iapp/ openthai-1.6-72b

5 Downloads Updated 6 days ago

OpenThai's general-purpose flagship — 98.2% Thai language accuracy, strongest of the family at Thai coding. ~48 GB RAM/VRAM.

ollama run iapp/openthai-1.6-72b

curl http://localhost:11434/api/chat \
  -d '{
    "model": "iapp/openthai-1.6-72b",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='iapp/openthai-1.6-72b',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'iapp/openthai-1.6-72b',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Models

Name

2 models

Size / Usage

Context

Input

openthai-1.6-72b:latest

47GB · 32K context window · Text · 6 days ago

openthai-1.6-72b:latest

47GB

32K

Text

openthai-1.6-72b:q4_K_M

47GB · 32K context window · Text · 6 days ago

openthai-1.6-72b:q4_K_M

47GB

32K

Text

Readme

OpenThaiGPT 1.6 72B — GGUF

ollama run iapp/openthai-1.6-72b

Official GGUF quantizations of openthaigpt/openthaigpt-1.6-72b-instruct

Website · Leaderboard · Discord · Paper

The general-purpose workhorse of the OpenThai family — 98.2% Thai language accuracy, strongest of the family on Thai coding (LiveCodeBench-TH 32.43). These are the official quantizations, built from the source weights by the OpenThai team.

For step-by-step reasoning use R1 32B — smaller and better at it. For a laptop, use 1.5 7B.

Quants

File	Quant	Size	Notes
`openthaigpt-1.6-72b-instruct.Q4_K_M.gguf`	Q4_K_M	~44 GB	Recommended. 2× 24 GB GPUs or a 64 GB Mac.
`openthaigpt-1.6-72b-instruct.Q5_K_M.gguf`	Q5_K_M	~51 GB	Higher quality.
`openthaigpt-1.6-72b-instruct.Q8_0.gguf`	Q8_0	~77 GB	Near-lossless.

Usage

Ollama

ollama run hf.co/openthaigpt/openthaigpt-1.6-72b-instruct-GGUF:Q4_K_M

llama.cpp

llama-cli -m openthaigpt-1.6-72b-instruct.Q4_K_M.gguf \
  -p "เขียนฟังก์ชัน Python แปลงเลขไทยเป็นเลขอารบิก พร้อมอธิบายโค้ด" -n 2048 --temp 0.7

Uses the ChatML template (<|im_start|> / <|im_end|>), embedded in the GGUF. Recommended sampling: temperature=0.7, top_p=0.9.

Citation

@misc{yuenyong2025openthaigpt16r1thaicentric,
      title={OpenThaiGPT 1.6 and R1: Thai-Centric Open Source and Reasoning Large Language Models},
      author={Sumeth Yuenyong and Thodsaporn Chay-intr and Kobkrit Viriyayudhakorn},
      year={2025},
      eprint={2504.01789},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2504.01789}
}

OpenThai (formerly OpenThaiGPT) — free, open-weight Thai large language models from AIEAT and iApp Technology. With thanks to the community members who published unofficial GGUF conversions before these existed.

![OpenThai](https://huggingface.co/spaces/openthaigpt/README/resolve/main/openthai-logo-white.png)

# OpenThaiGPT 1.6 72B — GGUF

```
ollama run iapp/openthai-1.6-72b
```

**Official** GGUF quantizations of [openthaigpt/openthaigpt-1.6-72b-instruct](https://huggingface.co/openthaigpt/openthaigpt-1.6-72b-instruct)

[Website](https://openthai.aieat.or.th) · [Leaderboard](https://huggingface.co/spaces/openthaigpt/thai-llm-leaderboard) · [Discord](https://discord.gg/7KDdKkBGUs) · [Paper](https://arxiv.org/abs/2504.01789)

The general-purpose workhorse of the OpenThai family — 98.2% Thai language accuracy,
strongest of the family on Thai coding (LiveCodeBench-TH 32.43). These are the official
quantizations, built from the source weights by the OpenThai team.

For step-by-step reasoning use
[R1 32B](https://huggingface.co/openthaigpt/openthaigpt-r1-32b-instruct-GGUF) — smaller
and better at it. For a laptop, use
[1.5 7B](https://huggingface.co/openthaigpt/openthaigpt1.5-7b-instruct-GGUF).

## Quants

| File | Quant | Size | Notes |
|---|---|---|---|
| `openthaigpt-1.6-72b-instruct.Q4_K_M.gguf` | Q4_K_M | ~44 GB | **Recommended.** 2× 24 GB GPUs or a 64 GB Mac. |
| `openthaigpt-1.6-72b-instruct.Q5_K_M.gguf` | Q5_K_M | ~51 GB | Higher quality. |
| `openthaigpt-1.6-72b-instruct.Q8_0.gguf` | Q8_0 | ~77 GB | Near-lossless. |

## Usage

**Ollama**

```bash
ollama run hf.co/openthaigpt/openthaigpt-1.6-72b-instruct-GGUF:Q4_K_M
```

**llama.cpp**

```bash
llama-cli -m openthaigpt-1.6-72b-instruct.Q4_K_M.gguf \
  -p "เขียนฟังก์ชัน Python แปลงเลขไทยเป็นเลขอารบิก พร้อมอธิบายโค้ด" -n 2048 --temp 0.7
```

Uses the **ChatML** template (`<|im_start|>` / `<|im_end|>`), embedded in the GGUF.
Recommended sampling: `temperature=0.7`, `top_p=0.9`.

## Citation

```bibtex
@misc{yuenyong2025openthaigpt16r1thaicentric,
      title={OpenThaiGPT 1.6 and R1: Thai-Centric Open Source and Reasoning Large Language Models},
      author={Sumeth Yuenyong and Thodsaporn Chay-intr and Kobkrit Viriyayudhakorn},
      year={2025},
      eprint={2504.01789},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2504.01789}
}
```

---

*OpenThai (formerly OpenThaiGPT) — free, open-weight Thai large language models from AIEAT
and iApp Technology. With thanks to the community members who published unofficial GGUF
conversions before these existed.*

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