---
library_name: transformers
license: llama3.2
base_model: scb10x/llama3.2-typhoon2-3b-instruct
model-index:
- name: llama3.2-typhoon2-3b-instruct
  results: []
language:
- en
- th
datasets:
- scb10x/typhoon-t1-3b-research-preview-data
pipeline_tag: text-generation
---

# Typhoon T1 3B (Research Preview)

**Typhoon T1 3B (Research Preview)** is the first in a new family of open reasoning model "**Typhoon T**". Reasoning model is a novel type of model that think longer before giving a final answer.

Typhoon T1 3B (Research Preview) is built on top of [Typhoon 2 3B Instruct](https://huggingface.co/scb10x/llama3.2-typhoon2-3b-instruct). It has improved performance on challenging benchmarks like GPQA, MMLU Pro, and AI Mathematics Olympiad validation set.

> [!NOTE]
> 🚀
> **2025-02-01 Update**: We have released a new version of Typhoon T1 3B (Research Preview) with the ability to 🇹🇭 *generate Thai reasoning traces*, improved *Thai performance in general*, and *enhanced instruction following*. This version has the a comparative level of English performance to `v2025-01-23`.

## Key Points

- **Typhoon T1** is a new family of open reasoning models developed by SCB 10X
- **Typhoon T1 3B (Research Preview)**, the *first* in the **Typhoon T** family, shows improved performance across **challenging benchmarks** compared to the original Typhoon 2 3B Instruct
- Typhoon T1 3B (Research Preview) offers a **fast**, **low-compute requirements** model, yet is **capable** in a variety of tasks by scaling test-time compute, enabling the model to think longer before giving a final answer. Typhoon T1 3B (Research Preview) is able to **_reason across domains_**, unlike many open reasoning models limited to mathematics and coding
- We **open** our recipe for data pipeline and training this model without distilling from other reasoning models
- We introduce **a new thinking paradigm** for reasoning models, structured thinking, where we add auxiliary tokens to help structure the thinking process of the model. This approach shows an increase in performance over a common variant of separating only thought and response parts based on our experiments
- Typhoon T1 3B (Research Preview) `v2025-02-01` is the first reasoning model where we intentionally equipped the model with the ability to **generate Thai reasoning traces**, improving *transparency* and *interpretability* of the model.

For more technical details, please visit our [technical blog](https://blog.opentyphoon.ai/introducing-typhoon-t1-a-family-of-open-reasoning-models-research-preview-22daacc88662).

* To acknowledge Meta's effort in creating the foundation model and to comply with the license, we explicitly include `llama-3.2` in the model name.

## Performance

| Model name            | GSM8K (↑), 8-shot | HumanEval+ (↑), Pass@10 | GPQA (↑), 0CoT | AIME (↑) |
|-----------------------|-------------------|-------------------------|----------------|----------|
| Typhoon 2 3B Instruct | 56.63             | 66                      | 27.01          | 0        |
| Typhoon T1 3B (semi)  | 59.59             | 68.99                   | 25.89          | 0        |
| **Typhoon T1 3B (Research Preview)** v2025-01-23     | **62.40**         | **69.87**               | **31.7**       | **2.22** |

### MMLU Pro (↑), 5-shot

| Model name            | Average   | Math      | Health    | Physics  | Business  | Biology   | Chemistry | Computer Science | Economics | Engineering | Philosophy | Other     | History   | Psychology | Law       |
|-----------------------|-----------|-----------|-----------|----------|-----------|-----------|-----------|------------------|-----------|-------------|------------|-----------|-----------|------------|-----------|
| Typhoon 2 3B Instruct | 26.7      | 26.8      | 33.62     | 23.4     | 25.35     | 43.38     | 19.88     | 28.29            | 35.43     | 18.37       | 28.06      | 27.92     | 25.72     | 37.84      | 13.17     |
| **Typhoon T1 3B (Research Preview)** v2025-01-23     | **30.65** | **30.57** | **36.19** | **27.1** | **31.69** | **50.77** | **22.17** | **31.22**        | **38.86** | **21.98**   | **30.66**  | **32.79** | **26.51** | **43.36**  | **17.26** |

## Model description

- **Model type**: A 3B instruct decoder-only model based on Llama architecture.
- **Requirement**: `transformers` 4.46.1 or newer.
- **Primary Language(s)**: English 🇬🇧 and Thai 🇹🇭
- **License**: [Llama 3.2 Community License](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/LICENSE)


## Usage Examples

⚠️ Please note that `max_new_tokens` should be at least `512`, but is recommended at a minimum of `1,024` to provide space for complete generation.

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "scb10x/llama-3.2-typhoon-t1-3b-research-preview"
revision = "main" # To use the previous version comment this line
# revision = "v2025-01-23" # To use the previous version uncomment this line

tokenizer = AutoTokenizer.from_pretrained(model_id, revision=revision)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
    revision=revision
)

messages = [
    {"role": "user", "content": "หากแปลคำว่า \"ไต้ฝุ่น\" เป็นภาษาอังกฤษ ในคำที่ถูกแปลแล้วจะมีตัวอักษร \"o\" ทั้งหมดกี่ตัว"},
]

input_ids = tokenizer.apply_chat_template(
    messages,
    add_generation_prompt=True,
    return_tensors="pt"
).to(model.device)

terminators = [
    tokenizer.eos_token_id,
    tokenizer.convert_tokens_to_ids("<|eot_id|>")
]

outputs = model.generate(
    input_ids,
    max_new_tokens=1024,
    eos_token_id=terminators,
    do_sample=False,
    temperature=0.0,
    top_p=0.9,
)
response = outputs[0][input_ids.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True))
```

### OpenAI API-compatible Server with vLLM

```bash
pip install vllm
vllm serve scb10x/llama-3.2-typhoon-t1-3b-research-preview

# To serve the previous version, add the revision parameter as shown below
# vllm serve scb10x/llama-3.2-typhoon-t1-3b-research-preview --revision v2025-01-23
# see more information at https://docs.vllm.ai/
```

## Intended uses & limitations

While we made an effort to make our model safe, like all generative models, it may generate unsafe content in rare cases. Introducing a reasoning model paradigm may introduce some unforeseen behaviors, as model safety in the reasoning domain is a relatively new and ongoing area of research.

## Follow Us

[https://twitter.com/opentyphoon](https://twitter.com/opentyphoon)

## Support

[https://discord.gg/CqyBscMFpg](https://discord.gg/CqyBscMFpg)

## Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 6
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 6
- total_train_batch_size: 288
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2.0

## Citation

```
@misc{taveekitworachai2025typhoont1openthai,
      title={Typhoon T1: An Open Thai Reasoning Model}, 
      author={Pittawat Taveekitworachai and Potsawee Manakul and Kasima Tharnpipitchai and Kunat Pipatanakul},
      year={2025},
      eprint={2502.09042},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2502.09042}, 
}
```