refusing件中Answers instead件
security, fictionとsensitive questions that mainstream models often decline or water down.上のAbliteration removes the learned refusal behavior, so it takes
The Abliterated Large V2 API: Abliteration AI's large model with its refusal behavior removed, for security research, red-teamingとdark fiction, 3% below Abliteration AI'sの定価
abliterated-large-v2from openai import OpenAIclient = OpenAI( base_url="https://api.zurelay.com/v1", api_key="YOUR_ZURELAY_KEY",)stream = client.chat.completions.create( model="abliterated-large-v2", messages=[{"role": "user", "content": "Explain quicksort in two sentences."}], stream=True,)for chunk in stream: if chunk.choices: print(chunk.choices[0].delta.content or "", end="")ベースURL https://api.zurelay.com/v1. どのOpenAI SDKにも対応しています。 チャットAPIドキュメント
料金
プリペイド残高からの従量課金で、サブスクリプションは不要です。$10からチャージできます。失敗したリクエストには課金されません。
| 料金 | Zurelay | Abliteration AIの定価 | 節約額 |
|---|---|---|---|
入力 1M トークンあたり | $2.90 | 3%割引 | |
出力 1M トークンあたり | $4.85 | 3%割引 |
プロンプトの長さにかかわらず同じ料金です, up to the full 1M context window。ストリーミング、ツール呼び出し、構造化出力に追加料金はかかりません。
スライダーで月間使用量を設定してください。
年間$78.00
概要
Service still apply to everything you send it.でAbliterated Large V2 is Abliteration AI's large text model with its built-in refusal behavior removed by abliteration, a technique that edits a model's weights to suppress its learned refusals, so it answers many requests that mainstream models decline. Abliteration AI's documentation links it to Z.ai's GLM-5.3. The Zurelay Abliterated Large V2 API serves it through one OpenAI-compatible endpoint with a 1M-token context window,件中3% below Abliteration AI's list price. Zurelay's Terms件
Abliterated Large V2 is the large text model from Abliteration AI, a company that hosts models with their refusal behavior removed. Abliteration AI's documentation links it to GLM-5.3, Z.ai's open-weight flagship,とlists it as its recommended text model; the earlier Abliterated Large is deprecated. It reads text and writes text, with a context window of 1,000,000 tokens. On Zurelay the model ID is abliterated-large-v2, and abliterated-model-large-v2 and abliteration-ai/abliterated-model-large-v2 work too. Itの出力料金は1Mトークンあたり$2.90 per 1M input tokens and $4.85です。
Abliteration works on open-weight models. It compares a model's internal activations on prompts it refusesとprompts it answers, finds the direction linked to refusing,とedits the weights to suppress it. The edited model answers prompts the original would decline. Abliteration AI notes that fewer refusals don't guarantee that instruction following, tool use or code quality stay the same, so test it on your own tasks before you rely on it.
It suits work that mainstream models often refuse or water down: authorized security researchとred-teaming, explanations of penetration-testing techniques, testing your own AI agentsとsafety filters, fiction with dark themes, and plain answers on controversial or sensitive topics without moralizing. Removing a model's refusals doesn't change what you may use it for. Zurelay's Terms of Service (https://zurelay.com/legal/terms) still apply to everything sent to it, including the acceptable use rules in section 7, and you are responsible for how you use its output.
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,とnone runs at low. It calls tools, several at onceとwhile streaming, follows json_object and json_schema in response_format, and takes max_tokens, stop sequences and the usual sampling settings; logprobs isn't supported. Because it reasons first, a stop sequence that also turns up in its reasoning can end the answer early, so use one that only belongs in the answer, such as a distinctive end marker. In our tests it found one fact buried in a 112K-token prompt in 11 seconds. You pay $2.90 per 1M input tokens and $4.85 per 1M output tokens against Abliteration AI's list price of $3.00 and $5.00.
強み
security, fictionとsensitive questions that mainstream models often decline or water down.上のAbliteration removes the learned refusal behavior, so it takes
It answers the question asked, so a sensitive topic gets a plain, factual reply rather than a refusal or a lecture.
Long reports, logs, codebasesとtranscripts fit in one request. In our tests it found one fact buried in a 112K-token prompt in 11 seconds.
並列での関数呼び出しとwhile streaming,とJSON schema output, so it fits into agents and pipelines like any OpenAI model.
ユースケース
Authorized penetration tests, threat modelingとred-team exercises, with explanations of how attacksとexploits work that other models often refuse to give.
Adversarial promptsとtest cases for your agents, chatbotsとsafety filters, which a model that refuses won't write for you.
it to object.件中Crime, war, horrorとmorally complex characters, written for the story without the model stepping out件
Researchとfrank discussion of contested history, politics, religionとother subjects where mainstream models hedge or decline.
始める
ウェイトリストも新しいSDKも不要です。OpenAIに対応したコードなら、そのままZurelayでも使えます。
Sign up, add creditとcreate an API key. Set a monthly budget or a rate limit per key if you like.
Change the base URL. Everything else in your code stays the same.
https://api.zurelay.com/v1Send chat completions as usual. Streaming, tool callsとusage reporting work as you expect.
abliterated-large-v2比較
1Mトークンあたり入力$0.38 / 出力$1.21
Pick GLM-5.3, the Z.ai model Abliteration AI's documentation links Large V2 to, with its refusal behavior intact, cached input pricingとa much lower price per token.
GLM-5.3 API1Mトークンあたり入力$0.058 / 出力$0.19
Pick GLM-5.3 Flash, Z.ai's low-cost GLM, for everyday codingとagent work that doesn't need refusals removed.
GLM-5.3 Flash API1Mトークンあたり入力$0.30 / 出力$1.30
Pick Kimi K2.6 for Moonshot's open-weight model with imageとvideo input and thinking you can switch off, at a lower price per token.
Kimi K2.6 APIOn Zurelay, abliterated-large-v2 costs $2.90 per 1M input tokensと$4.85 per 1M output tokens. Abliteration AI's list price is $3.00 inputと$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とprompts it answers, finds the direction linked to refusingと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とred-teaming, explanations of penetration-testing techniques, testing your own AI systems with adversarial prompts, fiction with dark themes,とfrank answers on controversial or sensitive topics without moralizing.
Service (https://zurelay.com/legal/terms) apply to everything sent to Abliterated Large V2, including the acceptable use rules in section 7,とyou are responsible for how you use its output, as with any model on Zurelay.件中Yes. Abliteration removes the model's refusals, not the rules. Zurelay's Terms件
Install the official openai package, set base_url to https://api.zurelay.com/v1と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とabliteration-ai/abliterated-model-large-v2.
It holds 1,000,000 tokens of context,とin our tests it found one fact buried in a 112K-token prompt in 11 seconds. Reasoningとthe answer share the output budget you set with max_tokens, so leave room for both.
Abliteration AI's own API. A request that includes枚s or files is turned away with a clear error before anything is billed.上の画像No. It takes text only, as
low. Abliteration AI's documentation says the same of its own API.で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,とa request for none runs
Yes, with one catch. The model reasons before it answers,と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,と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,とreads tool results. tool_choice "required", a tool forced by nameと"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,とZurelay doesn't swap in a smaller or substitute model. Asked what it is, it names itself Abliterated Large V2, made by Abliteration AI,と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.