Mesh dense baseline: Qwen3-32B weights configured (not trained) by THOX with the Mesh system profile and Knowledge Pack v0.1. 4.87 tok/s shared-host floor, grounding 8/8 (2026-11-01). Apache-2.0.
THOX Mesh routing build, dense flagship, over Qwen3-32B — THOX-configured, not THOX-trained. 5.39 tok/s, 22.61 GB loaded (measured 2026-11-01), grounding 8/8. Apache-2.0.
THOX MeshGroup workgroup build, dense, over Qwen3-32B — THOX-configured, not THOX-trained. 5.36 tok/s, 22.61 GB loaded (measured 2026-11-01), grounding 8/8. Apache-2.0.
Zhi-Create-Qwen3-32B is a fine-tuned model derived from Qwen/Qwen3-32B, with a focus on enhancing creative writing capabilities. Through careful optimization, the model shows promising improvements in creative writing performance, as evaluated using the W
包含2个量化版本GGUF：Qwen3-32B-Q8_0，Qwen3-32B-Q5_K_M
这是unsloth的Q4动态量化版本，精度第一的量化版本！Unsloth Dynamic 2.0 实现了卓越的准确性，并超越了其他领先的量化模型。
Local professional model: THOX configuration (not training) of Qwen3-32B for document analysis and multi-step workflows. Q4_K_M served build. THOX evaluation pending. Apache-2.0.
这是unsloth的Q8动态量化版本，精度第一的量化版本！Unsloth Dynamic 2.0 实现了卓越的准确性，并超越了其他领先的量化模型。
GGUF Ruadapt версии модели Qwen/Qwen3-32B (квантизованная версия Q4_K_M)
pulled as BF16, vocab slice (combined_en_huge) requant to IQ4_NL (combined_en_huge) -- (English + Coding focus) - ~20% faster than Q4_K_M
Qwen3.8-27B in Q4_K_M quantization (32GB+ VRAM required). Dense 27.8B parameters with hybrid attention for long context (256K tokens). Apache 2.0 license. Ideal for high-VRAM setups (RTX 5090/4090 dual, M4 Ultra, etc.).
Recommended for transcribing and summarizing text from screenshots.
Qwen3-30B-A3B-Instruct-2507 has the following features: - Type: Causal Language Models - Training Stage: Pretraining & Post-training - Number of Parameters: 30.5B in total and 3.3B activated - Number of Paramaters (Non-Embedding): 29.9B - Number of Layers
This model is a distilled version of Qwen/Qwen3-30B-A3B-Instruct designed to inherit the reasoning and behavioral characteristics of its much larger teacher model, deepseek-ai/DeepSeek-V3.1.
Qwen2.5 32B uncensored from Karsh-CAI/Qwen2.5-32B-AGI-Q4_K_M-GGUF
This repo contains both the Q4_K_XL version of Qwen3-30B-A3B-Instruct-2507 and Qwen3-30B-A3B-Thinking-2507
Qwen-SEA-LION-v4-32B-IT is a multilingual model which has been pretrained and instruct-tuned for the Southeast Asia region. Developed by AI Singapore and funded by National Research Foundation, Singapore.
Deductive Reasoning Qwen 32B is a reinforcement fine-tune of Qwen 2.5 32B Instruct to solve challenging deduction problems