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Open-weight model · Image and text to text

Qwen3.6-27B-AmberKite-BF16

by Phan Tran Viet Bach bachthetrollface/Qwen3.6-27B-AmberKite-BF16

Qwen3.6-27B-AmberKite-BF16 is an open-weight model for image and text to text from Phan Tran Viet Bach, released under Apache License 2.0. It has 27.4B parameters and a 262,144-token context. At 16-bit it needs about 65.7 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.

Fine-tuned derivative of Qwen/Qwen3.6-27B via Tooony133/Qwen-3.6-27B-SkinnyPete, stored in FP8 (compressed-tensors). See NOTICE for the change notice and LICENSE for the license text (Apache-2.0).

Parameters27.4B
Context262,144
Weights55.6 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads—

Runs On

What it takes to serve Qwen3.6-27B-AmberKite-BF16 (27.4B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

PrecisionWeightsMemory neededCheapest setupPer hourAlso fits
16-bit 54.7 GB 65.7 GB 1x MI300X (192 GB)
Vultr		 $1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 27.4 GB 32.8 GB 1x MI300X (192 GB)
Vultr		 $1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 13.7 GB 16.4 GB 1x MI300X (192 GB)
Vultr		 $1.85 1x H100 $1.99 · 1x MI325X $2.00

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Oct 18, 2026.

Qwen3.6-27B-AmberKite-BF16 on every accelerator the SAVRN Index prices, at every precision

Model Card

By Phan Tran Viet Bach, published under apache-2.0, revision 2cdf6884bf65.

Fine-tuned derivative of Qwen/Qwen3.6-27B via Tooony133/Qwen-3.6-27B-SkinnyPete, stored in FP8 (compressed-tensors). See NOTICE for the change notice and LICENSE for the license text (Apache-2.0).

Read Phan Tran Viet Bach's full model card

Qwen-3.6-27B-AmberKite

Fine-tuned derivative of Qwen/Qwen3.6-27B via Tooony133/Qwen-3.6-27B-SkinnyPete, stored in FP8 (compressed-tensors).

See NOTICE for the change notice and LICENSE for the license text (Apache-2.0).

Configuration

Architecture
Qwen3_5ForConditionalGeneration
Context length (tokens)
262,144
Layers
64
Hidden size
5,120
Feed-forward size
17,408
Attention heads
24
Key/value heads
4
Head dimension
256
Vocabulary size
248,320
Model type
qwen3_5

Identity and Version

Repository
bachthetrollface/Qwen3.6-27B-AmberKite-BF16
Publisher
Phan Tran Viet Bach
Task
Image and text to text
Modality
Image and text
Library
transformers
Parameters
27.4B parameters
Languages
Not stated by the source
Revision
2cdf6884bf657a927581e9d47ba702116abe28fa
First published
2026-10-12
Last updated
2026-10-12

Files and Weights

19 files, 55.6 GB in total. The weights are 2 files totalling 55.6 GB in safetensors.

Weights2 files · 55.6 GB
Configuration8 files · 138.2 KB
Tokenizer4 files · 30.1 MB
Documentation3 files · 13.3 KB
Other1 file · 7.8 KB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
model-mtp.safetensorsWeights849.4 MB 713b0fafacc9
model.safetensorsWeights54.7 GB d6825b5e76f3
config.jsonConfiguration3.7 KB —
dequantization_provenance.jsonConfiguration28.1 KB —
generation_config.jsonConfiguration202 B —
model.safetensors.index.jsonConfiguration94.3 KB —
original_quantization_config.jsonConfiguration10.8 KB —
preprocessor_config.jsonConfiguration390 B —
recipe.yamlConfiguration302 B —
video_preprocessor_config.jsonConfiguration385 B —
LICENSEDocumentation11.3 KB —
NOTICEDocumentation1.4 KB —
README.mdDocumentation538 B —
chat_template.jinjaOther7.8 KB —
.gitattributesRepository1.6 KB —
merges.txtTokenizer3.4 MB —
tokenizer.jsonTokenizer20.0 MB 06b9509352d2
tokenizer_config.jsonTokenizer1.2 KB —
vocab.jsonTokenizer6.7 MB —

License and Download

License
apache-2.0
Access
Open weights, no gate
Download size
55.6 GB
Download from Phan Tran Viet Bach

Released by Phan Tran Viet Bach through its official repository on Hugging Face. Read the license.

Built From

  • Derived from Tooony133/Qwen-3.6-27B-SkinnyPete

Memory Requirements

PrecisionWeights in memory
As published55.6 GB
16-bit54.7 GB
8-bit27.4 GB
4-bit13.7 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About Qwen3.6-27B-AmberKite-BF16

How much GPU memory does Qwen3.6-27B-AmberKite-BF16 need?

About 65.7 GB at 16-bit and 16.4 GB at 4-bit: the weights (27.4B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run Qwen3.6-27B-AmberKite-BF16 on?

At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

Can I use Qwen3.6-27B-AmberKite-BF16 commercially?

Yes. Qwen3.6-27B-AmberKite-BF16 is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

What is Qwen3.6-27B-AmberKite-BF16's context length?

262,144 tokens, from the maximum position embeddings in its published configuration.

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