Instructions to use JetBrains/Qwen3.8-3.6-27B-blend with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use JetBrains/Qwen3.8-3.6-27B-blend with Transformers:

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

pipe = pipeline("image-text-to-text", model="JetBrains/Qwen3.8-3.6-27B-blend")
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)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("JetBrains/Qwen3.8-3.6-27B-blend")
model = AutoModelForMultimodalLM.from_pretrained("JetBrains/Qwen3.8-3.6-27B-blend", device_map="auto")
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=256)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use JetBrains/Qwen3.8-3.6-27B-blend with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "JetBrains/Qwen3.8-3.6-27B-blend"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "JetBrains/Qwen3.8-3.6-27B-blend",
		"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/JetBrains/Qwen3.8-3.6-27B-blend

SGLang

How to use JetBrains/Qwen3.8-3.6-27B-blend 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 "JetBrains/Qwen3.8-3.6-27B-blend" \
    --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": "JetBrains/Qwen3.8-3.6-27B-blend",
		"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 "JetBrains/Qwen3.8-3.6-27B-blend" \
        --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": "JetBrains/Qwen3.8-3.6-27B-blend",
		"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 JetBrains/Qwen3.8-3.6-27B-blend with Docker Model Runner:
```
docker model run hf.co/JetBrains/Qwen3.8-3.6-27B-blend
```

Qwen3.8-3.6-27B-blend

File size: 4,337 Bytes

# Modifications to upstream Qwen material

This distribution contains files modified by JetBrains from Qwen models developed by Alibaba Cloud. This document records the modifications and identifies the affected model files; it accompanies the binary artifacts listed below.

## Base model merge

This model is a 50/50 combination of Qwen3.6-27B and Qwen3.8-27B, created by linearly interpolating their checkpoint parameters. The configuration, tokenizer, processor, and chat template are retained from Qwen3.8-27B. Exact source revisions and merge settings are recorded in [merge-manifest.json](merge-manifest.json).

The interpolation uses float32 accumulation. Upstream sources:

- [Qwen/Qwen3.6-27B](https://huggingface.co/Qwen/Qwen3.6-27B/tree/6a9e13bd6fc8f0983b9b99948120bc37f49c13e9), revision `6a9e13bd6fc8f0983b9b99948120bc37f49c13e9`, weight 0.5.
- [Qwen/Qwen3.8-27B](https://huggingface.co/Qwen/Qwen3.8-27B/tree/1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0), revision `1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0`, weight 0.5.

## Distribution-specific changes

The merged parameters were saved as a sharded Safetensors checkpoint with a corresponding tensor index. Configuration, tokenizer, processor, and chat template were retained from the pinned Qwen3.8-27B source.

## Modified model artifacts

The following files contain the merged parameters and, where applicable, the format conversions described above. SHA-256 values identify the binaries to which this modification notice applies.

| File | SHA-256 |
|---|---|
| `model-00001-of-00018.safetensors` | `5dcc8a33f79a5e063f8648c139f4f7eb14acbd53c44226776af8287ed23291e7` |
| `model-00002-of-00018.safetensors` | `8a308f482a8bbd87d4bdd8d627aa0c50d30e07a165f835d256aadb40f3ea33d4` |
| `model-00003-of-00018.safetensors` | `d35724d2fd43fa933e049d3075341694cc1c445c506f91fb88122ee5cd017f84` |
| `model-00004-of-00018.safetensors` | `673f15b2b35d050c0085c698bd334d59a6e3e780444bafff2355b768f447d265` |
| `model-00005-of-00018.safetensors` | `7623ad5b8d4c9bcb784fc8dc268dfb518a14b132b7bb064f8c0f9acdfd076c80` |
| `model-00006-of-00018.safetensors` | `2d46dc60da2269dc308a4f21cf944a625a87e0ecb0d4aa26f346ab52f0c9f65e` |
| `model-00007-of-00018.safetensors` | `934883a996ed41778fe56d5afa0a533df6508d2b627c54b6ef2e39870827ed14` |
| `model-00008-of-00018.safetensors` | `7bfae1bf1254971178c9ecf2d9fcabc0998578ca6c64022b662404c21a4f5e26` |
| `model-00009-of-00018.safetensors` | `f0bf6b75c951e190cb60980124e59c7c050b0d69c6b07ffb828318e69ddb0dce` |
| `model-00010-of-00018.safetensors` | `37353451306ed0aaba5b2d7ce7fca000fe0db9426ed5ffdd7f51c88b75ab6138` |
| `model-00011-of-00018.safetensors` | `8d7f6535a8c3bd6ae19051fdbaf087a933a435655425a4a281ce1bb71557ba5b` |
| `model-00012-of-00018.safetensors` | `f52f6f39ef26d09e1917ecd1c0ff75d9b6f1958593efd913c530e756449a9ffd` |
| `model-00013-of-00018.safetensors` | `d73e22a85ec5ad13c59903ae15f1815202fe11f5cb58f11f4463b5defc6629db` |
| `model-00014-of-00018.safetensors` | `c3c7847f227e7cfd8021241e874efff1fc5f219de32cf16818495c6e230da11f` |
| `model-00015-of-00018.safetensors` | `1187f2cc10d9f86f77f2ef162fab80eeab446645d6d60556a0d05d0821d5244c` |
| `model-00016-of-00018.safetensors` | `9b221bc8f0b5b908c195f8d74ac4fbbe729947b8f9ea2a5172c8bbeb203e28d7` |
| `model-00017-of-00018.safetensors` | `bb4d9b0ab787fec853d49c1bc7cfc68c99eba02a8805f73c756e2b43afb3bdb8` |
| `model-00018-of-00018.safetensors` | `181f41305054e557806eb7755bfe9261dfe4eefb3e78cb803bd8c978024b3fe5` |

## Documentation and attribution — 2026-09-15

Model cards and repository references were adapted for the JetBrains distribution. The model cards now prominently identify this release as an unofficial JetBrains derivative and disclose the absence of Alibaba affiliation or endorsement. NOTICE and this modification record were added. This documentation update does not alter model artifacts, runtime configuration, or provenance manifests.

The original Qwen LICENSE and Alibaba Cloud copyright notice are retained unchanged. Neither pinned upstream source contains a NOTICE file; this distribution's NOTICE was added by JetBrains.

Copyright © 2026 JetBrains s.r.o. applies only to original material contributed by JetBrains. Upstream Qwen material remains subject to its original copyright and attribution notices. See [LICENSE](LICENSE) and [NOTICE](NOTICE).