights are byte-for-byte the tensors of unsloth/GLM-5.3-Flash-GGUF at revision 621d456e93e926e4b52f85cff5f634358c1828f9 (Unsloth's dynamic quantization of zai-org/GLM-5.3-Flash). Source shard names and sizes are recorded in manifest.json (source.shards[], source.content_hash). License follows the base model: mit, see LICENSE. Credit to the base-model authors and to Unsloth for the quantization.

About

Published by xAutonomics for dreamcatcher.