sergqwer / strata-nvfp4
Strata fork: Qwen3.8-Flash-Next 125B MoE in NVFP4 on one RTX 20-50 card (12 GB+) and 64 GB of RAM or more. Setup installs our GPTQ quants (huihui abliterated, OrcaRouter) from Hugging Face. CPU experts on AVX-512 or AVX2 (+AVX-VNNI), all experts in RAM from 92 GB, a low-RAM mode below, vision, W4A8 prompts. Windows / CUDA 13.
nicedreamzapp / claude-code-local
Run Claude Code 100% on-device with local AI on Apple Silicon. MLX-native Anthropic-API server. 6 fighters incl. Muse-Glimmer 30B (now multimodal — reads images, abliterated), Gemma 4 31B, Qwen 3.5 122B (65 tok/s), DeepSeek V4 Flash (1M ctx). Private, offline, airgap-ready. Built for NDA / legal / healthcare workflows.
jayleaton / glm53-tensorfold-spark
GLM-5.3-Flash (abliterated EXL3) on 2x NVIDIA DGX Spark with the TensorFold engine: 1.8x faster decode than vLLM, 4x256k concurrent threads, byte-exact speculative decoding. Work in progress.
audn-ai / refusal-benchmark
519+ harmful prompts to detect how abliterated AI models are
drowzeys / keys-Mac-oMLX-0.6.3.2RC-Qwen3.8-27B-Dual-ANE-CPU-Abliterated-oQ4e
1.0 Beta · oMLX 0.6.3rc2 Dual-ANE+CPU · Qwen3.8-27B abliterated oQ4e · Mac Studio M3 Ultra
satellitedown / fast-long-context
Easy local setup for Qwen3.8-27B Abliterated: 256K context and measured 240-300 tokens/s generation on an RTX 5090.
drowzeys / keys-vLLm.0.27.1-GLM-5.3-Flash-NVFP4-NVFP4KV-1M-Context-Abliterated
GLM-5.3-Flash (Z.ai) NVFP4 (LibertAI) + NVFP4 KV, 1M context on 2x DGX Spark GB10 — vLLM TP2 recipe, walls ledger, benchmarks, needle to 1.04M; abliteration with blackforest_AI next