Highlights
- Reasons in the open. Native chain‑of‑thought via
<think>…</think> — transparent, inspectable reasoning distilled from a panel of frontier teachers.
- 1,000,000‑token context. Full 1M context window (YaRN‑extended), backed by a gated‑linear‑attention hybrid backbone that keeps long‑context inference efficient.
- Built for code and reasoning. Tuned for software engineering, step‑by‑step problem solving, and technical explanation.
- Vision‑language. Retains a full vision encoder — text and image understanding in one 9B model.
- Ships everywhere. Available in BF16, NVFP4, and a complete GGUF quant ladder (see Formats below).
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. Retains the vision encoder and the multi‑token‑prediction head.
Quickstart
from transformers import AutoModelForImageTextToText, AutoProcessor
model = AutoModelForImageTextToText.from_pretrained(
"Blackfrost-AI/PINQWEN-3.6-9B-BF16", dtype="bfloat16", device_map="auto")
proc = AutoProcessor.from_pretrained("Blackfrost-AI/PINQWEN-3.6-9B-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))
Table with columns: Format, Repository, Best for| Format | Repository | Best for |
|---|
| BF16 | Blackfrost-AI/PINQWEN-3.6-9B-BF16 | Reference precision, fine‑tuning, vision |
| NVFP4 | Blackfrost-AI/PINQWEN-3.6-9B-NVFP4 | Fast serving on NVIDIA Blackwell |
| GGUF | Blackfrost-AI/PINQWEN-3.6-9B-GGUF | llama.cpp / local (full quant ladder, MTP) |
Intended use
General reasoning, coding assistance, technical Q&A, long‑document and long‑codebase understanding, and multimodal (image + text) tasks. As with any language model, verify outputs for high‑stakes use.
License
Released under Apache‑2.0. Base architecture: Qwen 3.5 9B.
PINQWEN‑3.6‑9B is part of Blackfrost AI's Void model family.