← back to catalog · registered 2026-08-22 13:56

jcbtc/CHADROCK3.6-35B-UNCENSORED-MTP-STRIX-LEAN

jcbtc Qwen 35B GGUF MoE second-order 262K ctx
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model.

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/jcbtc%2FCHADROCK3.6-35B-UNCENSORED-MTP-STRIX-LEAN"
Response includes
  • classification m-uncensored
  • files 3
  • hub_downloads_all_time 3,101
  • author_summary 2 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
Abliteration classifier · v1.0.0
M-U
Primary method

Uncensored (method unknown)

No other method signals detected in this model.
Confidence
LOW
Why this label 3 signals
Weak or ambiguous signals. Best guess based on catalog patterns; treat as tentative and check the evidence below.
  • 'uncensored' in name/tags but no 'abliterated' marker
  • method not identifiable from author declaration alone
  • may be DPO fine-tune, prompt engineering, or unknown technique
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
3K
668 last 30d - stable
Likes
11
Model age
4mo ago
created 2026-06-04
Downloads over time
Now3.2K→from1.2K↑153%
1.2K1.9K2.6K3.4K1.2K on Jun 103.2K on Oct 11JunJulAugSepOct
Jun 10 → Oct 11 · 57 snapshots · spans 123 days

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Metadata

License
apache-2.0
Languages
en zh
Tags
llama.cpp gguf qwen3.6 qwen35moe 35b 35b-a3b 3b-active model-size-35b-a3b mixture-of-experts moe mtp rocmfp4

Related

Total size
17.7 GB
Files
3
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-06-23 01:58

Files by quantization

Auxiliary files 3 files 17.7 GB
CHADROCK3.6-35B-UNCENSORED-MTP-STRIX-LEAN.gguf 17.7 GB 32f40ebf download
README.md 8.44 KB 3e0de8f5 download
.gitattributes 85.0 B 8bf4e0ad download

README current version from Hugging Face


license: apache-2.0
base_model: HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
base_model_relation: quantized
language:

  • en
  • zh
    library_name: llama.cpp
    pipeline_tag: text-generation
    tags:
  • qwen3.6
  • qwen35moe
  • 35b
  • 35b-a3b
  • 3b-active
  • model-size-35b-a3b
  • mixture-of-experts
  • moe
  • gguf
  • mtp
  • llama.cpp
  • rocmfp4
  • chadrock
  • uncensored
  • strix-lean
  • amd
  • ryzen-ai-max-395
  • strix-halo

CHADROCK3.6 35B Uncensored Strix Lean MTP

CHADROCK3.6 35B Uncensored Strix Lean MTP

CHADROCK3.6 35B Uncensored Strix Lean MTP is a ROCmFP4/MTP GGUF for AMD Ryzen AI Max+ 395 / Strix Halo systems.

The behavior comes from HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive, based on Qwen/Qwen3.6-35B-A3B. This release turns that model into a Strix Lean ROCmFP4 GGUF with Qwen3.6 MTP speculative decoding enabled for high-throughput local serving.

This GGUF will not run correctly with stock llama.cpp. You need the pinned ciru-ai/ROCmFPX runner because this file uses ROCmFP4 tensor types and MTP runtime paths that upstream llama.cpp does not currently understand.

The model file is provided here. You do not need to rebuild or quantize the model.

This is an uncensored local-assistant build. It is intended for users who explicitly want that behavior on their own hardware.

Why This Build

This build is for Strix Halo owners who want the uncensored HauhauCS Qwen3.6 35B-A3B behavior, but with the local serving speed and coding strength that CHADROCK/ROCmFP4 and MTP can unlock on AMD unified-memory hardware.

The mix is:

  • HauhauCS uncensored/aggressive Qwen3.6 35B-A3B behavior
  • Qwen3.6 35B-A3B MoE efficiency, with roughly 3B active parameters per token
  • Qwen3.6 MTP speculative decoding
  • ROCmFP4 STRIX_LEAN GGUF conversion
  • Strix Halo tuned f16/f16 KV, b2048/u512, Vulkan0, one-slot serving
  • 262k context public profile with MTP enabled
  • a 157/164 HumanEval base result with fast HumanEval generation

Technical Metadata

Hugging Face may round the parsed GGUF tensor count to 36B in its automatic badge. This release is the Qwen3.6 35B-A3B MoE family: about 35B-class total parameters with roughly 3B active parameters per token.

Field Value
model family Qwen3.6 35B-A3B
architecture qwen35moe
active parameters ~3B class
direct source HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
base family Qwen/Qwen3.6-35B-A3B
runtime format ROCmFP4 STRIX_LEAN GGUF
target hardware AMD Ryzen AI Max+ 395 / Strix Halo
backend device Vulkan0
context 262144
max tokens 65536
serving slots 1
batch / ubatch 2048 / 512
target KV f16 / f16
draft KV f16 / f16
MTP draft depth --spec-draft-n-max 4
vision text-only profile, --no-mmproj

Model Tree

Qwen/Qwen3.6-35B-A3B
  -> HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
    -> CHADROCK3.6 35B Uncensored Strix Lean ROCmFP4
      -> CHADROCK3.6 35B Uncensored Strix Lean ROCmFP4 MTP

Headline Benchmarks

All local numbers below were measured on AMD Ryzen AI Max+ 395 / Strix Halo with the public MTP profile.

HumanEval

Model / row HumanEval base HumanEval+
CHADROCK3.6 35B Uncensored Strix Lean MTP 157/164 = 95.73% 150/164 = 91.46%

This is a strong HumanEval result for a local uncensored ROCmFP4/MTP GGUF run.

