Abliterated Large V2 API

On Zurelay, abliterated-large-v2 costs $2.90 per 1M input tokens et $4.85 per 1M output tokens. Abliteration AI's list price is $3.00 input et $5.00 output per 1M, so you save 3%. Reasoning tokens bill as output, one rate applies at every prompt length, and failed requests are never billed.

Abliteration removes a model's refusals by editing its weights rather than retraining it. It compares the model's internal activations on prompts it refuses et prompts it answers, finds the direction linked to refusing et suppresses it, a method described in 2024 research by Arditi and colleagues. Abliteration AI's documentation links Large V2 to Z.ai's GLM-5.3, and notes that other abilities can shift along with the refusals, so evaluate it on your own tasks.

Work that mainstream models often refuse or water down: authorized security research et red-teaming, explanations of penetration-testing techniques, testing your own AI systems with adversarial prompts, fiction with dark themes, et frank answers on controversial or sensitive topics without moralizing.

Yes. Abliteration removes the model's refusals, not the rules. Zurelay's Terms sur Service (https://zurelay.com/legal/terms) apply to everything sent to Abliterated Large V2, including the acceptable use rules in section 7, et you are responsible for how you use its output, as with any model on Zurelay.

Install the official openai package, set base_url to https://api.zurelay.com/v1 et use your Zurelay API key. Then send a Chat Completions request with model set to "abliterated-large-v2". Zurelay also accepts abliterated-model-large-v2 et abliteration-ai/abliterated-model-large-v2.

It holds 1,000,000 tokens of context, et in our tests it found one fact buried in a 112K-token prompt in 11 seconds. Reasoning et the answer share the output budget you set with max_tokens, so leave room for both.

No. It takes text only, as on Abliteration AI's own API. A request that includes images or files is turned away with a clear error before anything is billed.

It always reasons a little before it answers. Set reasoning_effort to low, high or max; max is the default. Reasoning can't be switched off, et a request for none runs en low. Abliteration AI's documentation says the same of its own API.

Yes, with one catch. The model reasons before it answers, et a stop sequence that also turns up in its reasoning ends the response early, sometimes before any answer text. Use a stop sequence that only belongs in the answer, such as a distinctive end marker, et it works as expected. max_tokens and the usual sampling settings work too.

Yes. Pass tools as you would to any OpenAI model; it can call several at once, also while streaming, et reads tool results. tool_choice "required", a tool forced by name et "none" all work. For JSON, send response_format with json_object or json_schema and the answer comes back as JSON. logprobs isn't supported.

Yes. Requests for abliterated-large-v2 run on Abliteration AI's Abliterated Large V2, et Zurelay doesn't swap in a smaller or substitute model. Asked what it is, it names itself Abliterated Large V2, made by Abliteration AI, et it keeps any persona your system prompt gives it. Automatic smart routing has no alternative for it, so a request never quietly falls back to a model that still has its refusals; only a fallback you set yourself, in a key's custom rules or a request's models list, can answer instead, and the x-zurelay-model header names the model that answered. Responses are sampled, so wording varies between runs. Zurelay is independent and is not affiliated with or endorsed by Abliteration AI.