AI Model2026
An uncensored, "abliterated" fork of Qwen3.8-27B that removes refusal behavior by modifying targeted weights and provides multiple GGUF/BF16 quantized variants for local research and deployment, while carrying significantly reduced safety filtering.
AI Model2026
Provides a quantized MLX conversion of Qwen3.8-27B for Apple Silicon (2/4/6/8-bit) with the model's refusal-direction ablated, preserving multimodal vision+text capability; intended for red‑teaming, interpretability and safety research, not unmoderated production use.
AI Video2026
Upscales Minimax H3 24-channel VAE latents in-place to increase spatial resolution while preserving the time dimension. Replaces the decode→pixel-upscale→encode round-trip with a learned 2D/3D latent upscaler to save compute and avoid interpolation ghosting; supports 1.0–4.0× scaling.
AI Model2026
Injects proprietary news, regulatory and legal data into an open checkpoint via data-centric continual learning to improve performance on legal, tax and journalism tasks while preserving general capabilities and very long context support.
AI Model2026
A 9B open-weight reasoning LLM that uses a self-improvement loop to auto-generate tasks, construct scaffolds, and optimize rollouts for stronger agentic coding and long-context reasoning. Single-GPU deployable, supports tool-calling and a 262,144-token context window.
AI Model2026
Provides an abliterated (refusal-removed) build of Qwen3.8-27B for offline research and red‑teaming, keeping multimodal vision, an MTP speculative head, and a 262,144-token context. It has no built-in safety guardrails and is released under Apache‑2.0 for research use only.
AI Model2026
A 35B mixture-of-experts LLM tuned for agentic coding and end-to-end self-improvement: it jointly generates tasks, scaffolds, and solution rollouts. Activates ~3B params/token, supports 256K context (extendable), and emits chain-of-thought plus OpenAI-style tool calls.
AI Model2026
A draft model that predicts whole blocks of tokens in parallel for speculative decoding of Qwen3.8-27B. Uses block-diffusion drafting with per-position candidate sets and a selector plus dynamic convolutions to keep end-of-block accuracy, increasing accepted tokens per verification and end-to-end throughput versus autoregressive decoding.
AI Model2026
An uncensored, weight-modified variant of Qwen3.8-27B that surgically removes the model's refusal directions to produce 0% refusals while aiming to preserve or improve capability. Uses complementary abliteration blending (SVD + LEACE blend) and ships with recommended greedy inference settings; intended for AI-safety research and red‑teaming, not for causing harm.
AI Audio2026
Zero-shot multilingual text-to-speech checkpoint for speech generation and voice cloning with a compact footprint. Features an ~170M-parameter main model plus a bundled ~120M-parameter codec decoder, with primary support for Chinese and English; other languages show more variable quality and long/noisy references reduce fidelity.
AI Model2026
Provides 2-bit quantized weights of Qwen3.8-27B (~10.15 GB) for local deployment, enabling the full 27B parameter model to run on a single 24 GB GPU with long-context support. Delivered as safetensors plus a companion SGLang runtime; measured to match FP8 reference on common benchmarks with small or no quality loss.
AI Model2026
A 4B-parameter on-device general-purpose LLM for chat, writing, translation, coding and agentic workflows with native 1,000,000-token context. Uses a hybrid attention design to enable long-context efficiency, pretrained on ~20T tokens, and compatible with vLLM, llama.cpp, Ollama and LM Studio.