AI Model2026
Unified 4B vision-language model for document understanding that converts images or text into template-driven structured JSON or clean Markdown. Key features: multimodal inputs (image+text), template-based extraction, reasoning vs non-reasoning modes, and vLLM/OpenAI-compatible deployment for OCR, invoice/forms extraction, and RAG preprocessing.
AI Model2026
An uncensored, fine-tuned and GGUF-quantized variant of Qwen3.6-27B tailored for long-context, coding, vision and creative-writing use. Offers multiple NEO-CODE Di-Matrix quants (IQ2/IQ4/Q6/Q8), mmproj vision support and recommended inference settings for local servers.
AI Model2026
Draft model for speculative decoding that uses a lightweight block-diffusion drafter to propose multiple tokens in parallel; designed to pair with google/gemma-4-31B-it and accelerate autoregressive text generation (official benchmarks report up to ~5.8× throughput).
AI Model2026
DavidAU/Qwen3.6-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking-NEO-CODE-Di-IMatrix-MAX-GGUF
A 40B GGUF-quantized Qwen3.6 variant fine-tuned with Claude 4.6 Opus and Deckard/Heretic datasets for multimodal image-text-to-text tasks. Offers 256K context, custom NEO-CODE Di-IMatrix quants for long conversations and coding, optimized for local inference and creative/coding use cases; safety alignment removed.
AI Deploy2026
Runs local LLMs on Apple Silicon using native MTP speculative decoding to accelerate token generation while preserving the model's output distribution. Leverages the model's own MTP heads with batched verification and exact rejection sampling; ships with a Mac app, CLI, local OpenAI/Anthropic-compatible server, auto-tune, and Forge for building/verifying MTP adapters.
AI Model2026
Generates uncensored videos from text and images using an LTX 2.3–based diffusion model with native t2v and i2v support; ships with a prompt enhancer and developer-focused gguf/bf16 dev releases for local experimentation.
AI Model2026
Mixture-of-Experts LLM tuned for mathematical and coding reasoning, with ~760M active / 8.4B total parameters and post-training for improved stepwise reasoning. Optimized for inference efficiency (vLLM/transformers forks) so it can run in computation-constrained or local deployments; Apache-2.0 licensed.
AI Infra2026
Defines OpenTelemetry semantic conventions for generative AI telemetry — spans, metrics, and events for GenAI clients, the Model Context Protocol (MCP), and provider-specific integrations. Includes YAML models, human-readable docs, and reference implementations to standardize observability across GenAI deployments.
AI Infra2026
Native local inference engine for DeepSeek V4 Flash (also supports GLM 5.2 and PRO on high‑memory machines). Focused features include model-specific loading, SSD expert streaming, asymmetric routed-expert 2-bit quant support, multi-GPU/tensor/pipeline parallelism, and an OpenAI-compatible server plus a native coding agent.
AI Model2026
Merges Unsloth UD XL quantized GGUF of Qwen3.6-27B with compact Q8_0 MTP heads to enable multi-token (speculative) decoding on llama.cpp builds that support MTP; aimed at image-text-to-text usage with reduced MTP overhead.
AI Infra2026
High-throughput LLM inference engine for agentic workloads, combining a local‑SPMD static compiler for parallelism, a C++ scheduler with a Python execution plane and type‑safe KV‑cache reuse, pluggable high-performance kernels (including an MLA implementation), and a low‑overhead AsyncLLM entrypoint for production GPU inference.
AI Audio2026
Converts text into natural-sounding speech locally using compact ONNX TTS assets. Optimized for CPU/edge inference (~99M params) with support for 31 languages, expression tags (e.g., <laugh>), and improved stability versus Supertonic 2 — suitable for on-device multilingual TTS.