AI Model2026
Unifies multimodal image understanding, text-to-image generation, and instruction-based editing in a single diffusion LLM using a Mixture-of-Experts backbone, SigLIP-VQ discrete tokenizer, and a distilled diffusion decoder enabling fast (8-step) decoding; full-generation needs ~47GB GPU RAM.
AI Model2026
A 14B dense tri‑mode language model that supports autoregressive, diffusion‑based parallel decoding, and self‑speculation—designed to increase token throughput and acceptance length; best suited for researchers and engineers exploring decode‑efficiency tradeoffs on NVIDIA hardware under the Nemotron Open Model License.
AI Dataset2026
Provides 150,000 synthetic Vietnamese patient personas to condition clinical text generation. Each persona bundles demographics, socioeconomic context, health and behavior fields, and prompt-ready narratives; intended for research and simulation, not clinical decision-making.
Chatbot2026
Drop-in Jinja chat templates for Qwen 3.5/3.6 that fix rendering errors, token waste, and tool-calling failures across runtimes (LM Studio, llama.cpp, vLLM, MLX). Adds a think-on/think-off toggle, auto-closes broken thinking tags, robust tool-argument handling, and a graceful fallback for missing user queries.
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
A Qwen-3.6 27B model variant optimized for DFlash (speculative decoding) to reduce generation latency and increase throughput. Focuses on faster inference on serving stacks and is suitable for text-generation endpoints where lower latency and resource efficiency matter.
AI Dataset2026
Provides a 30K+ problem multimodal, multilingual dataset of Olympiad-level math problems with expert solutions and a math-aware retrieval benchmark—includes images, hierarchical topics, provenance from official booklets, and LLM-assisted metadata (v0, CC BY 4.0).
AI Model2026
A GGUF-format preview checkpoint derived from Qwen3.6-27B — a multimodal, image-text-to-text reasoning model fine-tuned for more structured reasoning and consistent answer style; packaged for local inference and compatible with engines like vLLM/SGLang/llama.cpp.
AI Model2026
A 33B Mixture-of-Experts text-to-text model optimized for local, long-context agentic coding—3B activated params per token, 131k token window, mixed sliding-window and global attention, FP8 KV cache, Apache-2.0 license.
AI Model2026
Provides a lightweight assistant (draft) model for Gemma 4 E4B used in speculative-decoding pipelines — it predicts token drafts that the target model verifies in parallel, enabling up to ~2× decoding speedups while preserving identical final outputs. Useful for low-latency, multimodal assistant and on-device scenarios.
AI Model2026
A lightweight 'drafter' assistant for Gemma 4 31B that generates speculative token drafts to enable up-to-2× decoding speedups while preserving final output quality; compatible with Hugging Face Transformers and any-to-any pipelines.
AI Model2026
Acts as the assistant (drafter) checkpoint for Gemma 4 26B A4B on Hugging Face, used in Speculative Decoding to pre-draft tokens and speed up generation. Designed for long-context, multimodal workflows where lower latency and on-device or edge inference matter.