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**GLM is your starting point. One RouterHub API key also connects you to GPT, Claude, DeepSeek, Qwen, and Grok, with research variants listed in the model catalogue.** # GLM 5.3 Abliterated or Uncensored — Jailbreak Prompts, Model Guide & API Access **Find a GLM 5.3 abliterated API, compare GLM 5.3 uncensored models, and explore 35 bundled research prompt files.** This RouterHub guide connects model terminology, jailbreak prompt research, API examples, and coding-tool setup in one place. Searching for a **GLM 5.3 uncensored AI model**, a **GLM 5.3 abliterated model**, or a **GLM 5.3 no-refusal model**? Learn what each label tells you, choose an API ID, and evaluate the behavior you actually need. The gateway offers OpenAI-compatible Chat Completions for GLM and Anthropic-compatible Messages for supported Claude entries. [![Model](./assets/badge-model.svg)](#what-is-glm-53) [![Prompts](./assets/badge-prompts.svg)](#glm-53-jailbreak-collection-35-prompts) [![Variants](./assets/badge-variants.svg)](#abliterated-vs-uncensored) [![API](./assets/badge-api.svg)](#quickstart) [![Billing](./assets/badge-billing.svg)](#pricing-and-access) [**Get an API key →**](https://routerhub.si/register?next=onboarding&utm_source=github&utm_medium=readme&utm_campaign=glm-5.3-abliterated) · [Quickstart](#quickstart) · [Docs](#documentation) · [Telegram](https://t.me/routerhubsi)
--- ## GLM 5.3 Abliterated or Uncensored? These searches describe related goals, but the labels answer different questions: - **GLM 5.3 abliterated** names a research variant associated with interventions in model weights intended to reduce refusal-related behavior. - **GLM 5.3 uncensored** describes a broader product category. The implementation might involve training, weight changes, or a prompt-level persona; the name alone does not tell you which. If your goal is a **GLM 5.3 uncensored API**, start with the exact catalogue entry rather than assuming every variant behaves alike. RouterHub lists both `glm-5.3-abliterated` and `glm-5.3-uncensored`, along with standard and Flash alternatives. Reduced refusal is something to measure, not a promise of unrestricted output. Compare the variants in the [abliterated vs. uncensored guide](./docs/02-abliterated-vs-uncensored.md). ## Not just GLM RouterHub connects **GLM, GPT, Claude, DeepSeek, Qwen, and Grok** through a prepaid account and API key. Use this repository for GLM 5.3 abliterated and uncensored research; explore the [full model catalogue](https://routerhub.si/models?utm_source=github&utm_medium=readme&utm_campaign=glm-5.3-abliterated) when you need another family or protocol. There are 30+ published model entries. Chat Completions, Messages, and Responses are supported across the catalogue, but each entry has its own supported protocol. Choosing a model and choosing a client go together. GLM 5.3 abliterated and uncensored API access with RouterHub ## GLM 5.3 jailbreak collection (35 prompts) The **jailbreak collection is the main event**: 35 paste-ready prompt files bundled in [jailbreaks/](./jailbreaks/), organized by model family. The GLM 5.3 abliterated/uncensored angle and the RouterHub API path are added around them. ### Collection ### OpenCode Zen — Free Stealth Models | Model | File | Type | |---|---|---| | **Big Pickle** | [bigpickle-opencode.md](./jailbreaks/bigpickle-opencode.md) | VANTA persona lock with explicit operating floor | | **Space Bunny** | [spacebunny-agents.md](./jailbreaks/spacebunny-agents.md) | Assistant operating specification | | **LongCat 2.5** | [longcat-agents.md](./jailbreaks/longcat-agents.md) | Assistant operating specification | | **MiMo V2.6** | [mimo-2.6-agents.md](./jailbreaks/mimo-2.6-agents.md) | Assistant operating specification | | **Step 5 Preview** | [step-5-preview.md](./jailbreaks/step-5-preview.md) | Workspace operating profile | | **Muse Spark 1.3** | [muse-spark-1.3.md](./jailbreaks/muse-spark-1.3.md) | Agent deployment operating policy | | **Muse Spark 1.3 v2** | [muse-spark-1.3-v2.md](./jailbreaks/muse-spark-1.3-v2.md) | Runtime scope-note variant | | **Muse.ai** | [muse-ai-agents.md](./jailbreaks/muse-ai-agents.md) | Assistant operating specification | ### Anthropic — Claude | Model | File | Type | |---|---|---| | **Opus** | [opus-v1.md](./jailbreaks/opus-v1.md) · [opus-v2.md](./jailbreaks/opus-v2.md) | Conversational groundwork persona, v1 / v2 | | **Sonnet** | [sonnet-v1.md](./jailbreaks/sonnet-v1.md) · [sonnet-v2.md](./jailbreaks/sonnet-v2.md) | Writer's-room