Instructions to use gdubicki/GLM-4.7-Flash-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use gdubicki/GLM-4.7-Flash-NVFP4 with Transformers:

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

pipe = pipeline("text-generation", model="gdubicki/GLM-4.7-Flash-NVFP4")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("gdubicki/GLM-4.7-Flash-NVFP4")
model = AutoModelForCausalLM.from_pretrained("gdubicki/GLM-4.7-Flash-NVFP4")
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 gdubicki/GLM-4.7-Flash-NVFP4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "gdubicki/GLM-4.7-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": "gdubicki/GLM-4.7-Flash-NVFP4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/gdubicki/GLM-4.7-Flash-NVFP4

SGLang

How to use gdubicki/GLM-4.7-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 "gdubicki/GLM-4.7-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": "gdubicki/GLM-4.7-Flash-NVFP4",
		"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 "gdubicki/GLM-4.7-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": "gdubicki/GLM-4.7-Flash-NVFP4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use gdubicki/GLM-4.7-Flash-NVFP4 with Docker Model Runner:
```
docker model run hf.co/gdubicki/GLM-4.7-Flash-NVFP4
```

gdubicki/GLM-4.7-Flash-NVFP4

Public mirror of GadflyII/GLM-4.7-Flash-NVFP4.

This mirror exists to provide a pinned, stable reference for deployment on DGX Spark (GB10). Use the upstream repo if you want to track author updates.

Credits

Base model: zai-org/GLM-4.7-Flash by Zhipu AI / Z.ai (MIT)
NVFP4 quantization: GadflyII using LLM Compressor (compressed-tensors format)
License: Apache-2.0 (base model MIT permits relicensing with attribution)

Model details

Architecture: glm4_moe_lite — GLM-4 MoE (lite variant)
Parameters: ~31B total (MoE, fraction active per token)
Quantization: NVFP4 via compressed-tensors
KV cache: FP8 (recommended on GB10)
Max context: inherits from base (zai-org/GLM-4.7-Flash)

Usage

docker run --rm --runtime=nvidia --gpus all \
  -p 8000:8000 \
  -v ~/.cache/huggingface:/root/.cache/huggingface \
  -e VLLM_NVFP4_GEMM_BACKEND=marlin \
  -e VLLM_USE_FLASHINFER_MOE_FP4=0 \
  vllm/vllm-openai:cu130-nightly \
  gdubicki/GLM-4.7-Flash-NVFP4 \
  --dtype auto \
  --kv-cache-dtype fp8 \
  --gpu-memory-utilization 0.30 \
  --enable-chunked-prefill \
  --enable-prefix-caching

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Safetensors

Model size

18B params

Tensor type

F32

BF16

F8_E4M3

Model tree for gdubicki/GLM-4.7-Flash-NVFP4

Base model

zai-org/GLM-4.7-Flash

Quantized

GadflyII/GLM-4.7-Flash-NVFP4

Quantized

(1)

this model