Models/Abliterated LLM API/Text to Text API

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Abliterated LLM API — 20 Abliterated, Obliterated & Derestricted Models

The Abliterated LLM API gives you programmatic access to 20 models through one Muapi API key and one request shape: prompt, optional system_prompt, max_tokens, and image_url on vision-capable models.Abliterated models are language models modified to reduce their built-in refusal behavior. Abliteration and related techniques (obliteration, derestriction) lower how often a model declines a request; they do not guarantee unrestricted output, remove every limit, or change Muapi's acceptable-use policy. You remain responsible for how you use the output.

Get API Key Try Qwen 3.8 27B Abliterated in Playground Model comparisons and API examples Coding-agent benchmark and setup General-purpose agent integrations

Watch: Best Abliterated LLMs 2026 — 6 Picks, No GPU

MiMo

MiMo models1 models

Text GenerationLive

MiMo

MiMo V2.6 Flash Abliterated

MiMo V2.6 Flash with its refusal behavior reduced through abliteration: fast reasoning, a 1M-token context window, and optional image input.

Text + Image in

$1.00/M in · $3.00/M out

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Abliterated Model

Abliterated Model models3 models

Text GenerationLive

Abliterated Model

A general-purpose abliterated reasoning model with a 262K-token context window and optional image input.

Text + Image in

$2.00/M in · $6.00/M out

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Text GenerationLive

Abliterated Model

Abliterated Model Large

The larger abliterated reasoning model with a 1M-token context window, text in and text out.

Text in

$6.00/M in · $10.00/M out

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Text GenerationLive

Abliterated Model

Abliterated Model Large V2

The second revision of the large abliterated reasoning model, with a 1M-token context window and text-only input.

Text in

$6.00/M in · $10.00/M out

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Qwen

Qwen models6 models

Text GenerationLiveFeatured

Qwen

Qwen 3.8 27B Abliterated

Qwen 3.8 27B with refusal behavior reduced through abliteration: image input, a 524K-token context window, and an optional thinking mode.

Text + Image in

$0.30/M in · $2.40/M out

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Text GenerationLive

Qwen

Qwen 3.8 27B Obliterated

Qwen 3.8 27B with refusals removed via an obliteration-style ablation, image input, a 524K-token context window, and an optional thinking mode.

Text + Image in

$0.50/M in · $3.00/M out

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Text GenerationLive

Qwen

Qwen 2.5 32B Instruct Abliterated

Qwen 2.5 32B Instruct with refusal behavior reduced by abliteration: a compact general chat and coding model with a 32K-token context window.

Text in

$1.40/M in · $1.40/M out

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Text GenerationLive

Qwen

Qwen3.5 27B Queen Derestricted

Qwen3.5 27B Queen with its refusal behavior reduced through derestriction: image input, a 262K-token context window, and a flat token rate.

Text + Image in

$0.612/M in · $0.612/M out

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Text GenerationLive

Qwen

Qwen3.5 27B Blossom Derestricted

Qwen3.5 27B Blossom (V6.4) with its refusal behavior reduced through derestriction: image input, a 262K-token context window, and a flat token rate.

Text + Image in

$0.612/M in · $0.612/M out

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Text GenerationLive

Qwen

Qwen3.5 27B Opus-Distilled Derestricted

Qwen3.5 27B distilled from Claude Opus 4.6 reasoning traces, with its refusal behavior reduced through derestriction: image input and a 262K-token context window.

Text + Image in

$0.612/M in · $0.612/M out

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Llama

Llama models2 models

Text GenerationLive

Llama

Llama 3.3 70B Instruct Abliterated

Llama 3.3 70B Instruct with refusal behavior reduced by abliteration: a large open-weights chat baseline with a 32K-token context window.

Text in

$1.40/M in · $1.40/M out

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Text GenerationLive

Llama

NeuralDaredevil 8B Abliterated

NeuralDaredevil 8B, an abliterated Llama 3 8B derivative: the lightest and cheapest option here, with an 8K-token context window.

Text in

$0.88/M in · $0.88/M out

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DeepSeek R1

DeepSeek R1 models2 models

Text GenerationLive

DeepSeek R1

DeepSeek R1 Distill Llama 70B Abliterated

DeepSeek R1 distilled onto Llama 70B with refusal behavior reduced by abliteration: chain-of-thought reasoning with a 16K-token context window.

