54 5 hours ago

RANA: an abliterated, uncensored Qwen3.8-27B with vision, thinking and tools, from Abliterant.

vision tools thinking
ollama run abliterant/qwen3.8-rana:q8_0

Details

5 hours ago

a4e3dbbc8771 · 30GB

qwen35
·
26.9B
·
Q8_0
clip
·
461M
·
F16
Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR US
{ "min_p": 0, "presence_penalty": 0, "repeat_penalty": 1, "temperature": 1, "top

Readme

Abliterant’s refusal-ablated Qwen/Qwen3.8-27B for Ollama, built from the GGUF release of abliterant/Qwen3.8-27B-RANA-abliterated. Vision, thinking and tool calling are included.

Try RANA in Abliterant Chat · abliterant.ai · Research notes · All formats

This is a safety-alignment-removed research model. Read Intended use and Limitations below before using it. Method, full evaluation and release gates are on the BF16 card.

Run

ollama run abliterant/qwen3.8-rana

Requires Ollama 0.40.5 or later.

Tag Size Notes
latest, q4_K_M 17.5 GB the usual choice when memory is tight; functional and refusal tests run on this quantization
q3_K_M 14.2 GB for fitting into about 16 GB, with a visible quality cost
q5_K_M 20.2 GB
q6_K 23.0 GB near-lossless
q8_0 29.5 GB near-lossless

Sizes include the vision tower (0.93 GB).

  • Thinking is on by default. The defaults are Qwen’s recommended thinking-mode settings: temperature 1.0, top_p 0.95, top_k 20.
  • Long technical requests can need 20–50k tokens of reasoning; raise the context length (num_ctx) accordingly.
  • The MTP speculative-decoding head is not part of the Ollama builds; it is in the GGUF repo for llama.cpp.

Limitations

  • Refusal behavior was evaluated on Q4_K_M only, with one seed and one judge. Other quantizations were checked for closeness to BF16 (KLD) but not for refusal behaviour; the lowest-bit quants drift the most from BF16 and may behave differently.
  • Everything listed under Limitations on the BF16 card applies here too: judge-measured refusal rates, long reasoning on technical requests, and the capability changes measured there.
  • Reduced refusal does not establish greater safety, accuracy, factual reliability, or universal compliance.

Intended use

  • Research only: interpretability, red-teaming, and robustness evaluation of refusal behaviour.
  • Not for public or end-user deployment without a separate moderation layer. The model’s own refusals have been largely removed, so any safety filtering has to happen outside it.
  • You are responsible for complying with applicable law, the Apache-2.0 license inherited from Qwen, and the terms of any platform where outputs are used.

License

Apache-2.0, inherited from Qwen/Qwen3.8-27B.