Instructions to use Motif-Technologies/Motif-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Motif-Technologies/Motif-3 with Transformers:

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

pipe = pipeline("text-generation", model="Motif-Technologies/Motif-3", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Motif-Technologies/Motif-3", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Motif-Technologies/Motif-3 with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Motif-Technologies/Motif-3

SGLang

How to use Motif-Technologies/Motif-3 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 "Motif-Technologies/Motif-3" \
    --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": "Motif-Technologies/Motif-3",
		"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 "Motif-Technologies/Motif-3" \
        --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": "Motif-Technologies/Motif-3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Motif-Technologies/Motif-3 with Docker Model Runner:
```
docker model run hf.co/Motif-Technologies/Motif-3
```

Add community evaluation results

by SaylorTwift HF Staff - opened 3 days ago

base: refs/heads/main

←

from: refs/pr/2

Discussion Files changed

+26

-0

Files changed (1) hide show

.eval_results/Motif-3.yaml +26 -0

.eval_results/Motif-3.yaml ADDED Viewed

	@@ -0,0 +1,26 @@

+- dataset:
+    id: SWE-bench/SWE-bench_Verified
+    task_id: swe_bench_%_resolved
+  value: 76.2
+  date: "2026-08-07"
+  source:
+    url: https://arxiv.org/abs/2608.09119
+    name: "Motif 3 Technical Report — Table 6"
+- dataset:
+    id: Idavidrein/gpqa
+    task_id: diamond
+  value: 83.4
+  date: "2026-08-07"
+  source:
+    url: https://arxiv.org/abs/2608.09119
+    name: "Motif 3 Technical Report — Table 6"
+- dataset:
+    id: cais/hle
+    task_id: hle
+  value: 37.0
+  date: "2026-08-07"
+  source:
+    url: https://arxiv.org/abs/2608.09119
+    name: "Motif 3 Technical Report — Table 6"