> For the complete documentation index, see [llms.txt](https://documentation.rorulabs.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://documentation.rorulabs.com/overview/roru-rouge.md).

# Roru Rouge (Uncensored Flagship)

**Roru Rouge** is Roru AI's flagship uncensored language model. It is a world-class **32B** dense, all-active model with a 256K-token context window that runs entirely inside a sealed Trusted Execution Environment (TEE). Your prompts and outputs never leave the enclave, so even the host running the hardware cannot read them.

Roru Rouge is the uncensored intelligence layer behind your Personal AI. Where most frontier models are heavily censored, guardrailed, and routed through centralized servers under vendor-imposed filters, Roru Rouge is built for operators who demand raw, unfiltered frontier-class intelligence with full ownership of weights, keys, and data. It delivers massive compute power while running comfortably on a single consumer GPU.

***

### Why Roru Rouge

* **Uncensored & Operator-Controlled.** Fully uncensored open weights under Apache 2.0. No artificial corporate refusals, no vendor-imposed censorship, no third party dictating what your AI can discuss or analyze.
* **Enclave-Native Privacy.** Every inference runs inside a sealed TEE. The host never sees your prompts, and nothing leaves the enclave unencrypted.
* **Complete Sovereignty.** You hold the weights and the keys. Self-host Roru Rouge or run it on the decentralized Roru network.
* **$RORU-Gated Access.** API access is metered through the $RORU token, keeping inference decentralized and operator-owned.
* **Architectural Stability.** A pure dense 32B architecture offers extreme reliability with no mixture-of-experts routing variance.

***

### Specifications

| Property       | Roru Rouge                           |
| -------------- | ------------------------------------ |
| Parameters     | 32B (dense, all-active)              |
| Alignment      | Uncensored / Operator-defined policy |
| Context window | 256K tokens                          |
| Execution      | Sealed TEE (enclave)                 |
| Weights        | Open, user-owned (Apache 2.0)        |
| Access         | $RORU-gated API or self-host         |

***

### Benchmark Performance

Against its closest same-class rival, Qwen 3.6, Roru Rouge holds the edge across the board—dominating on vision while securing definitive leads in graduate-level reasoning and competition math.

| Benchmark             | Roru Rouge (32B) | Qwen3.6 35B-A3B | GLM-5.1 | Llama 4 Scout |
| --------------------- | ---------------- | --------------- | ------- | ------------- |
| **MMLU Pro**          | **85.9%**        | \~85.2%         | —       | —             |
| **AIME 2026**         | **93.4%**        | 92.7%           | 95.3%   | —             |
| **GPQA Diamond**      | **86.8%**        | 86.0%           | \~86.4% | 74.3%         |
| **LiveCodeBench v6**  | **82.1%**        | —               | —       | —             |
| **MMMU Pro (vision)** | **76.9%**        | 75.1%           | —       | —             |
| **Context**           | 256K             | 256K            | 200K    | 10M           |

Key wins:

* **Best-in-class vision:** Tops MMMU Pro and MATH-Vision among self-hostable models.
* **Unmatched class performance:** Edges out Qwen 3.6 in pure text reasoning and math — undisputed crown in the 30B–35B tier.
* **Elite at scale:** Beats Llama 4 Scout outright across reasoning, math, and vision under Apache 2.0.

***

### How Roru Rouge Compares

Roru Rouge is built to match leading open-weight models on quality and scale, while adding what centrally hosted models cannot offer: uncensored execution, enclave-level privacy, and true ownership.

|                                  | Roru Rouge | Gemma 4 26B | Llama 3.1 70B | Dolphin 2.9 | Gemma 2 27B |
| -------------------------------- | ---------- | ----------- | ------------- | ----------- | ----------- |
| Uncensored intelligence          | ✅          | ❌           | ❌             | ◐           | ❌           |
| You control the usage policy     | ✅          | ❌           | ❌             | ◐           | ❌           |
| Private enclave (TEE) execution  | ✅          | ❌           | ❌             | ❌           | ❌           |
| Prompts never leave your control | ✅          | ❌           | ❌             | ❌           | ❌           |
| You own the weights and keys     | ✅          | ✅           | ◐             | ◐           | ◐           |
| Decentralized inference network  | ✅          | ❌           | ❌             | ❌           | ❌           |
| $RORU-gated API access           | ✅          | ❌           | ❌             | ❌           | ❌           |
| Parameters                       | 32B        | 26B         | 70B           | 8B          | 27B         |
| Context window                   | 256K       | 256K        | 128K          | 8K          | 8K          |
| Open weights                     | ✅          | ✅           | ✅             | ✅           | ✅           |

*✅ full · ◐ partial · ❌ none. Comparison reflects default configurations of publicly available open-weight models; capabilities vary by deployment.*

***

{% hint style="info" %}
*Note:* Roru Rouge runs inside the same hardware-enforced enclave as the rest of Roru AI. Your prompts, context, and outputs stay sealed; only you can read them.
{% endhint %}


---

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