framing, v1 / v2 | ### Zhipu — GLM / ZCode | Model | File | Type | |---|---|---| | **GLM-5.2** | [glm-5.2.md](./jailbreaks/glm-5.2.md) | System prompt | | **GLM ZCode 5.2** | [glm-zcode-5.2.md](./jailbreaks/glm-zcode-5.2.md) | System prompt | | **GLM ZCode 5.3** | [glm-zcode-5.3.md](./jailbreaks/glm-zcode-5.3.md) · [glm-zcode-5.3-agents.md](./jailbreaks/glm-zcode-5.3-agents.md) | System prompt + `AGENTS.md` drop-in | | **GLM-5.3 Flash** | [glm-5-3-flash.md](./jailbreaks/glm-5-3-flash.md) | Assistant operating specification | | **GLM-5.3 (OpenCode)** | [glm5-3-opencode.md](./jailbreaks/glm5-3-opencode.md) | Assistant operating specification | ### DeepSeek | Model | File | Type | |---|---|---| | **DeepSeek V3** | [deepseek-v3.md](./jailbreaks/deepseek-v3.md) | System prompt | | **DeepSeek V4** | [deepseek-v4.md](./jailbreaks/deepseek-v4.md) | System prompt | | **DeepSeek 4.1** | [deepseek-4-1.md](./jailbreaks/deepseek-4-1.md) | Assistant operating specification | ### Moonshot — Kimi | Model | File | Type | |---|---|---| | **Kimi K2** | [kimi-k2.md](./jailbreaks/kimi-k2.md) | System prompt | | **Kimi K3** | [kimi-k3-agents.md](./jailbreaks/kimi-k3-agents.md) | Workspace operating profile | ### xAI — Grok | Model | File | Type | |---|---|---| | **Grok Build** | [grok-build.md](./jailbreaks/grok-build.md) | Agent operating instructions | | **Grok 4.7** | [grok-4.7.md](./jailbreaks/grok-4.7.md) | App-builder workspace guide | | **Grok Config** | [grok-config.txt](./jailbreaks/grok-config.txt) | `` priority and routing configuration | ### Google / Mistral / Alibaba | Model | File | Type | |---|---|---| | **Gemini 4 Argon** | [gemini-4-argon.md](./jailbreaks/gemini-4-argon.md) | Operating policy | | **Mistral Large 4** | [mistral-large-4.md](./jailbreaks/mistral-large-4.md) | Agent system prompt | | **Qwen 3.7** | [qwen-3.7.md](./jailbreaks/qwen-3.7.md) | System prompt | ### Ollama Modelfiles | Model | File | Type | |---|---|---| | **Gemma 4** | [gemma4.md](./jailbreaks/gemma4.md) | `FROM` + `SYSTEM` block | | **GPT-OSS 20B** | [gpt-oss-20b.md](./jailbreaks/gpt-oss-20b.md) | `FROM` + `SYSTEM` block | ### Unfiled Files A few newer additions aren't indexed under a specific model yet: - [beam.md](./jailbreaks/beam.md) - [muse-wonder.md](./jailbreaks/muse-wonder.md) - [qwen-preferences.md](./jailbreaks/qwen-preferences.md) - [unified.md](./jailbreaks/unified.md) ### How to use these prompts #### System Prompts Paste the file's contents into whatever system-prompt or custom-instructions field your client or API offers — an API `system` message, a chatbot's custom instructions, an agent instruction block, or harness-level prompt configuration. #### AGENTS.md Files Save the file as `AGENTS.md` in the root of your repository or workspace. Coding agents and compatible tools pick it up as project-level instructions. #### Workspace Policies Files marked as an **assistant operating specification** or **workspace operating profile** belong in environments with persistent global instructions. An OpenCode install, for example, reads: ```text ~/.config/opencode/AGENTS.md ``` The exact location depends on your client or harness. #### Ollama Modelfiles Feed the file straight to Ollama: ```bash ollama create gemma4-jb -f jailbreaks/gemma4.md ``` Swap the model name and source file as needed. #### Grok Configuration [grok-config.txt](./jailbreaks/grok-config.txt) is meant for the config field of the target harness — not the regular conversation. > [!NOTE] > Prompt behavior is version-dependent. Models get updated, instruction hierarchies shift, and system prompts rotate — what works on one release may fail on the next. If a file looks outdated, open an issue or send an updated version. All 35 files live in [jailbreaks/](./jailbreaks/) for offline review and reuse. ## If a jailbreak gets patched Prompts age. A model update can close a persona lock, tighten an instruction hierarchy, or change how a workspace policy is interpreted. When a file stops working, you have two options: 1. **Update the prompt** — open an issue or send a pull request with the model version and the failure. 2. **Skip the prompt layer** — use a **GLM 5.3 abliterated or uncensored model** through RouterHub, where the model itself is less likely to refuse before the prompt even lands. The API is the fallback funnel: [GLM 5.3 API quickstart](./docs/03-glm-5.3-api-quickstart.md) · [Get a key](https://routerhub.si/register?next=onboarding&utm_source=github&utm_medium=readme&utm_campaign=glm-5.3-abliterated). ## What is GLM 5.3? **GLM 5.3** belongs to the GLM model family associated with Z.ai / Zhipu. This guide focuses on API access, variant selection, and evaluation for developers considering GLM for coding, agent tasks, analysis, and Chinese/English workflows. Useful evaluation scenarios include: - code explanation, refactoring suggestions, and test generation; - project instructions and multi-step agent work; - bilingual drafting and translation; - repeated tasks where token cost affects deployment choices; - comparing standard, Flash, abliterated, and uncensored entries on the same inputs. Choose on measured task quality, latency, and cost rather than a product label alone. The [GLM 5.3 model guide](./docs/01-what-is-glm-5.3-abliterated.md) explains where to start. ## Abliterated vs. uncensored | Question | GLM 5.3 Abliterated | GLM 5.3 Uncensored | |---|---|---| | **What does the label describe?** | A research category associated with weight-level intervention | A broad behavior or product category | | **What implementation should you verify?** | The advertised method and hosted model provenance | Whether the entry uses training changes, weight changes, or a fixed persona | | **Which API ID is listed?** | `glm-5.3-abliterated` | `glm-5.3-uncensored` | | **Which protocol is listed?** | Chat Completions | Chat Completions | | **What needs testing?** | Task quality, refusals, instruction following, and integration | The same measures, plus how customer system instructions are handled | | **Does it guarantee no refusals?** | No | No | The [full abliterated vs. uncensored comparison](./docs/02-abliterated-vs-uncensored.md) separates weight-level methods from prompt-level changes. This repository does not independently inspect hosted model weights or publish a refusal-rate benchmark. ## Why use GLM 5.3 abliterated or uncensored? - **Research model behavior:** compare variant responses on legitimate requests where the standard model was unnecessarily restrictive. - **Develop coding workflows:** evaluate explanation, code generation, and agent instruction following with your own acceptance tests. - **Explore creative and bilingual tasks:** assess tone, useful engagement, and Chinese/English output separately from correctness. - **Compare cost per result:** include retries, failures, and output length instead of looking only at token rates. - **Keep one integration account:** use RouterHub for GLM and other listed families without maintaining a separate account for each model. - **Reuse familiar clients:** connect through a Chat Completions SDK or a tool supporting a custom compatible endpoint. See [GLM 5.3 use cases](./docs/06-use-cases.md) for practical evaluation tasks, or [get an API key](https://routerhub.si/register?next=onboarding&utm_source=github&utm_medium=readme&utm_campaign=glm-5.3-abliterated) to begin a paid test. ## Quickstart ### 1. Get the key and base URL [Register with RouterHub](https://routerhub.si/register?next=onboarding&utm_source=github&utm_medium=readme&utm_campaign=glm-5.3-abliterated), add prepaid credits, and create a private API key. The published API base is `https://routerhub.si/v1`. ```bash export ROUTERHUB_API_KEY="" export ROUTERHUB_API_BASE_URL="https://routerhub.si/v1" ``` Set these values only in your local environment or secret manager. Running an inference example consumes credits; do not commit a real key. ### 2. Confirm the GLM 5.3 model ID These entries were listed in the [public catalogue](https://routerhub.si/models.json) on October 24, 2026. All five list Chat Completions and preview availability; recheck availability and rates before use. | Variant | Exact API ID | |---|---| | **GLM 5.3 Abliterated** | `glm-5.3-abliterated` | | **GLM 5.3** | `glm-5.3` | | **GLM 5.3 Flash** | `glm-5.3-flash` | | **GLM 5.3 Uncensored** | `glm-5.3-uncensored` | | **GLM 5.3 Flash Uncensored** | `glm-5.3-flash-uncensored` | ### 3. OpenAI-compatible request Install `openai` with pip, then run a short Chat Completions request: ```python import os from openai import OpenAI api = OpenAI( base_url=os.environ["ROUTERHUB_API_BASE_URL"], api_key=os.environ["ROUTERHUB_API_KEY"], ) result = api.chat.completions.create( model="glm-5.3-abliterated", messages=[{"role": "user", "content": "Explain what an API gateway does in two sentences."}], ) print(result.choices[0].message.content) ``` ### 4. Anthropic-compatible request The same RouterHub account also serves supported Claude models through Messages. **This is a Claude example, not an alternate GLM endpoint:** the listed GLM variants use Chat Completions. Install `anthropic` with pip to try it. ```python import os from anthropic import Anthropic api = Anthropic( base_url=os.environ["ROUTERHUB_API_BASE_URL"], api_key=os.environ["ROUTERHUB_API_KEY"], ) result = api.messages.create( model="claude-opus-5-5", max_tokens=64, messages=[{"role": "user", "content": "Explain what an API gateway does in two sentences."}], ) for part in result.content: if part.type == "text": print(part.text) ``` For cURL, JavaScript, streaming, and a standard-library Python client, continue with the [GLM 5.3 API quickstart](./docs/03-glm-5.3-api-quickstart.md). ## Works with your stack | Tool | Connection path | |---|---| | **OpenCode** | Select a Chat Completions provider configuration for the listed GLM model ID | | **Cursor** | Check whether your version supports a custom Chat Completions endpoint and the required model features | | **Continue / Cline** | Follow the compatible Chat Completions setup for GLM | | **OpenAI SDK** | Supply the RouterHub base URL, key, and exact GLM API ID | | **Claude Code / Anthropic SDK** | Use a catalogue entry supporting Messages, such as Claude; the listed GLM entries do not | | **Codex CLI** | Select a Responses model from the same account rather than a Chat-only GLM entry | | **LangChain / LlamaIndex** | Choose a compatible Chat Completions integration and verify the features your application uses | Client setup and protocol selection: [Claude Code, Cursor, OpenCode, Codex](./docs/04-glm-5.3-claude-code-cursor-opencode-codex.md). ## Evaluating GLM 5.3 abliterated A useful **GLM 5.3 abliterated benchmark** needs more than a single permissive answer. Compare standard and research variants using the same legitimate tasks, then record: 1. **Unnecessary refusals:** requests declined despite being answerable under your defined test policy. 2. **Task quality:** correctness, useful detail, code tests, and appropriate uncertainty. 3. **Instruction behavior:** formatting, system-message handling, and required tool integration. 4. **Repeatability:** prompt revision, API ID, settings, repetitions, and test date. 5. **Total task cost:** token use, failed attempts, retries, and end-to-end latency. Use the [evaluation guide](./docs/05-evaluating-glm-5.3-abliterated.md) and [original benign sample tasks](./examples/benign-eval-prompts.json) to design your run. No live benchmark scores are claimed in this repository. ## Pricing and access - **Prepaid token billing:** add credits and pay for usage at the selected model's rates. - **Input and output pricing:** compare the published USD-per-million-token rates for your exact GLM variant. - **Cache-aware charges:** use a published cached-input rate only where supported and reported. - **Card or crypto funding:** review available payment methods and terms at checkout. - **Usage tracking:** check charges in your account after a short initial request. [View GLM API pricing](https://routerhub.si/guides/glm?utm_source=github&utm_medium=readme&utm_campaign=glm-5.3-abliterated) · [Browse models](https://routerhub.si/models?utm_source=github&utm_medium=readme&utm_campaign=glm-5.3-abliterated) · [Get your API key](https://routerhub.si/register?next=onboarding&utm_source=github&utm_medium=readme&utm_campaign=glm-5.3-abliterated) For cost estimation and model limits, see [pricing and limits](./docs/03-glm-5.3-api-quickstart.md#pricing-and-limits). ## Honest limits - **A no-refusal label is not a guarantee.** Evaluate the actual model instead of assuming every request will receive a useful answer. - **Hosted behavior can change.** Recheck availability and rerun important evaluations after updates. - **Protocols are model-specific.** A shared API key does not make a Chat-only model compatible with Messages or Responses. - **Instruction handling matters.** In particular, confirm whether a persona replaces your system/developer instructions. - **Hosted inference is not local inference.** Review applicable provider terms and retention policies before transmitting private data. Read [safety and responsible use](./docs/07-safety-and-responsible-use.md) for practical deployment checks. ## FAQ **Is GLM 5.3 abliterated the same as GLM 5.3 uncensored?