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KordAI/Typhoon-Gemma3-KordTranslate-EN-TH-4B-GGUF
Typhoon-Gemma3-KordTranslate-EN-TH-4B-GGUF is a translation model from KordAI. Use it when you need text moved from one language to another. The card lists the license as apache-2.0.
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.gguf24.4 GB · 100%
From the Hugging Face model README
Typhoon Gemma 3 KordTranslate EN-TH 4B (GGUF) is the official GGUF quantized release of Typhoon Gemma 3 KordTranslate EN-TH 4B, optimized for fast and efficient local inference with llama.cpp and compatible applications including LM Studio, Ollama, KoboldCpp, Jan, and other GGUF-supported runtimes.
The original model is instruction-tuned specifically for high-quality English ↔ Thai machine translation, while preserving the multilingual understanding inherited from the Typhoon Gemma 3 base model.
| Item | Value |
|---|---|
| Model | KordAI/Typhoon-Gemma3-KordTranslate-EN-TH-4B-GGUF |
| Original Model | KordAI/Typhoon-Gemma3-KordTranslate-EN-TH-4B |
| Base Model | typhoon-ai/typhoon2.1-gemma3-4b |
| Architecture | Gemma 3 (4B) |
| Format | GGUF |
| Task | Machine Translation |
| Languages | English, Thai |
| Quantization | GGUF |
| Quantization | Approx. Size | Recommended Use |
|---|---|---|
| Q2_K_L | ~1.5 GB | Smallest footprint. Best for systems with very limited memory. |
| Q3_K_M | ~1.8 GB | Better quality than Q2 while remaining lightweight. |
| Q4_K_M | ~2.2 GB | Excellent balance of speed, size, and translation quality. |
| Q5_K_M | ~2.6 GB | Recommended. Best overall balance between quality, speed, and memory usage. |
| Q6_K | ~3.0 GB | Higher translation quality with moderate memory requirements. |
| Q8_0 | ~3.8 GB | Highest-quality quantized model, closest to full precision. |
| F16 | ~7.2 GB | Original float16 weights for compatible hardware and highest precision. |
Recommended Models
- ⭐ Q5_K_M — Best overall choice for most users.
- 💻 Q4_K_M — Great for CPU inference and laptops.
- 🎯 Q8_0 — Best quantized quality.
- 🚀 F16 — Best accuracy if sufficient VRAM/RAM is available.
This model is optimized for:
For the best translation quality, use the following prompts.
Translate the following English text to Thai.
### English:
[Your English text here]
Translate the following Thai text to English.
### Thai:
[Your Thai text here]
./llama-cli \
-m Typhoon-Gemma3-KordTranslate-EN-TH-4B.Q5_K_M.gguf \
-p "Translate the following English text to Thai.
### English:
Artificial intelligence is transforming the world."
Create a Modelfile:
FROM Typhoon-Gemma3-KordTranslate-EN-TH-4B.Q5_K_M.gguf
Create the model:
ollama create kordtranslate -f Modelfile
Run it:
ollama run kordtranslate
Example prompt:
Translate the following Thai text to English.
### Thai:
สวัสดีครับ ยินดีที่ได้รู้จัก
| Quantization | Approx. RAM Required |
|---|---|
| Q2_K_L | 3–4 GB |
| Q3_K_M | 4 GB |
| Q4_K_M | 5 GB |
| Q5_K_M | 6 GB |
| Q6_K | 7 GB |
| Q8_0 | 8–10 GB |
| F16 | 12–16 GB |
Actual memory usage depends on the inference engine, context length, GPU offloading, and batch size.
This repository contains GGUF quantized versions of the original model.
The original model was fine-tuned from typhoon-ai/typhoon2.1-gemma3-4b using Supervised Fine-Tuning (SFT) on bilingual English–Thai translation datasets.
No additional fine-tuning has been performed for this release. Only weight quantization has been applied to improve inference efficiency while maintaining translation quality.
GGUF quantization significantly reduces model size and memory requirements while maintaining excellent translation performance.
Compared with the original full-precision model:
Special thanks to:
typhoon2.1-gemma3-4b base model.If you use this model in your work, please cite the original model.
@misc{kordtranslate2026,
title={Typhoon Gemma3 KordTranslate EN-TH 4B},
author={KordAI},
year={2026},
publisher={Hugging Face},
howpublished={https://huggingface.co/KordAI/Typhoon-Gemma3-KordTranslate-EN-TH-4B}
}
If you find this project useful, please consider:
Happy translating! 🇹🇭🇺🇸