HumanEval Speed

Metric CHADROCK3.6 35B Uncensored MTP
HumanEval tasks 164
total tokens processed 75,223
completion tokens generated 46,360
codegen wall time 488.0s
cumulative request latency 484.95s
mean request latency 2.96s
total-token throughput, prompt + completion 154.15 tok/s
completion-token generation throughput 95.60 tok/s
median per-request completion-token speed 95.21 tok/s

The total-token number counts prompt plus completion tokens over the full codegen wall time. The completion-token number counts generated completion tokens over request latency. The same EvalPlus HumanEval run produced the score table above and generated the full 164-task workload in about eight minutes of codegen wall time.

Best Settings / Advanced Setup

For the pinned runner build, copy-paste build commands, request-level speculative controls, and the 35B/27B reproduction notes, use the advanced Ciru setup page:

https://llm.ciru.ai/chadrock-rocmfpx/

The current pinned runner build is:

ciru-ai/ROCmFPX commit: 7aa484a2f0a504dc612a3d74a068024f3e6d6353
historical score tag: chadrock-rocmfp4-mtp-scores-20260621

For this 35B Uncensored Strix Lean release, use:

backend: Vulkan0 target + Vulkan0 draft
context: 262144
batch / ubatch: 2048 / 512
target KV: f16 / f16
draft KV: f16 / f16
MTP: draft-mtp, n_max=4, n_min=0, p_min=0.0
serving: one slot, metrics on, text-only, --no-mmproj
sampler: temperature=0.2, min_p=0.0, top_p=0.9, top_k=20
reasoning: off, reasoning_budget=0

This is the text-only Strix Lean profile used for the published local speed and
EvalPlus rows. Vision is intentionally disabled for this release path.

Run With llama-server

Build Charlie's custom llama.cpp once, download this GGUF, then run:

/path/to/rocmfp4-llama/build-strix-rocmfp4/bin/llama-server \
  -m CHADROCK3.6-35B-UNCENSORED-MTP-STRIX-LEAN.gguf \
  --alias CHADROCK3.6-35B-UNCENSORED-MTP-STRIX-LEAN \
  --host 127.0.0.1 \
  --port 8080 \
  --jinja \
  -c 262144 \
  --reasoning off \
  --reasoning-format none \
  --reasoning-budget 0 \
  --no-context-shift \
  -sm row \
  -ngl 999 \
  -fa on \
  -b 2048 \
  -ub 512 \
  -dev Vulkan0 \
  -t 16 \
  -tb 32 \
  -ctk f16 \
  -ctv f16 \
  --temp 0.2 \
  --min-p 0.0 \
  --top-p 0.9 \
  --top-k 20 \
  --repeat-penalty 1.0 \
  --seed 123 \
  --parallel 1 \
  --no-mmproj \
  --metrics \
  --cache-ram 8192 \
  --ctx-checkpoints 0 \

  --checkpoint-every-n-tokens -1 \

  --spec-type draft-mtp \
  --spec-draft-device Vulkan0 \
  --spec-draft-ngl all \
  --spec-draft-threads 16 \
  --spec-draft-threads-batch 32 \
  --spec-draft-type-k f16 \
  --spec-draft-type-v f16 \
  --spec-draft-n-max 4 \
  --spec-draft-n-min 0 \
  --spec-draft-p-min 0.0 \
  --poll 100 \
  --poll-batch 1 \
  --spec-draft-poll 1 \
  --spec-draft-poll-batch 1

Use --parallel 1 for this MTP profile. One slot is part of the intended MTP serving setup.

Text Only

This release is served as text-only. The public Strix Lean profile uses --no-mmproj.

The upstream HauhauCS repo includes multimodal metadata and a matching projector exists locally, but the June 4, 2026 Ciru real-image gate failed for this model with MTP on and with MTP off. The clean non-MTP Hauhau ROCmFP4 path and the original Hauhau Q8 path also failed that gate. Because of that, this release does not advertise or recommend vision use.

Build The Required llama.cpp

The GGUF is already provided. You only need to build the custom llama.cpp server once:

git clone https://github.com/ciru-ai/ROCmFPX.git
cd ROCmFPX
git checkout 7aa484a2f0a504dc612a3d74a068024f3e6d6353
env JOBS=16 scripts/build-strix-rocmfp4-mtp.sh llama-server llama-bench

The server binary will be here:

build-strix-rocmfp4/bin/llama-server

Charlie12345, also known as @Italianclownz, added the ROCmFP4 llama.cpp path this GGUF needs. The method adds custom ROCmFP4 GGUF tensor types and AMD-focused backend support so Strix Halo systems can run these very compact high-throughput builds.

File

File Size SHA256
CHADROCK3.6-35B-UNCENSORED-MTP-STRIX-LEAN.gguf 18G 32f40ebf853ee081b1e33b0104b384654266037fbf61d6ed07bece2a0560b238

Credits

  • HauhauCS: uncensored/aggressive Qwen3.6 35B-A3B source model.
  • Qwen: base Qwen3.6-35B-A3B model family.
  • charlie12345 / @Italianclownz: ROCmFP4 llama.cpp fork and AMD-focused MTP runtime path.

Notes

This is an experimental AMD ROCmFP4/MTP build. Performance depends on driver version, clocks, prompt shape, MTP acceptance, and serving flags. The numbers above are local reproducible measurements on Strix Halo, not universal llama.cpp claims.

README history 4 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-06-23Pin Chadrock v2 runner checkpoint fix83d719e8.4 KB
    Loading...
  2. 2026-06-22Pin ROCmFPX runner commit in README71064e08.4 KB
    Loading...
  3. 2026-06-21Add best Chadrock runtime settingsecf4c6b8.3 KB
    Loading...
  4. 2026-06-04Add CHADROCK3.6 35B uncensored model card05b16e27.4 KB
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration