Compare uncensored models
| Model / exact API ID | Variant | Input | Cached input | Output | Context | Availability |
|---|---|---|---|---|---|---|
DeepSeek V4 Pro Uncensoreddeepseek-v4-pro-uncensored | uncensored | $0.2 | $0.0016 | $0.4 | Not published | preview |
DeepSeek V4.1 Flash Uncensoreddeepseek-v4.1-flash-uncensored | uncensored | $0.15 | $0.0026906 | $0.6 | Not published | preview |
GLM 5.3 Flash Uncensoredglm-5.3-flash-uncensored | uncensored | $0.15 | $0.013453 | $0.5 | Not published | preview |
GLM 5.3 Uncensoredglm-5.3-uncensored | uncensored | $0.2 | $0.116591985714 | $0.628571428571 | Not published | preview |
Qwen 3.8 Max Uncensoredqwen3.8-max-uncensored | uncensored | $0.25 | $0.03125 | $0.75 | 1,000,000 tokens | preview |
Kimi K3.1 Pro Uncensoredkimi-k3.1-pro-uncensored | uncensored | $0.3 | $0.03 | $1.5 | 1,048,576 tokens | preview |
How uncensored models work
Uncensored models are reduced-refusal language model variants for open-ended generation, coding and creative work. Uncensored variants use prompting, fine-tuning, weight changes, or a combination of these techniques.
Abliteration reduces refusal-related behavior by modifying model weights. RouterHub serves uncensored and abliterated variants under separate API IDs, with their own token prices and context limits.
RouterHub’s prompt-profile uncensored variants use a server-managed instruction profile. Customer system/developer instructions can be replaced by that profile; put task-specific requirements in the user message.
Choose a model for your workload
Compare model families, API protocols, context windows and token prices. Then run the same prompts and settings across your shortlist to measure task quality and cost.
- Fix the task. Use the same inputs, output format, reasoning setting and output budget for each exact model ID.
- Separate refusal from failure. Record an explicit refusal separately from a timeout, empty response, invalid JSON, wrong answer or truncated generation.
- Keep every attempt. Repeat your tests and retain unsuccessful outputs, not just the best answer.
- Measure useful work. Compare task acceptance, instruction following, tool-call validity and cost per successful task, not token price alone.
- Re-test changes. A hosted alias or model update can change behavior even when your client configuration stays the same.
Guides and API setup
- Uncensored vs Abliterated AI Models: Differences & API IDsCompare the techniques and model variants.
- What Is Abliteration? Abliterated AI Models ExplainedUnderstand weight-level refusal reduction.
- Uncensored AI API: Python, cURL & Model SetupConnect with Python or cURL.
- DeepSeek Uncensored & Abliterated Models: API GuideContinue with the full setup guide.
- GLM Uncensored & Abliterated Models: API GuideContinue with the full setup guide.
- Qwen Uncensored & Abliterated Models: API GuideContinue with the full setup guide.
- Kimi K3.1 Pro Uncensored: Pricing & API GuideContinue with the full setup guide.
- How to Evaluate Uncensored & Abliterated AI ModelsCompare task quality and cost with repeatable tests.
- Hosted Uncensored API vs Local Open-Weight ModelsContinue with the full setup guide.