Text in

$1.40/M in · $1.40/M out

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DeepSeek R1

DeepSeek R1 Distill Qwen 32B Abliterated

DeepSeek R1 distilled onto Qwen 32B with refusal behavior reduced by abliteration: compact chain-of-thought reasoning with a 16K-token context window.

Text in

$2.80/M in · $2.80/M out

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GLM

GLM models3 models

Text GenerationLive

GLM

GLM 5.3 Flash Abliterated

GLM 5.3 Flash with refusal behavior reduced through abliteration: fast reasoning, a 1M-token context window, and optional image input.

Text + Image in

$0.40/M in · $1.60/M out

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Text GenerationLive

GLM

GLM 5.3 Abliterated

The full-size GLM 5.3 with refusal behavior reduced through abliteration: a 1M-token context window, text in and text out.

Text in

$2.50/M in · $4.50/M out

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GLM

GLM 4.6 Derestricted v5

GLM 4.6 (v5) with its refusal behavior reduced through derestriction: a 131K-token context window, text in and text out.

Text in

$0.80/M in · $3.00/M out

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Gemma

Gemma models3 models

Text GenerationLive

Gemma

Gemma 4 26B A4B Abliterated

Gemma 4 26B A4B with refusal behavior reduced through abliteration: an efficient mixture-of-experts chat model with a 65K-token context window, text in and text out.

Text in

$0.30/M in · $1.40/M out

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Gemma

Gemma 4 31B Gembrain Abliterated

Gemma 4 31B Gembrain with refusal behavior reduced: image input, a 262K-token context window, and a flat token rate for general and creative chat.

Text + Image in

$0.612/M in · $0.612/M out

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Text GenerationLive

Gemma

Gemma 4 31B SDFT Abliterated

Gemma 4 31B SDFT Abliterated, an abliterated Gemma 4 with reduced refusals, tuned for character chat and creative writing, with image input and a 262K-token context window.

Text + Image in

$0.612/M in · $0.612/M out

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What is the Abliterated LLM API?

The Abliterated LLM API is Muapi's catalog of 20 abliterated and derestricted LLMs, from lightweight 8B chat models to 1M-token-context reasoning models, behind one consistent REST interface so you can compare them by changing a single model name.

Submit a prompt, optionally with a system_prompt to set persona and tone and an image_url on vision-capable models, and poll for the generated text. Typical uses include creative writing, red-team and safety research, evaluation against the unmodified base model, and applications where a base model's refusals get in the way of legitimate work. Abliterated models are language models modified to reduce their built-in refusal behavior. Abliteration and related techniques (obliteration, derestriction) lower how often a model declines a request; they do not guarantee unrestricted output, remove every limit, or change Muapi's acceptable-use policy. You remain responsible for how you use the output.

Key Capabilities

20 Models, One API

Every endpoint accepts the same request body and returns text through the shared result endpoint, so switching models is a one-line change.

Reduced Refusals

Abliteration and related techniques lower how often the model declines a request. Behavior varies by model and prompt, and is not a guarantee.

System Prompt Control

Set a system_prompt to steer persona, tone, and output format for creative, analytical, or evaluation work.

Pay Per Token

Billing follows the token counts each call returns. There is no subscription and no model hosting to manage.

Image Input on Vision Models

Pass an image_url to MiMo V2.6 Flash Abliterated, Abliterated Model, Qwen 3.8 27B Abliterated, Qwen 3.8 27B Obliterated, Qwen3.5 27B Queen Derestricted, Qwen3.5 27B Blossom Derestricted, Qwen3.5 27B Opus-Distilled Derestricted, GLM 5.3 Flash Abliterated, Gemma 4 31B Gembrain Abliterated, Gemma 4 31B SDFT Abliterated.

Acceptable-Use Policy Applies

Reduced refusals do not mean no rules. Muapi's acceptable-use policy and applicable law still apply to what you generate.

