Discover the Best AI Resources
Curated essentials, no noise — just what matters
AI Model2026
Instruction-tuned 13B LLM post-trained on 260B tokens of pre-1931 English and finetuned with online DPO (LLM-as-judge) to improve instruction-following; suited for period-style English generation and etiquette/letter-writing formats, but not optimized for contemporary factual updates.
AI Model2026
Unified multimodal LLM for enterprise workflows: ingests video, audio, image and text to perform transcription, OCR, Q&A, summarization and long-context reasoning. Provides BF16/FP8/NVFP4 weights and integrations with vLLM, TensorRT-LLM and other runtimes.
AI Model2026
An HDR LoRA fine-tune for Lightricks' LTX-2.3 (22B) that enables image‑conditioned any‑to‑any image-to-video and text-to-video generation. Designed for HDR-aware synthesis workflows; requires the LTX-2.3 base model and a LoRA-capable runtime.
AI Model2026
Produces 384‑dim multilingual (and code) embeddings with up to 32,768 token context, optimized for low‑latency production retrieval. Compact 97M model with ONNX/OpenVINO and vLLM/GGUF deployment options for edge and high‑throughput use.
AI Model2026
A 27B multimodal causal language model with a vision encoder and native long-context support (262,144 tokens). Optimized for repository-level coding agents and multimodal understanding; includes preserved "thinking" traces, multi-token prediction (MTP), and deployment recipes for vLLM / SGLang / Transformers.
AI Model2026
FP8-quantized 27B multimodal Qwen3.6 model weights in Hugging Face Transformers format — supports image/text/video inputs, native 262k token context (extensible to ~1M), and is compatible with vLLM/SGLang/KTransformers for efficient local serving and research.
AI Dataset2026
Benchmark dataset for evaluating clinician-facing chat assistants: physician-authored conversations plus rubric items, use-case and difficulty labels, specialty metadata, and a built-in canary to reduce benchmark contamination. Hosted on Hugging Face under an MIT license.
AI Dataset2026
Provides a large-scale multimodal embodied dataset (vision, depth, hand/arm kinematics, tactile) captured with an exoskeleton glove and egocentric sensors; organized as clip-level Zarr volumes for manipulation, imitation learning, and vision–action research. Includes both high-precision glove measurements and natural bare-hand clips; sizable storage required.
AI API2026
Provides a single OpenAI-compatible /v1 API that aggregates the free tiers of 16 LLM providers into one unified endpoint. Features smart routing and automatic failover, per-key free-tier tracking, encrypted key storage, embeddings/media routing, and a Docker one-liner for local use.
AI Client2026
Terminal-first developer workspace with an agentic AI side-panel that runs against your API keys or local models. Bundles a native PTY terminal, CodeMirror editor with AI edit diffs, file explorer, git history/graph, and a web preview in a ~7–8MB desktop app with no telemetry.
AI Model2026
A 284B-parameter Mixture-of-Experts LLM with only 13B activated parameters, designed for 1,000,000-token contexts. Uses hybrid compressed attention and mixed FP4/FP8 precision to reduce long-context KV-cache and per-token FLOPs; aimed at long-document QA, RAG pipelines, and local/high-capacity inference.
AI Model2026
Provides a locally runnable, refusal-free variant of Qwen3.6-27B with multiple K_P GGUF quantizations and mmproj multimodal support. The Aggressive flavor skips preambles on edgy prompts—use when you want direct/raw responses for local research, red‑teaming, or offline workflows.