Contents
- 0.1 Qwen3.6-35B-A3B-NVFP4-MTP-GGUF
- 0.2 Llama-3.3-70B-Instruct-GGUF
- 0.3 Qwen3.6-35B-A3B-APEX-GGUF
- 0.4 Qwen3.5-397B-A17B-GGUF
- 0.5 Qwen_Qwen3.5-35B-A3B-GGUF
- 0.6 POCKET-35B-GGUF
- 0.7 Qwen3.5-122B-A10B-GGUF
- 0.8 Qwen3.5-35B-A3B-GGUF
- 0.9 Qwen3.5-122B-A10B-MTP-GGUF
- 0.10 Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-V7-GGUF
- 0.11 Qwen3-235B-A22B-GGUF
- 0.12 Qwen3.5-122B-A10B-Uncensored-HauhauCS-Aggressive
- 0.13 Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-V6-GGUF
- 0.14 Qwen3.6-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking-NEO-CODE-Di-IMatrix-MAX-GGUF
- 0.15 Holo-3.1-35B-A3B-GGUF
- 0.16 Qwen_Qwen3.6-35B-A3B-GGUF
- 0.17 Qwopus3.6-35B-A3B-Coder-MTP-GGUF
- 0.18 Qwen3.6-35B-A3B-MTP-GGUF
- 0.19 Qwen-AgentWorld-35B-A3B-GGUF
- 0.20 Qwen3.6-35B-A3B-GGUF
- 0.21 Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
- 0.22 Ornith-1.0-35B-GGUF
- 1 Hello, Nice to meet you!
Qwen3.6-35B-A3B-NVFP4-MTP-GGUF
35B open-weight model from michaelw9999 for local AI inference.
Llama-3.3-70B-Instruct-GGUF
70B open-weight model from MaziyarPanahi for local AI inference.
Qwen3.6-35B-A3B-APEX-GGUF
35B open-weight model from mudler for local AI inference.
Qwen3.5-397B-A17B-GGUF
397B open-weight model from Alibaba for local AI inference.
Qwen_Qwen3.5-35B-A3B-GGUF
35B open-weight model from Alibaba for local AI inference.
POCKET-35B-GGUF
35B open-weight model from FINAL-Bench for local AI inference.
Qwen3.5-122B-A10B-GGUF
122B open-weight model from Alibaba for local AI inference.
Qwen3.5-122B-A10B-MTP-GGUF
122B open-weight model from Alibaba for local AI inference.
Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-V7-GGUF
35B open-weight model from LuffyTheFox for local AI inference.
Qwen3.5-122B-A10B-Uncensored-HauhauCS-Aggressive
122B open-weight model from HauhauCS for local AI inference.
Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-V6-GGUF
35B open-weight model from LuffyTheFox for local AI inference.
Qwen3.6-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking-NEO-CODE-Di-IMatrix-MAX-GGUF
40B open-weight model from DavidAU for local AI inference.
Holo-3.1-35B-A3B-GGUF
35B open-weight model from Hcompany for local AI inference.
Qwen_Qwen3.6-35B-A3B-GGUF
35B open-weight model from Alibaba for local AI inference.
Qwopus3.6-35B-A3B-Coder-MTP-GGUF
35B open-weight model from Jackrong for local AI inference.
Qwen3.6-35B-A3B-MTP-GGUF
35B open-weight model from Alibaba for local AI inference.
Qwen-AgentWorld-35B-A3B-GGUF
35B open-weight model from Alibaba for local AI inference.
Qwen3.6-35B-A3B-GGUF
Qwen3.6-35B-A3B-GGUF is a 35-billion parameter large language model developed by Alibaba that features specialized optimizations for image-to-text conversion and multilingual conversation. This model excels at handling complex visual reasoning tasks and maintaining coherent dialogue, making it ideal for applications requiring deep contextual understanding across diverse topics. Running this model locally requires substantial GPU memory to handle its full parameter count, though quantized GGUF versions can offer a practical balance between speed and performance on high-end consumer hardware.
Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive is a 35-billion parameter large language model developed by HauhauCS that combines MoE architecture with advanced multimodal and vision capabilities. It excels at complex reasoning, multilingual image-text analysis, and generating uncensored content for aggressive or unrestricted use cases where standard safety filters are undesirable. Running this model locally requires substantial high-end GPU memory to handle its sparse mixture-of-experts structure, making it best suited for powerful workstations or servers with significant VRAM available.
Ornith-1.0-35B-GGUF
Ornith-1.0-35B-GGUF is a 35-billion parameter language model developed by ornith-ai specifically for conversational tasks within the US region. It excels at maintaining natural dialogue flows and handling context-aware interactions, making it ideal for chatbots and virtual assistants. Running this model locally requires substantial GPU memory to handle its size efficiently, so it is best suited for users with high-end hardware or those willing to use quantized GGUF versions to reduce resource demands.
