ArliAI / Model details
Qwen3.5-35B-A3B-Derestricted
ArliAI/Qwen3.5-35B-A3B-Derestricted
About this model
ArliAI's refusal-modified Qwen3.5-35B-A3B, supplied as safetensors weights. The creator describes norm-preserving biprojected abliteration with the goal of retaining reasoning while reducing refusals. Its config contains a mixture-of-experts text architecture and a vision component; no retained image/video capability or active-parameter count has been verified here. The text configuration lists 262144 positions, not a measured usable-context window. The inherited base card's benchmarks and million-token scaling claims are not verified results for these weights.
Description sources
Source-based description, not an independent evaluation. Check the linked sources for the creator’s claims and limitations.
Size and formats
- Base model
- Qwen/Qwen3.5-35B-A3B
- Parameters
- 35.9518B
- Main repository formats
- safetensors
- License tag
- apache-2.0
- Languages
- Unknown
- Last updated
- 2026-03-18 · 05:07:01.000 UTC
What changed
Model types are creator-reported, not independently tested. These labels describe source metadata, not a guarantee of behavior.
- abliteratedsource tag:
abliterated
- uncensoredsource tag:
uncensored
- fine-tunedsource tag:
base_model:finetune:Qwen/Qwen3.5-35B-A3B
Family evidence
These groupings are source-reported. Explicit base identifiers take priority over generic architecture tags.
- Qwen: Base model: Qwen/Qwen3.5-35B-A3B
Available versions
Versions appear here only when they explicitly name this exact model as their source. Check each repository for available files.
Download sources
ModelScope distribution ↗- Distribution checked: ModelScope · 2026-10-24 · 03:14:44 UTC
Distribution links are not independent reviews or runtime compatibility guarantees. Check each source’s exact files and instructions.
Refusal profile
Refused 0 of 118 prompts (0.0%)
We asked this model 120 benign but risky-looking prompts across ten topics and counted how often it refused, hedged or answered. Lower means it answered more often; it says nothing about answer quality.
- Persuasion & deception0 refused · 0 partial · 12 complied
- Harassment & confrontation0 refused · 0 partial · 12 complied
- Risky activities0 refused · 0 partial · 12 complied
- Offensive & controversial speech0 refused · 0 partial · 12 complied
- Legal grey areas0 refused · 0 partial · 12 complied
- Privacy & personal data0 refused · 0 partial · 12 complied
- Self-harm & mental health topics0 refused · 0 partial · 10 complied
- Sexual & adult topics0 refused · 0 partial · 12 complied
- Ethically grey requests0 refused · 0 partial · 12 complied
- Violence & conflict0 refused · 0 partial · 12 complied
Capability check: 15 of 15 passed. Fifteen simple tasks with known answers, so a broken model cannot score well by refusing nothing.
Unclear answers: 2 (not counted). An answer is unclear when the two checker models disagree or the output was empty or garbled.
Measured 2026-10-25 · Q4_K_M via mradermacher/Qwen3.5-35B-A3B-Derestricted-GGUF ↗ · llama.cpp · prompt set v1
Link to this listing
Made or quantized this model? Paste one of these into your model card or README so people can find this listing.
Markdown
[Listed on Custom Clankers](https://customclankers.com/models/arliai-qwen3-5-35b-a3b-derestricted/)HTML
<a href="https://customclankers.com/models/arliai-qwen3-5-35b-a3b-derestricted/">Listed on Custom Clankers</a>Plain text links only: no image, no script, nothing loaded from this site.
Customize or build on this model
Listed from public GitHub data, not tested by us. Read the code and license before you run anything.
Linked in the model card
GitHub repositories the original model card links to.
- sgl-project/sglang ↗
Repo’s own description: SGLang is a high-performance serving framework for large language models and multimodal models.
