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Open-weight model

Qwen3.5-4B-Text-NoMTP

by Shuqing Luo xingruyu/Qwen3.5-4B-Text-NoMTP

Qwen3.5-4B-Text-NoMTP is an open-weight model from Shuqing Luo, released under Apache License 2.0. It has 4.2B parameters and a 262,144-token context. At 16-bit it needs about 10.1 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.

Parameters4.2B
Context262,144
Weights8.4 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads—

Runs On

What it takes to serve Qwen3.5-4B-Text-NoMTP (4.2B 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 8.4 GB 10.1 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 4.2 GB 5.0 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 2.1 GB 2.5 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 22, 2026.

Qwen3.5-4B-Text-NoMTP on every accelerator the SAVRN Index prices, at every precision

Model Card

The publisher has not written a card for this model.

Configuration

Architecture
Qwen3_5ForCausalLM
Context length (tokens)
262,144
Layers
32
Hidden size
2,560
Feed-forward size
9,216
Attention heads
16
Key/value heads
4
Head dimension
256
Vocabulary size
248,320
Model type
qwen3_5_text

Identity and Version

Repository
xingruyu/Qwen3.5-4B-Text-NoMTP
Publisher
Shuqing Luo
Task
Not stated by the source
Modality
Other
Library
Not stated by the source
Parameters
4.2B parameters
Languages
Not stated by the source
Revision
720372ac86647159e0fc44fb9478bab247070539
First published
2026-10-03
Last updated
2026-10-03

Files and Weights

20 files, 8.4 GB in total. The weights are 1 file totalling 8.4 GB in safetensors.

Weights1 file · 8.4 GB
Configuration9 files · 119.0 KB
Tokenizer4 files · 22.9 MB
Documentation2 files · 11.6 KB
Other3 files · 10.7 KB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
model.safetensorsWeights8.4 GB 944da4af029d
build_text_model.pyConfiguration9.3 KB —
config.jsonConfiguration2.0 KB —
configuration_qwen3_5.pyConfiguration4.1 KB —
conversion_report.jsonConfiguration49.8 KB —
generation_config.jsonConfiguration143 B —
inference.pyConfiguration1.4 KB —
modeling_qwen3_5.pyConfiguration45.9 KB —
validation_report.jsonConfiguration590 B —
verify_text_model.pyConfiguration5.7 KB —
LICENSEDocumentation11.5 KB —
README.mdDocumentation28 B —
USAGE.txtOther2.9 KB —
chat_template.jinjaOther7.8 KB —
requirements.txtOther51 B —
.gitattributesRepository1.6 KB —
merges.txtTokenizer3.4 MB —
tokenizer.jsonTokenizer12.8 MB 5f9e4d4901a9
tokenizer_config.jsonTokenizer16.7 KB —
vocab.jsonTokenizer6.7 MB —

License and Download

License
apache-2.0
Access
Open weights, no gate
Download size
8.4 GB
Download from Shuqing Luo

Released by Shuqing Luo through its official repository on Hugging Face. Read the license.

Memory Requirements

PrecisionWeights in memory
As published8.4 GB
16-bit8.4 GB
8-bit4.2 GB
4-bit2.1 GB

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

Questions About Qwen3.5-4B-Text-NoMTP

How much GPU memory does Qwen3.5-4B-Text-NoMTP need?

About 10.1 GB at 16-bit and 2.5 GB at 4-bit: the weights (4.2B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run Qwen3.5-4B-Text-NoMTP 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 Qwen3.5-4B-Text-NoMTP commercially?

Yes. Qwen3.5-4B-Text-NoMTP 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 Qwen3.5-4B-Text-NoMTP's context length?

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