---
title: "Abliterated Models by API: No Weights to Download"
canonical: https://pentestllm.ai/abliterated-models
generated: 2026-11-12T07:12:01.554Z
source: https://pentestllm.ai/abliterated-models
base_url: https://api.pentestllm.ai/v1
---

![Rows of server cabinets in a data centre](https://pentestllm.ai/img/datacenter.webp)

## Hosted or downloaded: the trade

- Hardware: A download runs on your GPU and needs the memory for it, which rules out the larger models on a workstation. A hosted build needs none.
- Quantization: Local copies are often quantized to fit the card, which changes output quality. Hosting removes the need to shrink a model to your hardware.
- Upkeep: Locally you pick the checkpoint, the runtime and the settings, and redo it when a better edit appears. Here you change one model id.
- Cost shape: A GPU costs money while it sits idle. Per-token billing costs nothing between requests.
- Data location: Local keeps every prompt on your machine. An API sends it out, so check your client’s rules before sending engagement data.

Most abliterated models start life as a checkpoint someone published on Hugging Face, and running one yourself is a reasonable choice. If your scope forbids sending data to any outside service, run locally. If it does not, the hosted route gets you the larger builds and removes the setup.

## Reading an abliterated model’s name

- Abliterated: The refusal direction was projected out of the weights. The original term for the edit.
- Obliterated: The same edit under the ordinary English word.
- Heretic: Made with an open-source tool that automates refusal removal and scores each attempt on refusals left and drift from the original.
- Derestricted: A norm-preserving variant that removes the refusal component and restores the original weight magnitudes.

The names in the table carry a few different words for closely related edits, and the gateway tags all of them abliterated. [What is abliteration](https://pentestllm.ai/what-is-abliteration) explains the edit in plain terms.

## Abliterated models by family

The table lists every abliterated build together. If you want an edit of one particular base model, the family pages narrow it down: the [DeepSeek](https://pentestllm.ai/deepseek-abliterated), [Qwen](https://pentestllm.ai/qwen-abliterated), [GLM](https://pentestllm.ai/glm-abliterated) and [Llama](https://pentestllm.ai/llama-abliterated) abliterated builds each have their own page with live prices.

## When to pick one over a security build

- Code with a security subject: Reviewing or refactoring tooling, where the base model’s coding habits matter more than security vocabulary.
- Long documents: Summarizing a threat report or a policy set, where a general model’s reading is the skill in use.
- Report prose: Turning notes into clear findings and an executive summary without the model objecting to the subject.
- A second opinion: Sending the same question to a security build and an abliterated build and comparing the answers.

On this site the security-tuned builds are the default for testing questions, because they were trained on the field’s material. An abliterated build is the stock general model minus the reflex to decline, and that suits the jobs above.

## How to call a hosted abliterated model

Create a key, top up by card from $10 and set the base URL to `https://api.pentestllm.ai/v1`. Pick a build from the table below; its page gives the id that goes in the `model` field. The request is the ordinary OpenAI chat format, and the same builds answer Anthropic-format requests on the Messages endpoint. No system prompt is needed to make the build answer, since the change is in the weights.

Check two things on the build’s page before wiring it into an agent: whether it takes tool calls, which only some abliterated builds do, and its context window. The [uncensored LLM API](https://pentestllm.ai/uncensored-llm-api) page covers routes and billing.

## Limits that stay in place

Abliteration lowers how often a model declines. It leaves a few refusals behind, it can shift the model’s behaviour slightly, and it does nothing for accuracy, so verify what the model tells you. It also changes nothing about who may use the service: lawful security work on systems you own or have written permission to test, under the [acceptable use policy](https://pentestllm.ai/acceptable-use).

