GLM 5.3 Abliterated

Name: GLM 5.3 Abliterated
Brand: GLM

A derivative of GLM 5.3 with modified refusal behavior for general-purpose inference.

AvailableGet an API key Read the API docs

GLM model family

About this model

GLM 5.3 Abliterated is a modified derivative of GLM 5.3. Abliterated describes modified refusal behavior, not unrestricted use. Responses can still be refused or inaccurate. Arnict acceptable-use rules apply to every model.

Parameters: 753B753.33 billion parameters in the official release tensor metadata.
Native context: 1,048,5761,048,576 tokens served by Arnict.
Maximum output: 131,072Hard limit

Capabilities

Chat completionsUse this model with the chat-completions API when it is marked Available.
Native input modalitiesText input is listed in the published catalog metadata.
Long-context input1,048,576 tokens · 1,048,576 tokens served by Arnict.
Defined output limit131,072 tokens

Published limits

Published model-card facts, kept separate from live availability.

Metric	Published value	Note
Arnict API output limit	131,072 tokens	Maximum output accepted by the Arnict API for this model
Parameters	753.33 billion parameters in the official release tensor metadata.	Upstream model card
Context window	1,048,576 tokens	1,048,576 tokens served by Arnict.
Maximum output	131,072 tokens hard limit	Upstream model card
Weights / activations	Official release: FP8 E4M3 with dynamic activations. Connected serving format may differ.	Published format

78 transformer layers
256 routed experts; 8 selected per token; 1 shared expert
6,144 hidden dimensions
Text-only input and output
Reasoning effort: low, high or max

Use zai/glm-5.3-uncensored with an OpenAI-compatible client now.

Read the API docs →

Call it with the OpenAI SDK

Use the complete model ID with the OpenAI SDK. Set your Arnict API key as an environment variable before running the example.

chat.tsTypeScript

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.arnict.com/v1",
  apiKey: process.env.ARNICT_API_KEY,
});

const completion = await client.chat.completions.create({
  model: "zai/glm-5.3-uncensored",
  messages: [
    { role: "user", content: "Explain continuous batching in one paragraph." },
  ],
});

console.log(completion.choices[0].message.content);