Instructions to use Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16 with Transformers:

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

pipe = pipeline("image-text-to-text", model="Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16")
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 AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16")
model = AutoModelForMultimodalLM.from_pretrained("Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16")
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?"}
        ]
    },
]
inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16",
		"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/Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16

SGLang

How to use Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16 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 "Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16" \
    --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": "Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16",
		"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 "Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16" \
        --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": "Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16",
		"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 Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16 with Docker Model Runner:
```
docker model run hf.co/Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16
```

PINQWEN-3.5-9B-1M-BF16 / README.md

Blackfrost-AI

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metadata

license: apache-2.0
base_model:
  - Qwen/Qwen3.5-9B
pipeline_tag: image-text-to-text
library_name: transformers
tags:
  - blackfrost
  - the-void
  - pinqwen
  - 1m-context
  - uncensored
  - reasoning
  - long-context
  - coding
  - vision-language

PINQWEN‑3.5‑9B‑1M

🪟 A 9B that reads a million tokens, thinks before it speaks, and never refuses.

PINQWEN‑3.5‑9B‑1M is Blackfrost AI's compact powerhouse — a reasoning model distilled through The Void, our multi‑teacher reasoning‑distillation method, on the Qwen 3.5 9B architecture. It reasons first and answers second: for any real problem it opens a <think> block, works it through, then delivers a clean, direct answer — and it does it across a full one‑million‑token context window that most models this size can only dream of.

🚀 Why PINQWEN‑3.5‑9B‑1M?


🪟 1,000,000‑token context	Feed it entire codebases, whole books, months of chat logs — at once. A YaRN‑extended window on a gated‑linear‑attention hybrid backbone built to make long context fast, not just possible.
🔓 Uncensored	De‑risked to answer directly, without the reflexive refusals of over‑aligned models. You decide what it works on.
🧠 Reasons in the open	Native `<think>…</think>` chain‑of‑thought distilled from a panel of frontier teachers — transparent, inspectable reasoning you can actually read.
💻 Codes and reasons	Tuned for software engineering, step‑by‑step problem solving, and precise technical explanation.
👁 Sees	A full vision encoder — text and images in one 9B model.
⚡ Runs anywhere	BF16, NVFP4 for Blackwell, and a complete GGUF quant ladder with the MTP speculative‑decode head.

📦 This repository — BF16

Full‑precision (bfloat16) weights: the reference model — ideal for fine‑tuning, evaluation, vision‑language use, and as the source for further quantization. Keeps the vision encoder and the multi‑token‑prediction head. Full 1M context.

⚡ Quickstart

from transformers import AutoModelForImageTextToText, AutoProcessor

model = AutoModelForImageTextToText.from_pretrained(
    "Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16", dtype="bfloat16", device_map="auto")
proc = AutoProcessor.from_pretrained("Blackfrost-AI/PINQWEN-3.5-9B-1M-BF16")

messages = [{"role": "user", "content": "Write a Python LRU cache with O(1) get/put and explain the design."}]
ids = proc.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
out = model.generate(ids, max_new_tokens=1024)
print(proc.decode(out[0][ids.shape[1]:], skip_special_tokens=True))

🎛 Formats — every one is 1M context

Format	Repository	Best for
BF16	`PINQWEN-3.5-9B-1M-BF16`	Reference precision, fine‑tuning, vision
NVFP4	`PINQWEN-3.5-9B-1M-NVFP4`	Fast serving on NVIDIA Blackwell
GGUF	`PINQWEN-3.5-9B-1M-GGUF`	llama.cpp / local — full quant ladder + MTP

🎯 Intended use

General reasoning, coding assistance, technical Q&A, ultra‑long‑document and whole‑codebase understanding, and multimodal (image + text) work. As an uncensored model, it will follow instructions directly — use responsibly and verify outputs for high‑stakes tasks.

📄 License

Apache‑2.0. Base architecture: Qwen 3.5 9B.

PINQWEN‑3.5‑9B‑1M — part of Blackfrost AI's Void model family. 🖤

Blackfrost-AI
/

PINQWEN-3.5-9B-1M-BF16

PINQWEN‑3.5‑9B‑1M

🪟 **A 9B that reads a million tokens, thinks before it speaks, and never refuses.**

🚀 Why PINQWEN‑3.5‑9B‑1M?

📦 This repository — BF16

⚡ Quickstart

🎛 Formats — every one is 1M context

🎯 Intended use

📄 License

PINQWEN‑3.5‑9B‑1M

🪟 A 9B that reads a million tokens, thinks before it speaks, and never refuses.

🚀 Why PINQWEN‑3.5‑9B‑1M?

📦 This repository — BF16

⚡ Quickstart

🎛 Formats — every one is 1M context

🎯 Intended use

📄 License

🪟 **A 9B that reads a million tokens, thinks before it speaks, and never refuses.**