AI Model2026
A non-autoregressive, multilingual System‑1 decision model that answers typed questions (choice/score/noul) over text or JSON in a single forward pass with probability distributions. Key differences: calibrated-probability design, sub-35ms GPU latency, and built-in multilingual routing; requires per-workflow recalibration and validation on long or low-resource languages.
AI Model2026
Converts multimodal inputs (text, image, audio, video) plus a question and options into calibrated probability distributions over choices. Built on Gemma 4 12B with a 30,000-question fine-tune, optimized for per-question decision classification and low-latency inference (Apache-2.0).
AI Image2026
Provides GGUF-quantized builds of Qwen-Image-2.1 for local text-to-image generation and ComfyUI workflows; includes multiple quantizations (Q4_K_M recommended), companion text encoders (BF16/Int8) and a VAE, and ships without a built-in safety filter.
AI Model2026
Generates a single, ready-to-send short message (email, text, or note) tuned to sound human; a 27B fine-tuned LLM with open Apache-2.0 weights, optimized to return one concise draft rather than multiple options or explanatory preamble.
AI Model2026
Provides quantized Qwen-Image-2.1-Turbo weights for text-to-image generation across GGUF, Safetensors, and MLX formats. It retains the model’s 8-step Turbo workflow, with options for different hardware and runtimes.
AI Model2026
GGUF-format, quantized (Q4_K_M) and refusal-ablated (Heretic) text encoder build for Qwen-Image-2.1, supplied with a separate f16 vision mmproj so the full multimodal pipeline runs on llama.cpp/ComfyUI (Mac/non-CUDA friendly); multiple formats and quantizations included.
AI Image2026
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.
AI Model2026
A sparse-MoE multimodal LLM fine-tuned with large-scale mixed reinforcement learning, supporting text/image/video/audio and a 1M-token context window; designed for long-horizon agentic tasks, coding and visual reasoning with groupwise grading and on-policy distillation.
AI Audio2026
Performs low-latency streaming speech-to-text, emitting one token per selectable 80/120/160 ms clock with configurable transcription delay and a 30s rolling KV cache for unlimited 24/7 transcription. Bilingual (zh/en) and includes semantic VAD.
AI Model2026
Scans long documents rendered as compressed page-images, locates relevant pages, and selectively expands only those pages to full text for question answering; built on Qwen3.5-9B, supports 5x/10x/15x compression and is released under Apple’s research-only model license.
AI Model2026
Open-weights multimodal LLM checkpoint designed for 1M-token long-context agent runs that combines large-scale on-policy RL with groupwise grading for iterative self-improvement. Key traits: sparse MoE backbone (≈1.02T total / 42B active), text-only output with image/video/audio inputs, MIT-licensed weights on HuggingFace—suited for long-horizon agents and research at significant infra cost.
AI Model2026
A 9B agentic multimodal SFT checkpoint distilled from Qwen3.5-9B for coding, general agent tasks, visual coding and cybersecurity. Provided by Xiaomi MiMo as a research seed (77.4B-token SFT mix) to bootstrap agentic RL and tool-use experiments.