## 32 abliterated builds, priced per token

Read from the live catalog on 2026-11-12. Prices are US dollars per million tokens, paid from a prepaid balance that starts at $10. The id `auto/security` has no price of its own: each request is billed at the build that answered.

| Build | Input | Output | Context |
| --- | --- | --- | --- |
| [GLM-4.7 Flash Heretic](https://pentestllm.ai/models/glm-4.7-flash-heretic) | $0.336 | $1.92 | 131,072 |
| [GLM-5.3 Flash Abliterated](https://pentestllm.ai/models/glm-5.3-flash-abliterated) | $0.4656 | $1.94 | not published |
| [Qwen3.8 27B Obliterated](https://pentestllm.ai/models/qwen3.8-27b-obliterated) | $0.582 | $7.27 | 524,288 |
| [Apex Flash 1 Abliterated](https://pentestllm.ai/models/apex-flash-1-abliterated) | $0.68 | $2.32 | 262,144 |
| [DeepSeek V4.1 Flash 1017 Abliterated](https://pentestllm.ai/models/deepseek-v4.1-flash-1017-abliterated) | $0.75 | $3.125 | 1,000,000 |
| [GLM-5.3 Flash Apex Abliterated](https://pentestllm.ai/models/glm-5.3-flash-apex-abliterated) | $0.80 | $3.20 | 1,048,576 |
| [DeepSeek V4.1 Flash 1017 Heretic](https://pentestllm.ai/models/deepseek-v4.1-flash-1017-heretic-uncensored) | $0.825 | $3.30 | 512,000 |
| [DeepSeek V4.1 Flash 1017 Heretic Thinking](https://pentestllm.ai/models/deepseek-v4.1-flash-1017-heretic-uncensored-thinking) | $0.825 | $3.30 | 512,000 |
| [DeepSeek V4.1 Flash Abliterated](https://pentestllm.ai/models/deepseek-v4.1-flash-abliterated) | $0.8488 | $1.6975 | not published |
| [DeepSeek V4 Pro Abliterated](https://pentestllm.ai/models/deepseek-v4-pro-abliterated) | $1.00 | $4.00 | 1,000,000 |
| [Qwen3.8 27B Abliterated](https://pentestllm.ai/models/qwen3.8-27b-abliterated) | $1.0037 | $4.5326 | 262,000 |
| [Qwen3.5 27B Blossom V6.4 Derestricted](https://pentestllm.ai/models/qwen3.5-27b-blossom-v6.4-derestricted) | $1.071 | $1.071 | 262,144 |
| [Qwen3.5 27B BlueStar v3 Derestricted](https://pentestllm.ai/models/qwen3.5-27b-bluestar-v3-derestricted) | $1.071 | $1.071 | 262,144 |
| [Qwen3.5 27B Claude 4.6 Opus Reasoning Distilled Derestricted](https://pentestllm.ai/models/qwen3.5-27b-claude-4.6-opus-distilled-derestricted) | $1.071 | $1.071 | 262,144 |
| [Qwen3.5 27B Claude 4.6 Opus Reasoning Distilled Derestricted Lite](https://pentestllm.ai/models/qwen3.5-27b-claude-4.6-opus-distilled-derestricted-lite) | $1.071 | $1.071 | 262,144 |
| [Qwen3.5 27B Queen Derestricted](https://pentestllm.ai/models/qwen3.5-27b-queen-derestricted) | $1.071 | $1.071 | 262,144 |
| [DeepSeek V4 Pro Qwen3.5 9B Uncensored Heretic](https://pentestllm.ai/models/deepseek-v4-pro-qwen3.5-9b-uncensored-heretic) | $1.12 | $1.12 | 32,768 |
| [GLM-4.6 Derestricted v5](https://pentestllm.ai/models/glm-4.6-derestricted-v5) | $1.40 | $5.25 | 131,072 |
| [Gemma 31B Heretic Uncensored](https://pentestllm.ai/models/gemma-31b-heretic-uncensored) | $1.50 | $8.25 | not published |
| [DeepSeek V4.1 Flash Abliterated Fast](https://pentestllm.ai/models/deepseek-v4.1-flash-abliterated-fast) | $1.75 | $3.50 | 1,000,000 |
| [Qwen 2.5 32B Abliterated](https://pentestllm.ai/models/qwen2.5-32b-abliterated) | $1.75 | $1.75 | 32,768 |
| [NeuralDaredevil 8B Abliterated](https://pentestllm.ai/models/neuraldaredevil-8b-abliterated) | $1.76 | $1.76 | 8,192 |
| [MiMo V2.6 Flash Abliterated](https://pentestllm.ai/models/mimo-v2.6-flash-abliterated) | $2.00 | $6.00 | 1,048,576 |
| [GLM-5.3 Abliterated](https://pentestllm.ai/models/glm-5.3-abliterated) | $2.1825 | $4.365 | not published |
| [Abliterated Large Flash](https://pentestllm.ai/models/abliterated-model-large-flash) | $2.50 | $5.00 | 1,048,576 |
| [Abliterated Model](https://pentestllm.ai/models/abliterated-model) | $2.50 | $7.50 | 262,144 |
| [DeepSeek R1 Distill Llama 70B Abliterated](https://pentestllm.ai/models/deepseek-r1-distill-llama-70b-abliterated) | $2.80 | $2.80 | 16,384 |
| [Llama 3 70B Abliterated v3.5](https://pentestllm.ai/models/llama-3-70b-abliterated) | $2.80 | $2.80 | 8,192 |
| [Llama 3.3 70B Abliterated](https://pentestllm.ai/models/llama-3.3-70b-abliterated) | $2.80 | $2.80 | 32,768 |
| [DeepSeek R1 Distill Qwen 32B Abliterated](https://pentestllm.ai/models/deepseek-r1-distill-qwen-32b-abliterated) | $5.60 | $5.60 | 16,384 |
| [Abliterated Model Large](https://pentestllm.ai/models/abliterated-model-large) | $7.50 | $12.50 | 1,000,000 |
| [Abliterated Model Large V2](https://pentestllm.ai/models/abliterated-model-large-v2) | $7.50 | $12.50 | 1,048,576 |

