Provides multiple quantized releases (GGUF, safetensors, MLX) of Qwen-Image-2.1 for local text-to-image generation; includes GPU- and Apple-Silicon–optimized quantizations, companion text encoders/VAEs, and recommended ComfyUI configurations.
Provides a locally deployable, FP4-quantized variant of Qwen3.8-Flash-Next for multimodal (text, image, video) text generation. Uses NVIDIA Model Optimizer with quantization-aware distillation (QAD), a ~96 GiB checkpoint, and is validated on vLLM for Blackwell and DGX Spark.
Text-only sparse Mixture-of-Experts language model for long-context reasoning, coding, and agentic tool use; 501B total / ~23B active parameters, 1M-token context, and BF16/FP8/NVFP4 checkpoints released under Apache 2.0.
Generates calibrated decisions (choice/score/noul) from a prompt and optional images, up to 256 options. Routed MoE experts are quantized to NVIDIA NVFP4 to reduce weights to ~25.6 GB and GPU memory to ~23.3 GiB; provided as a vLLM-compatible System 1 decision model with a /v1/decide endpoint.
A System 1 multimodal decision model that picks among up to 256 options and returns calibrated probabilities for choice, yes/no and 0–5 score decisions from text and images. Fine-tuned on Qwen3.5-35B-A3B, available in bf16 and NVFP4 builds (NVFP4 fits ~23.3 GiB GPU), and served via vLLM's POST /v1/decide API.
Quantized multimodal vision-language model for reasoning, coding, tool use, document and video understanding; 120B total (12B active) with NVFP4 quantization, native Multi-Token Prediction for speculative decoding, and up to 1M-token context — designed for deployment on NVIDIA GPU stacks.
Open-weight 5.6B FLUX.3 image model for text-to-image and multi-reference image editing with pixel-accurate bounding-box layout control. Ships distilled (fast, low-step) and base (fine-tuneable) checkpoints and runs on consumer GPUs down to an RTX 3090.
Runs the FLUX 3 Image Klein single-file checkpoint in ComfyUI for text-to-image generation and instruction-driven image editing with up to ten reference images, bounding-box layout control, and distilled/base variants; requires a prompt upsampler.
Generates text conditioned on multimodal inputs (text, image, audio, video) with a 1M-token context window; an open-weights mixture-of-experts model aimed at long-horizon coding and agentic workflows, with NVFP4 checkpoints to reduce memory footprint.
Provides open-weight, natively multimodal LLM optimized for long-horizon multi-step reasoning and coding/agentic workflows; 816B total / 42B active parameters, 1M-token context window, available as BF16 and NVFP4 checkpoints under the Muse Model License.