Instructions to use allenai/Olmo-3-32B-Think with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use allenai/Olmo-3-32B-Think with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="allenai/Olmo-3-32B-Think")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("allenai/Olmo-3-32B-Think")
model = AutoModelForMultimodalLM.from_pretrained("allenai/Olmo-3-32B-Think")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use allenai/Olmo-3-32B-Think with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "allenai/Olmo-3-32B-Think"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "allenai/Olmo-3-32B-Think",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/allenai/Olmo-3-32B-Think

SGLang

How to use allenai/Olmo-3-32B-Think with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "allenai/Olmo-3-32B-Think" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "allenai/Olmo-3-32B-Think",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "allenai/Olmo-3-32B-Think" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "allenai/Olmo-3-32B-Think",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use allenai/Olmo-3-32B-Think with Docker Model Runner:
```
docker model run hf.co/allenai/Olmo-3-32B-Think
```

Add pipeline tag, update paper link and add homepage

#15

by nielsr HF Staff - opened Dec 18, 2025

base: refs/heads/main

←

from: refs/pr/15

Discussion Files changed

-4

Files changed (1) hide show

README.md +6 -4

README.md CHANGED Viewed

@@ -1,12 +1,14 @@
 ---
-license: apache-2.0
 base_model: allenai/Olmo-3-32B-Think-DPO
-language:
-- en
 datasets:
 - allenai/Dolci-Think-RL
 library_name: transformers
 new_version: allenai/Olmo-3.1-32B-Think
 ---
 # Model Details
@@ -123,7 +125,7 @@ Moo Moo the cow would certinaly win.<|im_end|>
     - Open-Instruct for DPO and RLVR: https://github.com/allenai/open-instruct
     - OLMo-Core for pre-training and SFT: https://github.com/allenai/OLMo-core
     - OLMo-Eval for evaluation: https://github.com/allenai/OLMo-Eval
-- **Paper:** [TBD]
 <!-- - **Technical blog post:** (URL)  -->
 <!-- - **W&B Logs:** [SFT](()), [DPO](()), [RLVR](()) -->

 ---
 base_model: allenai/Olmo-3-32B-Think-DPO
 datasets:
 - allenai/Dolci-Think-RL
+language:
+- en
 library_name: transformers
+license: apache-2.0
 new_version: allenai/Olmo-3.1-32B-Think
+pipeline_tag: text-generation
+homepage: https://playground.allenai.org/?model=Olmo-3.1-32B-Think
 ---
 # Model Details
     - Open-Instruct for DPO and RLVR: https://github.com/allenai/open-instruct
     - OLMo-Core for pre-training and SFT: https://github.com/allenai/OLMo-core
     - OLMo-Eval for evaluation: https://github.com/allenai/OLMo-Eval
+- **Paper:** [Olmo 3](https://huggingface.co/papers/2512.13961)
 <!-- - **Technical blog post:** (URL)  -->
 <!-- - **W&B Logs:** [SFT](()), [DPO](()), [RLVR](()) -->