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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
17.1K Pulls 1 Tag Updated 11 months ago
Unsloth Dynamic 2.0 Quants achieves 1M tokens & superior accuracy & SOTA quantization performance. Select UD-IQ3_XXS for 16GB VRAM, UD-Q4_K_XL for 24GB VRAM, or UD-Q5_K_XL/UD-Q6_K_XL for 32GB VRAM.
10.6K Pulls 5 Tags Updated 10 months ago
Qwen3-Coder-30B-A3B-Instruct-GGUF from: https://huggingface.co/unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF
6,415 Pulls 1 Tag Updated 6 months ago
QwenLong-L1.5, a long-context reasoning model built upon Qwen3-30B-A3B-Thinking, augmented with memory mechanisms to process tasks far beyond its physical context window.
2,526 Pulls 8 Tags Updated 6 months ago
Qwen3-Coder is available in multiple sizes. Today, we’re excited to introduce Qwen3-Coder-30B-A3B-Instruct. This streamlined model maintains impressive performance and efficiency ........
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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.
2,065 Pulls 2 Tags Updated 10 months ago
Unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF with defaults to consume roughly 32 GB of VRAM
1,896 Pulls 3 Tags Updated 9 months ago
Qwen3-Coder is a highly capable coding assistant, based on Qwen3-Coder-30B-A3B-Instruct. She is designed for local development and agentic coding workflows
1,611 Pulls 1 Tag Updated 9 months ago
This repo contains both the Q4_K_XL version of Qwen3-30B-A3B-Instruct-2507 and Qwen3-30B-A3B-Thinking-2507
1,030 Pulls 3 Tags Updated 11 months ago
Unsloth Dynamic 2.0 Quants achieves superior accuracy & SOTA quantization performance. UD-Q4_K_XL provided.
988 Pulls 2 Tags Updated 11 months ago
model Qwen3-Coder-30B-A3B-Instruct-Q5_K_M
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Qwen3-30B-A3B-Instruct-2507,Q8_0
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