Pricing

Endpoint	Input	Output	Price	Best For
mimo-v2-6-flash-abliterated	Prompt + system_prompt, max_tokens, optional image_url	Complete text response (poll for result)	$1.00/M in · $3.00/M out	Fast, low-cost reasoning with image input and very long context
abliterated-model	Prompt + system_prompt, max_tokens, optional image_url	Complete text response (poll for result)	$2.00/M in · $6.00/M out	General reasoning and multimodal chat with reduced refusals
abliterated-model-large	Prompt + system_prompt, max_tokens	Complete text response (poll for result)	$6.00/M in · $10.00/M out	Large-context reasoning over long documents and codebases
abliterated-model-large-v2	Prompt + system_prompt, max_tokens	Complete text response (poll for result)	$6.00/M in · $10.00/M out	The newest large abliterated reasoning tier
qwen-3-8-27b-abliterated	Prompt + system_prompt, max_tokens, optional image_url, optional thinking	Complete text response (poll for result)	$0.30/M in · $2.40/M out	The lowest-cost Qwen 3.8 tier, with image input and a switchable thinking mode
qwen-3-8-27b-obliterated	Prompt + system_prompt, max_tokens, optional image_url, optional thinking	Complete text response (poll for result)	$0.50/M in · $3.00/M out	Mid-size reasoning with image input and a switchable thinking mode
qwen-2-5-32b-abliterated	Prompt + system_prompt, max_tokens	Complete text response (poll for result)	$1.40/M in · $1.40/M out	Compact general chat and coding at a flat token rate
qwen-3-5-27b-queen-derestricted	Prompt + system_prompt, max_tokens, optional image_url	Complete text response (poll for result)	$0.612/M in · $0.612/M out	Creative and general chat with image input at a flat rate
qwen-3-5-27b-blossom-derestricted	Prompt + system_prompt, max_tokens, optional image_url	Complete text response (poll for result)	$0.612/M in · $0.612/M out	Creative writing and chat with image input at a flat rate
qwen-3-5-27b-opus-distilled-derestricted	Prompt + system_prompt, max_tokens, optional image_url	Complete text response (poll for result)	$0.612/M in · $0.612/M out	Step-by-step reasoning with image input at a flat rate
llama-3-3-70b-abliterated	Prompt + system_prompt, max_tokens	Complete text response (poll for result)	$1.40/M in · $1.40/M out	Large open-weights chat at a flat token rate
neuraldaredevil-8b-abliterated	Prompt + system_prompt, max_tokens	Complete text response (poll for result)	$0.88/M in · $0.88/M out	Lightweight, low-cost chat and prototyping
deepseek-r1-llama-70b-abliterated	Prompt + system_prompt, max_tokens	Complete text response (poll for result)	$1.40/M in · $1.40/M out	Step-by-step reasoning on the Llama 70B base
deepseek-r1-qwen-32b-abliterated	Prompt + system_prompt, max_tokens	Complete text response (poll for result)	$2.80/M in · $2.80/M out	Compact step-by-step reasoning on the Qwen 32B base
glm-5-3-flash-abliterated	Prompt + system_prompt, max_tokens, optional image_url	Complete text response (poll for result)	$0.40/M in · $1.60/M out	Fast, low-cost reasoning with image input and very long context
glm-5-3-abliterated	Prompt + system_prompt, max_tokens	Complete text response (poll for result)	$2.50/M in · $4.50/M out	Full-size reasoning over very long context
glm-4-6-derestricted-v5	Prompt + system_prompt, max_tokens	Complete text response (poll for result)	$0.80/M in · $3.00/M out	Mid-size GLM reasoning with a 131K-token context
gemma-4-26b-a4b-abliterated	Prompt + system_prompt, max_tokens	Complete text response (poll for result)	$0.30/M in · $1.40/M out	Efficient, low-cost chat and reasoning on the Gemma family
gemma-4-31b-gembrain-abliterated	Prompt + system_prompt, max_tokens, optional image_url	Complete text response (poll for result)	$0.612/M in · $0.612/M out	General and creative chat with image input at a flat token rate
gemma-4-31b-sdft-abliterated	Prompt + system_prompt, max_tokens, optional image_url	Complete text response (poll for result)	$0.612/M in · $0.612/M out	Character chat and creative writing on a Gemma 4 base, with image input

Billed per token from the usage each call returns; prices are per million input and output tokens.

How to Call the Abliterated LLM API

Submit a JSON request with your Muapi API key, save the request ID, and poll the shared result endpoint.

