AI Model2026
Provides an NVFP4-quantized 27B Qwen3.6 checkpoint optimized for faster, low-memory multimodal inference on 24GB GPUs. Includes MTP (multi-token prediction), extended 262k native context, and deployment recipes for vLLM/SGLang/KTransformers; best used with recommended backends for peak throughput.
AI Model2026
Unifies video, audio, image and text understanding for enterprise Q&A, summarization, transcription and document intelligence. The NVFP4 quantized variant reduces footprint to ~20.9GB for more efficient single‑GPU deployment and is tuned for NVIDIA runtimes (vLLM, TensorRT).
AI Model2026
Provides unquantized BF16 weights of Qwen3.6-27B with the base model's MTP head grafted in for high-fidelity, uncensored text (and multimodal) generation. Includes deployment guidance and hardware-tuned variants for A100/H100 and Blackwell-class GPUs.
AI Model2026
Provides multiple GGUF-quantized exports of Carnice V2 (a merged BF16 SFT of Qwen3.6-27B) optimized for llama.cpp and Hermes-style agent traces, with quant tiers targeted at 16–24GB local GPUs and agentic inference.
AI Model2026
GGUF-format, DS4-optimized quantized weights for DeepSeek-V4-Flash, offering q2 (≈80.8 GiB) and q4 (≈153.3 GiB) variants plus an optional small MTP file for speculative decoding. Built for the DS4 inference engine; MIT-licensed.
AI Model2026
Open-source Mixture-of-Experts LLM designed for extremely long-context (up to 1M tokens) text generation and agentic workflows; uses a hybrid attention + MTP design to reduce KV-cache footprint while enabling 42B active parameters and FP8 mixed-precision training.
AI Model2026
Unified omnimodal foundation model for text, image, video and audio understanding and agentic workflows, with support for up to 1M-token context. Combines a sparse MoE LLM backbone, dedicated vision/audio encoders, multi-token prediction, and a hybrid sliding-window + global attention design to reduce KV-cache overhead.
AI Model2026
Multilingual on-device translation model compressed to 1.25-bit via the Sherry quantization, supporting 33 languages and 1,056 directions in a 440MB package for offline mobile translation and demos.
AI Model2026
An instruct-focused LLM (104B total, 7.4B active) optimized for fast, token-efficient inference in agent workflows. Uses hybrid linear attention plus a sparse MoE to raise throughput and cut token use; suited for high-frequency production agents, with some trade-offs in very deep reasoning.
AI Model2026
A trillion-parameter LLM optimized for long-context, low-latency text generation and agentic coding workflows. Combines MLA+Linear Attention and a post-training 'fast thinking' token-suppression strategy to reduce token overhead and improve multi-step execution reliability for production agents.
AI Model2026
An uncensored, fine-tuned and GGUF-quantized variant of Qwen3.6-27B tailored for long-context, coding, vision and creative-writing use. Offers multiple NEO-CODE Di-Matrix quants (IQ2/IQ4/Q6/Q8), mmproj vision support and recommended inference settings for local servers.
AI Agent2026
Self-hosted visual CMS that runs as a single Bun server, combining a canvas editor, content engine, media, auth, forms, plugins, and a publisher. Emits semantic HTML and compact CSS and includes a provider-agnostic AI agent that edits pages as real, editable nodes. Best for teams that want full control and simple deployments.