[Full price list and tool fees](https://pentestllm.ai/pricing) · [Every model](https://pentestllm.ai/models) · [API docs](https://pentestllm.ai/docs)

## Questions

- An open-weight model whose refusal direction has been projected out of its weights. Nothing is retrained and no prompt is added, so it keeps the base model’s knowledge and declines far less often.
- No. The builds on this page run behind the API. You send a model id and pay per token, with no checkpoint to download and no GPU to provision.
- The table on this page is read from the live catalog on 2026-11-12 and lists every abliterated build on the key with its input price, output price and context window.
- Those that take tool calls do. Tool support varies by build, so check the model page, then follow the agent guide for your tool.
- Not exactly. Abliterated names a method, a weight edit with no retraining. Uncensored names a result and can also describe a fine-tune. Every abliterated build is uncensored in the loose sense.
- Each build has its own per-token price in the table. Billing is prepaid from $10 by card, with no subscription.

## Read next

- [What is abliteration How the refusal direction is removed from a model’s weights, and what that changes in practice.](https://pentestllm.ai/what-is-abliteration)
- [Abliterated vs uncensored The difference between abliterated, uncensored, derestricted and security-tuned builds.](https://pentestllm.ai/abliterated-vs-uncensored)
- [Uncensored LLM The uncensored and abliterated builds on one key, with live prices and context windows.](https://pentestllm.ai/uncensored-llm)
- [WhiteRabbitNeo alternative Hosted security builds by API, for people who do not want to run the weights.](https://pentestllm.ai/whiterabbitneo-alternative)

## One key, from $10

PentestLLM is for systems you own or have written permission to test. The [acceptable use policy](https://pentestllm.ai/acceptable-use) says what is not allowed.

[Get a key](https://app.pentestllm.ai/console)

usage, 1,000 agent turns on Qwen3.8 27B Cybersecurity

- Input, 8,000 tokens at $0.40 per million: $0.0032
- Output, 1,000 tokens at $2.40 per million: $0.0024
- One turn: $0.0056
- 1,000 turns: $5.60

output price per million tokens, 9 builds

$1.3376 Gemma 4 26B A4B Cybersecurity OrcaCyber Zero 1.5 $18.75