license: other
license_name: qwen-community-1.0
license_link: LICENSE
base_model: orcarouter/Qwen3.8-Flash-Next-Uncensored-GGUF
base_model_relation: quantized
pipeline_tag: image-text-to-text
library_name: gguf
tags:

• gguf
• splash
• apple-silicon
• qwen3.8
• flash-next
• abliterated
• uncensored

Qwen3.8-Flash-Next-Uncensored — Q5_K_S for Splash

A lossless repack of the Q5_K_S quant from orcarouter/Qwen3.8-Flash-Next-Uncensored-GGUF that Splash can load. The encoding of 96 small tensors changes and nothing else: every other tensor is byte-identical, and every stored value is preserved exactly.

Safety alignment removed. The upstream build is abliterated (refusal-removed). This repack inherits that behaviour unchanged.

Why this exists

Splash 1.4.0 refuses orcarouter's 4- and 5-bit quants (revision d366e279) from the header alone:

error: this GGUF stores tensors Splash cannot load: hc_attn_inject.weight Q5_K (48 tensors), hc_ffn_inject.weight Q5_K (48 tensors); choose another variant

Splash accepts only F32, BF16 or Q8_0 for the hyper-connection inject tensors (FLOAT_ROW_TYPES in its install/gguf.py), and its loader widens them to F32 regardless. orcarouter's Q8_0 builds pass the check, but at 175–178 GiB they do not fit a 128 GB Mac. This repack stores those 96 tensors as F32 and keeps the rest of Q5_K_S.

What changed

Verification

Tested

Tested on a MacBook Pro (M4 Max, 128 GB) running oMLX 0.7.2 with Splash 1.4.0 and the incoai/Qwen3.8-Flash-Next-DFlash2 draft.

• Loads at the full 262,144-token context.
• The PLE table streams from SSD (36,621 MiB stays on disk, 511 MiB row cache). All 81,602 MiB of routed experts stay in memory.
• With the mmproj present, Splash loads the vision tower; the projector passes Splash's vision_config() and processor_config() checks. Image inference has not been tested.
• Smoke test: correct output at 98.4 tok/s (31 generated tokens).

Not tested with llama.cpp or other runtimes.

Files

Source files, orcarouter revision d366e279688c1f2fd6e75e2f98475d38db534f1d:

Reproduce it

From orcarouter's Q5_K_S shards, with llama.cpp's llama-quantize:

llama-quantize --allow-requantize --keep-split \
  --tensor-type "hc_attn_inject=f32" --tensor-type "hc_ffn_inject=f32" \
  Qwen3.8-Flash-Next-Uncensored-Q5_K_S-00001-of-00003.gguf \
  out/Qwen3.8-Flash-Next-Uncensored-Q5_K_S-Splash.gguf \
  Q5_K_S

• The target type must be Q5_K_S. With COPY, --tensor-type is silently ignored and the inject tensors stay Q5_K.
• Same-type tensors pass through without requantization; the log shows a conversion only on the 96 inject tensors.
• --keep-split appends -0000N-of-00003 to the output name, so give the output name without a shard suffix.
• It took 1 min 40 s on an M4 Max.

The same override with the matching target type should make orcarouter's other 4- and 5-bit variants loadable too. Only Q5_K_S was converted and tested here.

Credits and license

Quantization, abliteration and the imatrix (whose metadata is preserved) are by orcarouter. The base model is Qwen/Qwen3.8-Flash-Next.

The base model is released under the Qwen Community License 1.0, which governs this derivative. Abliteration and requantization do not change it. The license is included verbatim in LICENSE.