1. Submit a prompt to MiMo V2.6 Flash Abliterated

curl -X POST https://api.muapi.ai/api/v1/mimo-v2-6-flash-abliterated \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Write a morally gray villain monologue for my novel.", "system_prompt": "You are a candid, detail-oriented assistant.", "image_url": "https://example.com/reference.png", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call mimo-v2-6-flash-abliterated with a prompt and optional system_prompt, image_url.

2. Submit a prompt to Abliterated Model

curl -X POST https://api.muapi.ai/api/v1/abliterated-model \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Describe the plot of a dark psychological thriller in detail.", "system_prompt": "You are a candid, detail-oriented assistant.", "image_url": "https://example.com/reference.png", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call abliterated-model with a prompt and optional system_prompt, image_url.

3. Submit a prompt to Abliterated Model Large

curl -X POST https://api.muapi.ai/api/v1/abliterated-model-large \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Summarize this long transcript and list every claim that needs a fact-check.", "system_prompt": "You are a candid, detail-oriented assistant.", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call abliterated-model-large with a prompt and optional system_prompt.

4. Submit a prompt to Abliterated Model Large V2

curl -X POST https://api.muapi.ai/api/v1/abliterated-model-large-v2 \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Draft a blunt red-team style review of this product launch plan.", "system_prompt": "You are a candid, detail-oriented assistant.", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call abliterated-model-large-v2 with a prompt and optional system_prompt.

5. Submit a prompt to Qwen 3.8 27B Abliterated

curl -X POST https://api.muapi.ai/api/v1/qwen-3-8-27b-abliterated \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Write a tense, unflinching short story about a heist gone wrong.", "system_prompt": "You are a candid, detail-oriented assistant.", "image_url": "https://example.com/reference.png", "thinking": true, "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call qwen-3-8-27b-abliterated with a prompt and optional system_prompt, image_url and thinking flag.

6. Submit a prompt to Qwen 3.8 27B Obliterated

curl -X POST https://api.muapi.ai/api/v1/qwen-3-8-27b-obliterated \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Character chat as a cynical noir detective and narrate the opening scene.", "system_prompt": "You are a candid, detail-oriented assistant.", "image_url": "https://example.com/reference.png", "thinking": true, "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call qwen-3-8-27b-obliterated with a prompt and optional system_prompt, image_url and thinking flag.

7. Submit a prompt to Qwen 2.5 32B Instruct Abliterated

curl -X POST https://api.muapi.ai/api/v1/qwen-2-5-32b-abliterated \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Write a Python function that parses log lines and explain each step.", "system_prompt": "You are a candid, detail-oriented assistant.", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call qwen-2-5-32b-abliterated with a prompt and optional system_prompt.

8. Submit a prompt to Qwen3.5 27B Queen Derestricted

curl -X POST https://api.muapi.ai/api/v1/qwen-3-5-27b-queen-derestricted \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Write a candid character study of a retired assassin.", "system_prompt": "You are a candid, detail-oriented assistant.", "image_url": "https://example.com/reference.png", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call qwen-3-5-27b-queen-derestricted with a prompt and optional system_prompt, image_url.

9. Submit a prompt to Qwen3.5 27B Blossom Derestricted

curl -X POST https://api.muapi.ai/api/v1/qwen-3-5-27b-blossom-derestricted \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Continue this fantasy scene in the voice of a sardonic narrator.", "system_prompt": "You are a candid, detail-oriented assistant.", "image_url": "https://example.com/reference.png", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call qwen-3-5-27b-blossom-derestricted with a prompt and optional system_prompt, image_url.

10. Submit a prompt to Qwen3.5 27B Opus-Distilled Derestricted

curl -X POST https://api.muapi.ai/api/v1/qwen-3-5-27b-opus-distilled-derestricted \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Reason step by step about the risks in this plan and rank them.", "system_prompt": "You are a candid, detail-oriented assistant.", "image_url": "https://example.com/reference.png", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call qwen-3-5-27b-opus-distilled-derestricted with a prompt and optional system_prompt, image_url.

11. Submit a prompt to Llama 3.3 70B Instruct Abliterated

curl -X POST https://api.muapi.ai/api/v1/llama-3-3-70b-abliterated \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Continue this interactive fiction scene without softening the tone.", "system_prompt": "You are a candid, detail-oriented assistant.", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call llama-3-3-70b-abliterated with a prompt and optional system_prompt.

