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Open-weight model · Text generation

Qwen3.5-397B-A17B-VQ-2.6bpw

by Noah Zelezny TheDrainFlorist/Qwen3.5-397B-A17B-VQ-2.6bpw

Qwen3.5-397B-A17B-VQ-2.6bpw is an open-weight model for text generation from Noah Zelezny, released under Apache License 2.0. It has 59.2B parameters and a 262,144-token context. At 16-bit it needs about 142 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index. It draws 1.5k downloads a month.

105.5 GiB text weights — the balanced build. Also ships the bf16 vision tower (+0.85 GiB) and an optional MTP draft head (+5.4 GiB); full download 111.8 GiB.

Parameters59.2B
Context262,144
Weights120.0 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads1.5k

Runs On

What it takes to serve Qwen3.5-397B-A17B-VQ-2.6bpw (59.2B 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 118.3 GB 142.0 GB 1x MI300X (192 GB)
Vultr
$1.85 1x MI325X $2.00 · 1x MI355X $2.59
8-bit 59.2 GB 71.0 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 29.6 GB 35.5 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 7, 2026.

Qwen3.5-397B-A17B-VQ-2.6bpw on every accelerator the SAVRN Index prices, at every precision

Model Card

By Noah Zelezny, published under apache-2.0, revision 5ff492af70af.

105.5 GiB text weights — the balanced build. Also ships the bf16 vision tower (+0.85 GiB) and an optional MTP draft head (+5.4 GiB); full download 111.8 GiB.

It lands in the same size class as the strongest community quant at this rate; the table below is the comparison. A vector-quantized build of Qwen3.5-397B-A17B for Apple Silicon. Stock mlx-lm, no patches — the VQ runtime ships inside the checkpoint as model.py. It sits between the VQ-2.4bpw daily driver and the VQ-3bpw quality build, and needs the same hardware class as the latter.

Changelog

2026-10-01 — vq-skipzero: dead rows dropped

Read the full model card (2,705 words)

Configuration

Architecture
Qwen3_5MoeForConditionalGeneration
Context length (tokens)
262,144
Layers
60
Hidden size
4,096
Attention heads
32
Key/value heads
2
Head dimension
256
Vocabulary size
248,320
Experts
512
Experts active per token
10
Model type
qwen3_5_moe

Identity and Version

Repository
TheDrainFlorist/Qwen3.5-397B-A17B-VQ-2.6bpw
Publisher
Noah Zelezny
Task
Text generation
Modality
Text
Library
mlx
Parameters
59.2B parameters
Languages
en
Revision
5ff492af70af6174712977788b4fb3c2a1b2d8d5
First published
2026-08-25
Last updated
2026-10-02

Files and Weights

44 files, 125.9 GB in total. The weights are 29 files totalling 120.0 GB in safetensors.

Weights29 files · 120.0 GB
Configuration8 files · 715.3 KB
Tokenizer2 files · 20.0 MB
Documentation1 file · 18.5 KB
Other3 files · 5.8 GB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
model-00001-of-00027.safetensorsWeights2.9 GB 13336296bd63
model-00002-of-00027.safetensorsWeights2.9 GB 3f627ffffd6c
model-00003-of-00027.safetensorsWeights3.5 GB fe3fdf452290
model-00004-of-00027.safetensorsWeights4.0 GB 1d8f8cf6c837
model-00005-of-00027.safetensorsWeights3.7 GB 7aa0e8b6259f
model-00006-of-00027.safetensorsWeights3.9 GB 9aeaa842415c
model-00007-of-00027.safetensorsWeights4.3 GB 13599756042f
model-00008-of-00027.safetensorsWeights4.2 GB 95019aaee0f8
model-00009-of-00027.safetensorsWeights4.3 GB 8fea418dcece
model-00010-of-00027.safetensorsWeights4.6 GB 6c33be9fe149
model-00011-of-00027.safetensorsWeights4.5 GB 69f9c5f0c15f
model-00012-of-00027.safetensorsWeights4.6 GB fe087e399e41
model-00013-of-00027.safetensorsWeights4.8 GB 5cecc8238fa5
model-00014-of-00027.safetensorsWeights4.8 GB a743a8cb5ae3
model-00015-of-00027.safetensorsWeights4.8 GB 1c495f545d4a
model-00016-of-00027.safetensorsWeights4.9 GB 855fe5458298
model-00017-of-00027.safetensorsWeights4.8 GB efe1be6fab36
model-00018-of-00027.safetensorsWeights4.7 GB edfa2485d70a
model-00019-of-00027.safetensorsWeights4.9 GB 497e27b264f3
model-00020-of-00027.safetensorsWeights4.7 GB 13dcca9068cc
model-00021-of-00027.safetensorsWeights4.7 GB d49698bd239a
model-00022-of-00027.safetensorsWeights4.8 GB a4db98df474a
model-00023-of-00027.safetensorsWeights4.6 GB b398e044c6e0
model-00024-of-00027.safetensorsWeights4.5 GB 7ef60393b775
model-00025-of-00027.safetensorsWeights3.8 GB 83a68dcf7925
model-00026-of-00027.safetensorsWeights3.1 GB 2f1291d47896
model-00027-of-00027.safetensorsWeights2.0 GB 278ee2fb3735
model-vision-graft.safetensorsWeights912.1 MB b47e83150554
mtp-head-q6.safetensorsWeights5.8 GB 1563d297c7bc
config.jsonConfiguration149.7 KB —
generation_config.jsonConfiguration244 B —
model.pyConfiguration262.3 KB —
model.safetensors.index.jsonConfiguration288.6 KB —
preprocessor_config.jsonConfiguration390 B —
skipzero_load.pyConfiguration5.6 KB —
video_preprocessor_config.jsonConfiguration385 B —
vqlab_provenance.jsonConfiguration8.1 KB —
README.mdDocumentation18.5 KB —
chat_template.jinjaOther7.8 KB —
mtp-head-q6.safetensors.fp32norms-bakOther5.8 GB a5cad76f094e
vqlab_provenance.history.jsonlOther55.8 KB —
.gitattributesRepository1.6 KB —
tokenizer.jsonTokenizer20.0 MB 06b9509352d2
tokenizer_config.jsonTokenizer1.2 KB —

License and Download

License
apache-2.0
Access
Open weights, no gate
Download size
120.0 GB
Download from Noah Zelezny

Released by Noah Zelezny through its official repository on Hugging Face. Read the license.

Built From

  • Derived from Qwen/Qwen3.5-397B-A17B
  • Quantized from Qwen/Qwen3.5-397B-A17B

Memory Requirements

PrecisionWeights in memory
As published120.0 GB
16-bit118.3 GB
8-bit59.2 GB
4-bit29.6 GB

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

Questions About Qwen3.5-397B-A17B-VQ-2.6bpw

How much GPU memory does Qwen3.5-397B-A17B-VQ-2.6bpw need?

About 142 GB at 16-bit and 35.5 GB at 4-bit: the weights (59.2B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run Qwen3.5-397B-A17B-VQ-2.6bpw 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 Qwen3.5-397B-A17B-VQ-2.6bpw commercially?

Yes. Qwen3.5-397B-A17B-VQ-2.6bpw 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 Qwen3.5-397B-A17B-VQ-2.6bpw's context length?

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

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