AI Dataset2026
Human-annotated text dataset that labels perceived “AI slop” with a continuous human slop_score (-1 / 0 / +1) plus provenance metadata (source_dataset, source_row_id, content_hash). Collected via Bench Labs SlopFinder from public datasets for training classifiers and studying subjective perception.
AI Model2026
A 29.6B-parameter multimodal causal language model with a dedicated ViT-G/14 perception encoder for running agentic, tool-using, multimodal reasoning locally on consumer hardware. Offers 4-bit quantized weights and a DFlash drafter for speculative decoding to reduce memory and speed up generation.
AI Model2026
A GGUF release of Meta's Muse Glimmer 30B optimized for local multimodal agent inference; includes two quantized text builds, a perception encoder for image input, and an optional DFlash drafter for speculative decoding—fits on 24–32 GB VRAM.
AI Dataset2026
Provides OCR full text for 11.55M public-domain German newspaper pages (1638–1964) with per-page IIIF scans and ALTO XML coordinates; suited for historical NLP, language-model training, and OCR research. Pages carry explicit per-page public-domain licenses.
AI Model2026
Multimodal Mixture-of-Experts text-generation model that accepts text, images, video and audio and returns text; preview open-weight release with 280B total params, 16B activated params, up to 512K token context and BF16/FP8 checkpoints under Apache-2.0.
AI Model2026
Runs a quantized, locally executable 29.6B multimodal causal language model optimized for agentic workflows. Includes a perception encoder for image+text input, 4-bit quantized weights for 24–32GB devices, a DFlash drafter for speculative decoding, and robust tool-call support.
AI Dataset2026
Provides 1,000 five-second video clips generated by MiniMax H3 for lightweight evaluation of multimodal generation and understanding. Clips are roughly 768p base resolution with diverse aspect ratios and themes, produced with a pruned int8 minimax_h3_fl2va checkpoint at 30 steps.
AI Video2026
A LoRA adapter for MiniMax H3 that improves photorealistic rendering of people—preserving skin texture, coherent micro-expressions, film-style lighting and subtle handheld motion. Trigger word: r34l1sm; intended for text-to-video portrait and close-up shots.
Chatbot2026
Provides a drop-in Jinja chat template for Qwen 3.5/3.6/3.8 that reduces reasoning-token waste, enforces a concise terseness system prompt, and preserves in-chat reasoning and tool-call rendering across turns. Terseness is on by default but switchable per request; no model weights are changed.
AI Model2026
Lightweight sparse-MoE LLM (7.9B params, ~1.3B activated per token) designed for hybrid multi-step reasoning and agentic tasks. Uses a KDA–MLA hybrid attention stack and a 128-expert sparse FFN; offered in BF16/FP8/INT4 for local and edge deployment.
AI Model2026
Multimodal vision-language model optimized for on-device image+text tasks: image captioning, full-page OCR with layout annotation, grounding/bounding-box prediction, and function calling. Built on the LFM2.5-2.6B backbone with a SigLIP2 NaFlex 400M vision encoder and tuned for low-latency, low-memory edge inference.
AI Model2026
Open-weight 30B-parameter Mixture-of-Experts LLM with 3B active params, NVFP4-quantized checkpoint, and speculative-decoding support for long-context (up to 1M tokens) agentic, chat, reasoning and tool-calling workloads optimized for NVIDIA GPUs.