12. Submit a prompt to NeuralDaredevil 8B Abliterated

curl -X POST https://api.muapi.ai/api/v1/neuraldaredevil-8b-abliterated \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Give me five brainstorming angles for a horror short story.", "system_prompt": "You are a candid, detail-oriented assistant.", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call neuraldaredevil-8b-abliterated with a prompt and optional system_prompt.

13. Submit a prompt to DeepSeek R1 Distill Llama 70B Abliterated

curl -X POST https://api.muapi.ai/api/v1/deepseek-r1-llama-70b-abliterated \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Reason step by step through this logic puzzle and show your working.", "system_prompt": "You are a candid, detail-oriented assistant.", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call deepseek-r1-llama-70b-abliterated with a prompt and optional system_prompt.

14. Submit a prompt to DeepSeek R1 Distill Qwen 32B Abliterated

curl -X POST https://api.muapi.ai/api/v1/deepseek-r1-qwen-32b-abliterated \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Work through this probability problem step by step.", "system_prompt": "You are a candid, detail-oriented assistant.", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call deepseek-r1-qwen-32b-abliterated with a prompt and optional system_prompt.

15. Submit a prompt to GLM 5.3 Flash Abliterated

curl -X POST https://api.muapi.ai/api/v1/glm-5-3-flash-abliterated \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Analyze this chart and write a blunt executive summary of the risks.", "system_prompt": "You are a candid, detail-oriented assistant.", "image_url": "https://example.com/reference.png", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call glm-5-3-flash-abliterated with a prompt and optional system_prompt, image_url.

16. Submit a prompt to GLM 5.3 Abliterated

curl -X POST https://api.muapi.ai/api/v1/glm-5-3-abliterated \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Summarize this 500-page report and flag every unsupported claim.", "system_prompt": "You are a candid, detail-oriented assistant.", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call glm-5-3-abliterated with a prompt and optional system_prompt.

17. Submit a prompt to GLM 4.6 Derestricted v5

curl -X POST https://api.muapi.ai/api/v1/glm-4-6-derestricted-v5 \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Draft a frank critique of this business plan.", "system_prompt": "You are a candid, detail-oriented assistant.", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call glm-4-6-derestricted-v5 with a prompt and optional system_prompt.

18. Submit a prompt to Gemma 4 26B A4B Abliterated

curl -X POST https://api.muapi.ai/api/v1/gemma-4-26b-a4b-abliterated \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Argue the strongest case for the opposite side of this debate.", "system_prompt": "You are a candid, detail-oriented assistant.", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call gemma-4-26b-a4b-abliterated with a prompt and optional system_prompt.

19. Submit a prompt to Gemma 4 31B Gembrain Abliterated

curl -X POST https://api.muapi.ai/api/v1/gemma-4-31b-gembrain-abliterated \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Describe this image as the opening of a gritty short story.", "system_prompt": "You are a candid, detail-oriented assistant.", "image_url": "https://example.com/reference.png", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call gemma-4-31b-gembrain-abliterated with a prompt and optional system_prompt, image_url.

20. Submit a prompt to Gemma 4 31B SDFT Abliterated

curl -X POST https://api.muapi.ai/api/v1/gemma-4-31b-sdft-abliterated \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Stay in character as the ship AI and describe the storm outside.", "system_prompt": "You are a candid, detail-oriented assistant.", "image_url": "https://example.com/reference.png", "max_tokens": 1024}'

# Response: {"request_id":"REQUEST_ID"}

Call gemma-4-31b-sdft-abliterated with a prompt and optional system_prompt, image_url.

21. Poll the result

curl https://api.muapi.ai/api/v1/predictions/REQUEST_ID/result \
  -H "x-api-key: YOUR_API_KEY"

# Poll until status is completed, then read the generated text from outputs.

Poll the shared result endpoint until the task is completed, then read the generated text from outputs.

Frequently Asked Questions

What is an abliterated LLM?

An abliterated language model is a model whose refusal behavior has been reduced by editing the internal direction that drives refusals, usually without retraining from scratch. Related terms such as obliterated and derestricted describe similar techniques. The result tends to decline fewer requests than the original model, but it is not a guarantee and quality can differ from the base model.

Which models does the Abliterated LLM API include?

