GGUF
conversational
How to use from
Unsloth Studio
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for terasut/typhoon2.5-qwen3-30b-a3b-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for terasut/typhoon2.5-qwen3-30b-a3b-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for terasut/typhoon2.5-qwen3-30b-a3b-GGUF to start chatting
Quick Links

Typhoon2.5-Qwen3-30B-A3B (GGUF)

GGUF-format conversions of the scb10x/typhoon2.5-qwen3-30b-a3b model for efficient inference with llama.cpp and compatible runtimes.

Converted using llama.cpp’s convert_hf_to_gguf.py and quantize tool. No additional training or fine-tuning was performed.


🧩 Variants

Variant File size
BF16 61.1 GB
F16 61.1 GB
Q8_0 32.5 GB
Q_K_M 18.6 GB

πŸ“ Notes

  • Source model: scb10x/typhoon2.5-qwen3-30b-a3b
  • Tokenizer and metadata preserved during conversion
  • Choose BF16 for best fidelity, F16 for GPU does not support BF16, Q8_0 for balance, Q4_K_M for lowest memory

βš–οΈ License

Weights inherit the upstream model’s license.
This repository redistributes format-converted copies only.
Please review and comply with the upstream terms before use.


πŸ“ Acknowledgments

Original model by SCB10X.
GGUF conversion with quantization performed via llama.cpp tooling.

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GGUF
Model size
31B params
Architecture
qwen3moe
Hardware compatibility
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