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Qwen3.5 27B Queen Derestricted: Modele wielkojęzykowe AI

Call Qwen3.5 27B Queen Derestricted through one API. 262K-token context, streaming and pay-per-token pricing. Try free in the Muapi playground. Qwen3.5 27B Queen Derestricted is a derestricted Qwen3.5 27B model with a 262K-token context window and image input, modified to reduce refusal behavior. Muapi exposes it through a single REST endpoint with async polling and Server-Sent Events streaming, so you can drop it into chat apps, agents and workflows without hosting GPUs. It is best suited to general chat and image understanding. Pricing is pay-per-token at $0.612/M input tokens and $0.612/M output tokens, with no subscription. See also Qwen 3.8 27B Obliterated, Qwen 2.5 32B Abliterated, Qwen 3.8 27B Abliterated, Qwen3.5 27B Blossom Derestricted, Qwen3.5 27B Opus-Distilled Derestricted. Browse the full lineup on the Qwen Abliterated API page or the abliterated LLM API hub; related families: GLM Abliterated API and Gemma Abliterated API. 'Abliterated' and 'derestricted' describe modifications that reduce the model's refusal behavior. They do not guarantee unrestricted output, and you remain responsible for complying with applicable laws and the Muapi terms of use.

Interaktywne sterowanie modelem

Call Qwen3.5 27B Queen Derestricted through one API. 262K-token context, streaming and pay-per-token pricing. Try free in the Muapi playground.

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Przegląd

O tym modelu

Qwen3.5 27B Queen Derestricted is a derestricted Qwen3.5 27B model with a 262K-token context window and image input, modified to reduce refusal behavior. Muapi exposes it through a single REST endpoint with async polling and Server-Sent Events streaming, so you can drop it into chat apps, agents and workflows without hosting GPUs. It is best suited to general chat and image understanding. Pricing is pay-per-token at $0.612/M input tokens and $0.612/M output tokens, with no subscription. See also Qwen 3.8 27B Obliterated, Qwen 2.5 32B Abliterated, Qwen 3.8 27B Abliterated, Qwen3.5 27B Blossom Derestricted, Qwen3.5 27B Opus-Distilled Derestricted. Browse the full lineup on the Qwen Abliterated API page or the abliterated LLM API hub; related families: GLM Abliterated API and Gemma Abliterated API. 'Abliterated' and 'derestricted' describe modifications that reduce the model's refusal behavior. They do not guarantee unrestricted output, and you remain responsible for complying with applicable laws and the Muapi terms of use.

1Chat and assistants: Build conversational apps on Qwen3.5 27B Queen Derestricted for general chat and image understanding.
2Low-refusal experimentation: Compare refusal behavior against the base model in your own evaluations, within Muapi's usage policy.
3Agents and workflows: Call the model from Muapi workflow nodes and the [abliterated LLM API](/abliterated-llm-api) hub examples.
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Ceny i wartość

Analiza kosztów

muapiapp$0.612/M input tokens and $0.612/M output tokens

Rozliczenie za token, według rzeczywistego użycia, z niewielką kwotą minimalną pobieraną z góry.

Fal.aiNiedostępne

Qwen3.5 27B Queen Derestricted nie jest dostępny jako hostowany endpoint.

ReplicateNiedostępne

Qwen3.5 27B Queen Derestricted nie jest dostępny jako hostowany endpoint.

** Ceny konkurencji są szacowane na podstawie podobnych architektur modeli i poziomów użytkowania.

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Szczegóły techniczne

Schemat konfiguracji

podpowiedźstring

dla przepływów pracy żądań/ankiet i zdarzeń wysyłanych przez serwer

Wartość domyślnaSummarize the trade-offs between a monolith and microservices in five bullet points.
Adres URL obrazustring

Optional public image URL for multimodal analysis.

Wartość domyślnaundefined
Monit systemowystring

, .

Wartość domyślnaYou are a concise, direct assistant.
Maksymalna liczba tokenówinteger

Optional maximum number of tokens to generate.

Wartość domyślna8192
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Przewodnik wdrożeniowy

Dokumentacja deweloperska

How to Use Qwen3.5 27B Queen Derestricted API

  1. Get an API key: Create a key in your Muapi dashboard.

  2. Send a prompt: POST prompt (plus optional system_prompt and max_tokens, up to 32768) to /api/v1/qwen-3-5-27b-queen-derestricted. Provide an optional public image_url to include an image with your prompt.

curl -X POST https://api.muapi.ai/api/v1/qwen-3-5-27b-queen-derestricted \
  -H "x-api-key: $MUAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Explain how attention works in transformers.", "image_url": "https://example.com/photo.jpg"}'
  1. Poll or stream: Poll GET /api/v1/predictions/{request_id}/result until status is completed, or stream tokens live from /api/v1/qwen-3-5-27b-queen-derestricted/stream.
curl -X POST https://api.muapi.ai/api/v1/qwen-3-5-27b-queen-derestricted/stream \
  -H "x-api-key: $MUAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Explain how attention works in transformers.", "image_url": "https://example.com/photo.jpg"}'
  1. Read the result: The generated text is returned in outputs. Usage is billed on actual token counts.
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Często zadawane pytania

Często zadawane pytania

What is Qwen3.5 27B Queen Derestricted?

Qwen3.5 27B Queen Derestricted is a derestricted Qwen3.5 27B model with a 262K-token context window and image input, modified to reduce refusal behavior.

What does abliterated mean?

Abliterated or derestricted models are modified to reduce refusal behavior. This lowers, but does not eliminate, refusals and does not guarantee unrestricted output.

How is Qwen3.5 27B Queen Derestricted priced?

Billing is per token: $0.612/M input tokens and $0.612/M output tokens. A small minimum is reserved when the request starts and reconciled to actual usage.

Does Qwen3.5 27B Queen Derestricted support streaming?

Yes. Stream tokens live from `/api/v1/qwen-3-5-27b-queen-derestricted/stream` using Server-Sent Events, or poll the async endpoint.

What is the context window?

The context window is about 262K tokens. Prompt and output together must fit inside it; `max_tokens` is capped at 32768. Image input is supported via `image_url`.

Is output guaranteed to be unrestricted?

No. Abliterated models are less likely to refuse, but behavior varies by prompt and quality can differ from the base model. Evaluate it for your use case and follow applicable laws.