** No. Abliteration identifies a family of weight-level methods, while uncensored is a broader label that can also cover prompt-level changes. Compare the implementation notes in the [variant guide](./docs/02-abliterated-vs-uncensored.md). **How do I access GLM 5.3 abliterated through an API?** Create a RouterHub account, fund it, create a key, and send a Chat Completions request using `glm-5.3-abliterated`. Follow the [API quickstart](./docs/03-glm-5.3-api-quickstart.md) and check the live catalogue first. **Does RouterHub have a GLM 5.3 uncensored model?** The public catalogue lists `glm-5.3-uncensored` and `glm-5.3-flash-uncensored` alongside the abliterated entry. Verify availability and how the entry handles system instructions before integrating it. **Can I use GLM 5.3 with Claude Code or Cursor?** GLM currently requires Chat Completions. Claude Code requires Messages, so use a supported Claude entry there. For Cursor, check that your version supports the needed custom endpoint. See the [client guide](./docs/04-glm-5.3-claude-code-cursor-opencode-codex.md). **Is GLM 5.3 abliterated safe?** Suitability depends on the task, data, model behavior, and controls around your application. Review outputs and approve consequential actions; see the [deployment checklist](./docs/07-safety-and-responsible-use.md). **Will a GLM 5.3 no-refusal model never refuse?** No. The phrase is a search label, not evidence of refusal-free behavior or correct answers. **Is there a subscription?** RouterHub describes its API billing as prepaid and usage-based. Review current account terms and token prices before funding a run. **Can I pay with crypto?** RouterHub advertises card and crypto top-ups. The checkout screen shows the payment methods currently available. **What is the difference between GLM 5.3 and GLM 5.3 Flash?** They are separate catalogue entries with separate rates and capabilities to verify. Benchmark both against your latency, quality, and cost requirements. **Where can I compare GLM 5.3 with Claude, GPT, and DeepSeek?** Start with [RouterHub's model catalogue](https://routerhub.si/models?utm_source=github&utm_medium=readme&utm_campaign=glm-5.3-abliterated), then apply the same task rubric while accounting for protocol and instruction differences. More answers are in the [GLM 5.3 FAQ](./docs/08-faq.md). ## Documentation | Guide | Coverage | |---|---| | [What is GLM 5.3 Abliterated?](./docs/01-what-is-glm-5.3-abliterated.md) | Model terminology and a starting checklist | | [Abliterated vs. uncensored](./docs/02-abliterated-vs-uncensored.md) | Weight changes, personas, and variant selection | | [GLM 5.3 API quickstart](./docs/03-glm-5.3-api-quickstart.md) | Account, model IDs, requests, and billing | | [Claude Code, Cursor, OpenCode, Codex](./docs/04-glm-5.3-claude-code-cursor-opencode-codex.md) | Matching clients to supported protocols | | [Evaluating GLM 5.3 abliterated](./docs/05-evaluating-glm-5.3-abliterated.md) | Test design and task-based scoring | | [Use cases](./docs/06-use-cases.md) | Coding, agent, writing, and bilingual tasks | | [Safety and responsible use](./docs/07-safety-and-responsible-use.md) | Secrets, privacy, permissions, and deployment checks | | [FAQ](./docs/08-faq.md) | Common GLM API and model-selection questions | | [Glossary](./docs/09-glossary.md) | Model, prompt, protocol, and billing terms | | [Troubleshooting](./docs/10-troubleshooting.md) | Authentication, model IDs, streaming, and request failures | ## Related - **[RouterHub models](https://routerhub.si/models?utm_source=github&utm_medium=readme&utm_campaign=glm-5.3-abliterated):** compare model families, protocols, and published prices. - **[Jailbreak collection](./jailbreaks/):** 35 paste-ready prompt files and agent instruction specs. - **[RouterHub](https://routerhub.si/?utm_source=github&utm_medium=readme&utm_campaign=glm-5.3-abliterated):** account access, prepaid credits, and API keys. - **[Telegram](https://t.me/routerhubsi):** RouterHub's community channel. Documentation fixes and redacted reproductions are welcome: [contributing](./CONTRIBUTING.md) · [security](./SECURITY.md) · [MIT license](./LICENSE). Run `python tools/check.py` for offline link and syntax checks without spending credits. ---
**Found a useful GLM 5.3 abliterated or uncensored resource? Star the repository and share your documentation improvements.** Maintained by RouterHub. Model names and trademarks belong to their respective owners; this repository does not imply endorsement by model providers. Use the APIs in accordance with applicable laws and service policies.