Tag

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.

AiSOC

Ingests and normalizes security telemetry, runs multi-model AI agents to produce replayable investigations and automated triage/response; key features include a step-by-step Investigation Ledger, CI-gated eval harness, and self-hostable deployments.

MolDeTox

Benchmarks LLM and VLM capabilities for toxicity-aware molecular editing using toxicity‑cliff molecule pairs. It provides QA-formatted tasks and CSV splits for fragment identification, non-toxic fragment generation, and detoxified molecule generation—useful for safety evaluation and drug-discovery research.

ZAYA1-8B

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.

havenoammo/Qwen3.6-27B-MTP-UD-GGUF

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.

TokenSpeed

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.

Command A+ (command-a-plus-05-2026-bf16)

Processes text and images to produce conversational, reasoning-focused multilingual outputs for agentic workflows. Built as a sparse MoE decoder (25B active / 218B total parameters) with 128K context and available in BF16/FP8/W4A4 quantizations to balance quality and deployability.

Hy-MT2-30B-A3B

A 30B mixture-of-experts multilingual translation model supporting 33 languages and instruction-following translation. Offers MoE architecture, fast-thinking mode, and quantized/deployment-ready variants for production translation and subtitle tasks.

Tencent Hy-MT2-1.8B

A family of multilingual translation models optimized for real-world, instruction-following translation across 33 languages. The 1.8B model targets on-device use with extreme quantization (≈440 MB via AngelSlim), while 7B/30B variants trade size for higher accuracy.

Hy-MT2-7B

7B multilingual translation model optimized for instruction-following and low-latency deployment across 33 languages; provides quantized/FP8/GGUF builds and integrations (vLLM, llama.cpp) for server and on-device inference.

unsloth/Qwen3.6-27B-MTP-GGUF

Provides a quantized GGUF build of Qwen3.6‑27B with MTP (multi‑token prediction) support for faster local inference. Packaged for GGUF-compatible runners (llama.cpp) and Hugging Face/transformers workflows, with deployment notes for CPU/GPU and vLLM/SGLang integration.

Qwen3.6-35B-A3B-MTP-GGUF (unsloth)

A GGUF-quantized build of Qwen3.6-35B packaged by unsloth for local and accelerated inference. Adds MTP speculative decoding guidance and deployment notes for llama.cpp, vLLM, SGLang and long-context/multimodal use cases.