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chore(model gallery): add qwen3-32b (#5270)

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Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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Ettore Di Giacinto 2025-04-29 09:48:28 +02:00 committed by GitHub
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gallery/index.yaml
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@ -44,6 +44,38 @@
- filename: Qwen_Qwen3-30B-A3B-Q4_K_M.gguf
sha256: a015794bfb1d69cb03dbb86b185fb2b9b339f757df5f8f9dd9ebdab8f6ed5d32
uri: huggingface://bartowski/Qwen_Qwen3-30B-A3B-GGUF/Qwen_Qwen3-30B-A3B-Q4_K_M.gguf
- !!merge <<: *qwen3
name: "qwen3-32b"
urls:
- https://huggingface.co/Qwen/Qwen3-32B
- https://huggingface.co/bartowski/Qwen_Qwen3-32B-GGUF
description: |
Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancements in reasoning, instruction-following, agent capabilities, and multilingual support, with the following key features:
Uniquely support of seamless switching between thinking mode (for complex logical reasoning, math, and coding) and non-thinking mode (for efficient, general-purpose dialogue) within single model, ensuring optimal performance across various scenarios.
Significantly enhancement in its reasoning capabilities, surpassing previous QwQ (in thinking mode) and Qwen2.5 instruct models (in non-thinking mode) on mathematics, code generation, and commonsense logical reasoning.
Superior human preference alignment, excelling in creative writing, role-playing, multi-turn dialogues, and instruction following, to deliver a more natural, engaging, and immersive conversational experience.
Expertise in agent capabilities, enabling precise integration with external tools in both thinking and unthinking modes and achieving leading performance among open-source models in complex agent-based tasks.
Support of 100+ languages and dialects with strong capabilities for multilingual instruction following and translation.
Qwen3-32B has the following features:
Type: Causal Language Models
Training Stage: Pretraining & Post-training
Number of Parameters: 32.8B
Number of Paramaters (Non-Embedding): 31.2B
Number of Layers: 64
Number of Attention Heads (GQA): 64 for Q and 8 for KV
Context Length: 32,768 natively and 131,072 tokens with YaRN.
For more details, including benchmark evaluation, hardware requirements, and inference performance, please refer to our blog, GitHub, and Documentation.
overrides:
parameters:
model: Qwen_Qwen3-32B-Q4_K_M.gguf
files:
- filename: Qwen_Qwen3-32B-Q4_K_M.gguf
sha256: e41ec56ddd376963a116da97506fadfccb50fb402bb6f3cb4be0bc179a582bd6
uri: huggingface://bartowski/Qwen_Qwen3-32B-GGUF/Qwen_Qwen3-32B-Q4_K_M.gguf
- &gemma3
url: "github:mudler/LocalAI/gallery/gemma.yaml@master"
name: "gemma-3-27b-it"