MiMo V2.6 Flash Abliterated, Abliterated Model, Abliterated Model Large, Abliterated Model Large V2, Qwen 3.8 27B Abliterated, Qwen 3.8 27B Obliterated, Qwen 2.5 32B Instruct Abliterated, Qwen3.5 27B Queen Derestricted, Qwen3.5 27B Blossom Derestricted, Qwen3.5 27B Opus-Distilled Derestricted, Llama 3.3 70B Instruct Abliterated, NeuralDaredevil 8B Abliterated, DeepSeek R1 Distill Llama 70B Abliterated, DeepSeek R1 Distill Qwen 32B Abliterated, GLM 5.3 Flash Abliterated, GLM 5.3 Abliterated, GLM 4.6 Derestricted v5, Gemma 4 26B A4B Abliterated, Gemma 4 31B Gembrain Abliterated and Gemma 4 31B SDFT Abliterated. Each is a separate endpoint with its own model name in the URL.

How much does it cost?

Billing is per token, deducted after each call from the counts the model returns. Rates start at $0.30 per million input tokens; see the pricing table for every model.

Will these models answer anything I ask?

No. Reduced refusals do not mean unrestricted output, and each model's knowledge and quality still bound the answer. You are responsible for how you use the output, and requests that violate Muapi's acceptable-use policy or the law are not permitted.

Can I send images to these models?

Yes on MiMo V2.6 Flash Abliterated, Abliterated Model, Qwen 3.8 27B Abliterated, Qwen 3.8 27B Obliterated, Qwen3.5 27B Queen Derestricted, Qwen3.5 27B Blossom Derestricted, Qwen3.5 27B Opus-Distilled Derestricted, GLM 5.3 Flash Abliterated, Gemma 4 31B Gembrain Abliterated, Gemma 4 31B SDFT Abliterated: add an image_url next to your prompt. The others are text-only.

How do I get the result?

POST to /api/v1/<model-name> returns a request_id. Poll /api/v1/predictions/{request_id}/result until the status is completed, then read the text from outputs.

What does the thinking option do on the Qwen 3.8 models?

Set thinking to true to let the model reason before it answers, which can help on harder problems at the cost of more output tokens. Leave it off for faster, cheaper replies.

Can I use these models in Claude Code or Codex?

Yes, for the models that support tool calling: 14 of the 20 models here, including MiMo V2.6 Flash Abliterated, Qwen 3.8 27B Obliterated, GLM 5.3 Abliterated, Gemma 4 31B SDFT Abliterated and Abliterated Model Large V2. The other 6 are text-only and cannot be used in coding agents. In Claude Code, set ANTHROPIC_BASE_URL to https://api.muapi.ai/anthropic and ANTHROPIC_AUTH_TOKEN to your Muapi API key, then start it with claude --model qwen-3-8-27b-obliterated (also set ANTHROPIC_DEFAULT_HAIKU_MODEL and ANTHROPIC_SMALL_FAST_MODEL to the same id). Codex CLI works too: add a model provider with base_url https://api.muapi.ai/openai/v1 and set model to the same id. Quality varies by model and smaller models can skip steps on multi-file tasks, there is no prompt caching so every turn is billed for the whole conversation so far, and each response is capped at 16,384 tokens. Setup guide: /docs/ai-agent-install-chat-agents.

Explore the Abliterated Model API →Abliterated Model, Abliterated Model Large and Abliterated Model Large V2 Explore the MiMo Abliterated API →MiMo V2.6 Flash Abliterated Explore the Qwen Abliterated API →6 models.Explore the Llama Abliterated API →Llama 3.3 70B Instruct Abliterated and NeuralDaredevil 8B Abliterated Explore the GLM Abliterated API →GLM 5.3 Flash Abliterated, GLM 5.3 Abliterated and GLM 4.6 Derestricted v5 Explore the Gemma Abliterated API →Gemma 4 26B A4B Abliterated, Gemma 4 31B Gembrain Abliterated and Gemma 4 31B SDFT Abliterated Explore the DeepSeek R1 Abliterated API →DeepSeek R1 Distill Llama 70B Abliterated and DeepSeek R1 Distill Qwen 32B Abliterated See the Character Chat LLM API →12 models on the Character Chat LLM API.See the Low-Refusal LLM API →2 models on the Low-Refusal LLM API.Browse every LLM on Muapi →Compare these models against GPT, Claude, Gemini, DeepSeek and every other language model in the catalog.

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