Instructions to use stepfun-ai/Step-3.7-Flash-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use stepfun-ai/Step-3.7-Flash-NVFP4 with Transformers:

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

pipe = pipeline("image-text-to-text", model="stepfun-ai/Step-3.7-Flash-NVFP4", trust_remote_code=True)
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("stepfun-ai/Step-3.7-Flash-NVFP4", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use stepfun-ai/Step-3.7-Flash-NVFP4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "stepfun-ai/Step-3.7-Flash-NVFP4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "stepfun-ai/Step-3.7-Flash-NVFP4",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/stepfun-ai/Step-3.7-Flash-NVFP4

SGLang

How to use stepfun-ai/Step-3.7-Flash-NVFP4 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 "stepfun-ai/Step-3.7-Flash-NVFP4" \
    --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": "stepfun-ai/Step-3.7-Flash-NVFP4",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "stepfun-ai/Step-3.7-Flash-NVFP4" \
        --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": "stepfun-ai/Step-3.7-Flash-NVFP4",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use stepfun-ai/Step-3.7-Flash-NVFP4 with Docker Model Runner:
```
docker model run hf.co/stepfun-ai/Step-3.7-Flash-NVFP4
```

MTP-layer weights?

by CosmicRaisins - opened 8 days ago

Discussion

CosmicRaisins

8 days ago

Any plans on publishing an NVFP4 quant with MTP-layer weights?

huangyu-nv

StepFun org 7 days ago

Yes, this is in plan, we will update a version with NVFP4 + MTP

maglat

7 days ago

For my understanding, MTP layers are available in the GUFF variants?

bumblebeer

6 days ago

For my understanding, MTP layers are available in the GUFF variants?

Yeah, but NVFP4 + MTP will be faster on NVIDIA hardware than a comparably sized GGUF + MTP (and potentially more accurate as well).

huangyu-nv

StepFun org 5 days ago

Update: the HF checkpoint has now been updated, so stepfun-ai/Step-3.7-Flash-NVFP4 should work with vLLM MTP speculative decoding directly.

NVFP4 + MTP

The Step-3.7-Flash-NVFP4 checkpoint has been updated with MTP draft layers and now supports vLLM speculative decoding with:

--speculative-config '{"method": "mtp", "num_speculative_tokens": 3}'

On GPQA Diamond avg@16, NVFP4 + MTP matches quality within statistical noise compared with the same NVFP4 checkpoint without MTP: 77.81% vs. 78.41% item accuracy over 3168 records.

On a GB200 TP=4 vLLM setup with GPQA-style long-reasoning streaming prompts (~250 token prompt, ~1.6K token completion), NVFP4 + MTP improves aggregate decode throughput:

Concurrency	NVFP4 + MTP	NVFP4 no-MTP	Speedup
8	1309 tok/s	1155 tok/s	1.13x
32	4391 tok/s	3480 tok/s	1.26x
64	8229 tok/s	5667 tok/s	1.45x

This makes the NVFP4 checkpoint a practical option for high-throughput long-reasoning workloads while keeping the original NVFP4 model weights unchanged.

archib4

1 day ago

•

edited 1 day ago

can you share a vllm working config please i tried everything here, from your modelcard . The latest nightly with b12x isnt starting and your own docker image complains and fallsback on Step3VLProcessor error.
im on 2x 6000 rtx pro cards 😀

Qucy

about 23 hours ago

can you share a vllm working config please i tried everything here, from your modelcard . The latest nightly with b12x isnt starting and your own docker image complains and fallsback on Step3VLProcessor error.
im on 2x 6000 rtx pro cards 😀

Same ask here, we want to benchmarking on 2x RTX pro 6000

huangyu-nv

StepFun org about 22 hours ago

I will take a look at running on rtx pro 6k.

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