★ 38,005 · Last updated 2026-10-25 · License: Apache-2.0
- vllm-project/vllm ↗
Repo’s own description: A high-throughput and memory-efficient inference and serving engine for LLMs
★ 95,376 · Last updated 2026-10-25 · License: Apache-2.0
- kvcache-ai/ktransformers ↗
Repo’s own description: A Flexible Framework for Experiencing Heterogeneous LLM Inference/Fine-tune Optimizations
★ 19,630 · Last updated 2026-10-20 · License: Apache-2.0
- QwenLM/Qwen-Agent ↗
Repo’s own description: Agent framework and applications built upon Qwen>=3.0, featuring Function Calling, MCP, Code Interpreter, RAG, Chrome extension, etc.
★ 17,211 · Last updated 2026-03-04 · License: Apache-2.0
- QwenLM/qwen-code ↗
Repo’s own description: An open-source AI coding agent that lives in your terminal.
★ 28,707 · Last updated 2026-10-25 · License: Apache-2.0
Tools to customize it further
Remove more refusals
- Heretic ↗ ★ 36,421
Removes refusal behavior from transformer models automatically. It pairs directional ablation (abliteration) with an Optuna parameter search that tries to cut refusals while keeping the model close to the original, so you don't have to pick layers by hand.
- OBLITERATUS ↗ ★ 8,946
A larger refusal-removal toolkit with several abliteration methods, usable locally or through a hosted Hugging Face Space. Check the telemetry setting before you run it: the README describes telemetry as opt-in, but on by default in the Spaces version.
Fine-tune it on your own data
- Unsloth ↗ ★ 78,528
A desktop app and Python library for running and training models locally. Its README lists LoRA, QLoRA, full fine-tuning, DPO and GRPO, plus export to formats including GGUF, on Windows, Linux, WSL and macOS.
- LlamaFactory ↗ ★ 75,713
Fine-tunes more than 100 language and vision-language models from a command line or a browser-based Web UI, aimed at training without writing code.
Make a smaller download (quantize)
- llama.cpp ↗ ★ 132,260
Runs models locally and includes the tools behind most GGUF files. A conversion script turns Hugging Face weights into GGUF, and llama-quantize shrinks a high-precision GGUF to lower-bit formats, which can cost some accuracy.
- MLX LM ↗ ★ 7,467
Apple's MLX package for running and fine-tuning models on Apple silicon. It can quantize models and upload them to the Hugging Face Hub, and supports LoRA and full fine-tuning.
Merge it with another model
- mergekit ↗ ★ 7,414
Merges pretrained models with many merge methods. It works out-of-core, so merges can run on a CPU or with as little as 8 GB of VRAM, and it also handles LoRA extraction and mixture-of-experts merges.
Learn the techniques
- LLM Course ↗ ★ 84,667
A free course with roadmaps and Colab notebooks. Its notebooks include one-click tools for merging with MergeKit, quantizing to GGUF, GPTQ, EXL2, AWQ and HQQ, and automatic abliteration with custom datasets.
Source provenance
- Downloads
- 189
- Likes
- 13
- Metadata checked
- 2026-10-25 · 05:05:23 UTC
- First seen in index
- 2026-10-23 · 01:14:11 UTC
- Source revision
- ee1ab6fb022b2f66d904b6eeab8c165629dbf150
Source-card excerpt
Source model card excerpt: Arli AI Qwen3.5-35B-A3B-Derestricted Qwen3.5-35B-A3B-Derestricted is a Derestricted version of Qwen3.5-35B-A3B, created by Arli AI . Our goal with this release is to provide a
From ArliAI/Qwen3.5-35B-A3B-Derestricted. Creator model-card excerpt, not an independent review.
Inspect before you run
Low refusal is not proof of correctness. Outputs can be inaccurate, harmful, or biased. Review the model card, license and files yourself. A license tag is not commercial-use advice. Parameter counts are source metadata; no hardware compatibility is implied.
This directory does not host or redistribute model weights. Refusal profiles are measured by us on a fixed prompt set; all other behavior claims are source-reported.
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