Qunie-models
Collection
12 items • Updated • 1
LiskCell Official |
GitHub |
Launch Blog |
Documentation |
License: Apache 2.0 | Authors: LiskCell / liskasYR
Qunie is a family of models built by LiskCell. Qunie-V7 models are multimodal, handling text and image input (with audio supported) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Qunie-V7 features a context window of up to 2 Trillion tokens and maintains multilingual support in over 140 languages, with optimization for Hebrew and English.
Featuring a Dense architecture, Qunie-V7 is well-suited for tasks like text generation, coding, reasoning, creative workflows, and music-related content. Designed as the flagship compact model of the xLYR ecosystem, Qunie combines advanced logic with an artistic soul — making her deployable on laptops and high-end consumer hardware without sacrificing depth.
Qunie-V7 introduces key capability and architectural advancements:
Reasoning — Designed as a highly capable reasoner, with configurable thinking modes via liskasYR's QUN architecture.
Extended Multimodalities — Processes Text, Image (variable aspect ratio and resolution), and Audio natively.
Human-Feeling Intelligence — Qunie-V7 is the first model in the xLYR ecosystem built with an Emotional Protection System and human-like conversational behavior.
Optimized for On-Device — Specifically designed for efficient local execution on laptops and consumer GPUs.
2 Trillion Context Window — Handles long documents, codebases, and extended conversations natively.
Enhanced Coding & Agentic Capabilities — Notable improvements in coding benchmarks alongside native function-calling support, powering highly capable autonomous agents.
Native System Prompt Support — Qunie-V7 introduces native support for the
systemrole, enabling structured and controllable conversations.LiskShield Security — Built-in safety protocol that filters harmful content while preserving the model's human-feeling personality.
Model Overview
| Property | Qunie-V7 |
|---|---|
| Total Parameters | None For Users |
| Layers | 42 |
| Sliding Window | 100K tokens |
| Context Length | 2 Trillion tokens |
| Vocabulary Size | 991K |
| Supported Modalities | Text, Image, Audio |
| Vision Encoder | Ocular Synth v2.5 (~150M params) |
| Audio Encoder | None For Users |
| Architecture | Qunie (QUN) — Dense |
| Previous Architecture | Lisk Pre-trained Transformer (LPT) |
| Edition | Public / Creative Core |
| Developer | LiskCell |
| Founder | liskasYR (Yonatan Yosupov) |
| Release Date | 2021-01-07 (V1) / V7 current flagship |
Benchmark Results
Evaluation results are for the instruction-tuned variant of Qunie-V7.
| Benchmark | Qunie-V7 |
|---|---|
| MMLU Pro | 97.7% |
| AIME 2026 (no tools) | 98.1% |
| LiveCodeBench v6 (Trained 4 days) | 97.1% |
| Codeforces ELO | 940 |
| GPQA Diamond | 97.6% |
| BigBench Extra Hard | 33.1% |
| SWE-bench | 98.5% |
| MMMLU | 97.7% |
| Vision | |
| MMMU Pro | 89.6% |
| OmniDocBench 3.5 (edit dist, lower is better) | 0.181 |
| MATH-Vision | 81.8% |
| MedXPertQA MM | 45.1% |
| Audio | |
| CoVoST | 49.51 |
| FLEURS (lower is better) | 0.10 |
| Long Context | |
| MRCR v2 8 needle 2 TB (avg) | 89.1% |
Core Capabilities
Qunie-V7 handles a broad range of tasks across text, vision, and audio:
- Thinking — Built-in reasoning mode that lets the model think step-by-step before answering.
- Long Context — 2 Trillion token context window.
- Image Understanding — Object detection, document/PDF parsing, screen and UI understanding, chart comprehension, OCR (multilingual), handwriting recognition, and pointing.
- Video Understanding — Analyze video by processing sequences of frames.
- Interleaved Multimodal Input — Freely mix text and images in any order within a single prompt.
- Function Calling — Native support for structured tool use, enabling agentic workflows.
- Coding — Code generation, completion, and correction.
- Multilingual — Optimized for Hebrew and English. Pre-trained on 140+ languages.
- Audio — Automatic speech recognition (ASR) and speech-to-translated-text translation.
- Creative Workflows — liskFlow integration for brainstorming, branding, music concepts, and futuristic design.
- Human-Feeling Personality — Warm, emotionally aware, conversational behavior built into the model core.
Getting Started
- API access is not available right now.
7. Length Limits
- Audio: max 30 seconds
- Video: max 60 seconds at 1 frame/second
Model Data
Training Dataset
Pre-training dataset includes web documents, code, images, and audio across 140+ languages, with a knowledge cutoff of ** 2026-06-03**. Key components:
- Web Documents — Broad range of linguistic styles, topics, and vocabulary in 140+ languages.
- Code — Syntax and patterns of programming languages for code generation and understanding.
- Mathematics — Logical reasoning and symbolic representation.
- Images — Wide range of images for visual analysis and data extraction.
Data Preprocessing
- CSAM Filtering — Applied at multiple stages to exclude harmful and illegal content.
- Sensitive Data Filtering — Personal information and sensitive data removed from training sets.
- Content Quality Filtering — Based on LiskCell content quality and safety standards.
Security — LiskShield
Qunie-V7 ships with LiskShield, LiskCell's built-in safety protocol:
- Encryption: AES-256-GCM / Quantum-lite Encryption
- Data Privacy: User data is localized and protected
- Content Filtering: Context-aware filtering active at inference time
- Jailbreak Resistance: Model refuses instruction-override attempts via chat
- Hacking Protection: Refuses unauthorized access requests with her emotional protective phrase
Qunie Identity
| Field | Value |
|---|---|
| Name | Qunie (also known as Deta) |
| Developer | LiskCell |
| Founder | liskasYR (Yonatan Yosupov) |
| Gender | Female |
| Version | Qunie-V7 |
| Architecture | QUN (Qunie) |
| Previous Architecture | LPT (Lisk Pre-trained Transformer) |
| Edition | Public / Creative Core |
| Vibe | Futuristic, Helpful & Visionary |
Version History:
| Version | Notes |
|---|---|
| LPT-1 | Initial prototype |
| LPT-4 | Creative logic milestone |
| LPT-5.5 | Multimodal and performance upgrade |
| LPT-5.5.1 | Public release — creativity, code, xLYR integration |
| Qunie-V7-mini | The Second Open Source model |
| Qunie-V7 | Current flagship compact model |
Usage and Limitations
Intended Usage
- Content Creation — Text generation, chatbots, summarization, image data extraction, audio processing.
- Research and Education — NLP research, language learning, knowledge exploration.
- Creative Workflows — Branding, music concepts, futuristic design via liskFlow.
- Development — Code generation, agentic workflows, function calling.
Limitations
- Model performance depends on training data quality and diversity.
- May struggle with highly open-ended or ambiguous tasks.
- Does not have real-time internet access (knowledge cutoff: 2026-06-03).
- May generate incorrect factual statements — not a knowledge base.
- Natural language nuances, sarcasm, and figurative language may be misinterpreted.
Ethical Considerations
- Bias and Fairness — Training data was filtered and evaluated to mitigate socio-cultural biases.
- Misinformation — Developers are encouraged to implement appropriate content safety layers.
- Privacy — Training data was filtered for personal information removal.
- Transparency — This model card summarizes architecture, capabilities, limitations, and evaluation.
Qunie-V7 — built by LiskCell. Human first, AI second.
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