> ## Documentation Index
> Fetch the complete documentation index at: https://docs.abliteration.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# What is abliteration?

> Abliteration is a technique that reduces refusal behavior in an open-weight LLM. Its effects on other capabilities vary by model.

Abliteration reduces refusal behavior in an open-weight LLM by suppressing a refusal-related direction. Abliterated models may answer prompts the source model would refuse, but other capabilities can change too.

The name combines **ablation** and **obliteration**.
Directional ablation can target behaviors beyond refusals; this page focuses on refusal reduction.

## How it works

Modern instruction-tuned LLMs encode refusal as a recognizable direction in their internal activation space. When a prompt activates that direction strongly, the model produces a refusal ("I can't help with that") instead of a substantive answer.

Abliteration:

1. Identifies the refusal direction by computing the difference in mean activations between **harmful** and **harmless** prompts on the original model.
2. **Suppresses that direction** during inference or edits model weights that contribute to it.
3. Evaluates refusal behavior and other capabilities after the edit. Results vary by model and method.

Weight-editing methods can modify many values across transformer layers. Reduced refusals do not guarantee unchanged instruction-following, tool use, code generation, or multilingual performance.

## How abliteration differs from related techniques

| Technique | What it changes | Persists across prompts? |
| - | - | - |
| **System prompt jailbreak** | Adds instructions in the system prompt | No — depends on the prompt being present |
| **Fine-tuning on uncensored data** | Updates many weights via gradient descent | Yes, but capability often degrades |
| **RLHF removal** | Re-runs preference training | Yes — expensive, requires labeled data |
| **Abliteration** | Suppresses a refusal-related direction in activations or weights | Yes for weight edits; runtime edits must stay enabled |

Abliteration uses a refusal-related direction identified from model activations. Its effect on other behavior must be measured.

## Origin

Arditi et al. described and demonstrated directional ablation of refusals across multiple model families, including Llama 2, Qwen 1, and Gemma 1. FailSpy published an implementation called abliterator.

## How abliteration.ai uses this

abliteration.ai hosts abliterated models behind an OpenAI- and Anthropic-compatible HTTP API. Send a request with the OpenAI or Anthropic SDK using `https://api.abliteration.ai` as the base URL. Refusal behavior varies by model and prompt.

The hosted models are exposed as `abliterated-model` (general-purpose, with vision), `abliterated-model-large-v2` (text-only, frontier-scale, GLM-5.3), and `abliterated-model-large` (text-only, the previous GLM-5.2 large model). See [models](/models).

## What this means for your application

* **Fewer refusals** on prompts that fall in the refusal subspace of the original model.
* **No system-prompt jailbreaks needed** — refusal reduction is applied to the model rather than added to each prompt.
* **Evaluate other capabilities** — abliteration can affect instruction-following, tool use, code generation, and multilingual performance. We run refusal checks and task benchmarks on our hosted models; test your own workload as well.
* **Policies are configurable.** Create [policies](/policy-gateway/overview) to monitor or block specific request or response behavior. Published policies can apply automatically to projects or only when selected for a run.

## Further reading

* [Models](/models) — the hosted abliterated model and its capabilities
* [OpenAI compatibility](/api/openai-compatibility) — drop-in for the OpenAI SDK
* [Anthropic compatibility](/api/anthropic-compatibility) — drop-in for the Anthropic SDK
* [Policies](/policy-gateway/overview) — configure request and response checks
* [Arditi et al., *Refusal in Language Models Is Mediated by a Single Direction*](https://arxiv.org/abs/2406.11717) — original directional ablation research
* [FailSpy's abliterator](https://github.com/FailSpy/abliterator) — implementation
* [Maxime Labonne, *Uncensor any LLM with abliteration*](https://huggingface.co/blog/mlabonne/abliteration) — separate writeup


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