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Open-weight model

TestSubject-1

by Mr. Black Beard CyanMonkey/TestSubject-1

TestSubject-1 is a model from Mr. Black Beard, released under Apache License 2.0 (access requested at publisher). It has 149M parameters. At 16-bit it needs about 0.4 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index. It draws 106 downloads a month.

Rose X1.5 SLM (148.8M params).

Parameters149M
Context—
Weights1.9 GB
Licenseapache-2.0
AccessAccess requested at publisher
Monthly Downloads106

Runs On

What it takes to serve TestSubject-1 (149M 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 0.3 GB 0.4 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 0.1 GB 0.2 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 0.1 GB 0.1 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 23, 2026.

TestSubject-1 on every accelerator the SAVRN Index prices, at every precision

Model Card

By Mr. Black Beard, published under apache-2.0, revision 84de86ce81f1.

Rose X1.5 SLM (148.8M params).

Read Mr. Black Beard's full model card

Rose X1.5 SLM (148.8M params).

Architecture

Property Value
Layers 30
Hidden 640
Heads 10 (kv=5)
QK Norm True
XSA True
Refresh Gate [9, 19]
Params 148.826M

Training

  • Tokens: 49,468,620,800
  • Val PPL: 9.86
  • Optimizer: muon_adamw

Identity and Version

Repository
CyanMonkey/TestSubject-1
Publisher
Mr. Black Beard
Task
Not stated by the source
Modality
Other
Library
Not stated by the source
Parameters
149M parameters
Languages
en
Revision
84de86ce81f1424d68cfe15bf6bf2d6952e50b90
First published
2026-10-16
Last updated
2026-10-23

Files and Weights

248 files, 1.9 GB in total. The weights are 2 files totalling 1.9 GB in pt, safetensors.

Weights2 files · 1.9 GB
Configuration5 files · 30.2 KB
Tokenizer2 files · 2.3 MB
Documentation1 file · 429 B
Other237 files · 7.9 MB
Repository1 file · 1.5 KB
Every file
FileTypeSizeSHA-256
model.safetensorsWeights595.3 MB —
resume/ckpt.ptWeights1.3 GB —
config.jsonConfiguration1.1 KB —
configuration_rose_x1_5.pyConfiguration2.8 KB —
generation_config.jsonConfiguration44 B —
modeling_rose_x1_5.pyConfiguration25.9 KB —
training_meta.jsonConfiguration360 B —
README.mdDocumentation429 B —
logs/log_10000.jsonlOther8.4 KB —
logs/log_10400.jsonlOther11.2 KB —
logs/log_10800.jsonlOther13.9 KB —
logs/log_11200.jsonlOther16.7 KB —
logs/log_11600.jsonlOther19.5 KB —
logs/log_1200.jsonlOther8.4 KB —
logs/log_12000.jsonlOther22.2 KB —
logs/log_12400.jsonlOther25.0 KB —
logs/log_12800.jsonlOther27.8 KB —
logs/log_13200.jsonlOther30.5 KB —
logs/log_13600.jsonlOther33.3 KB —
logs/log_14000.jsonlOther36.0 KB —
logs/log_14400.jsonlOther38.8 KB —
logs/log_14800.jsonlOther41.6 KB —
logs/log_15200.jsonlOther44.3 KB —
logs/log_15600.jsonlOther47.1 KB —
logs/log_1600.jsonlOther11.2 KB —
logs/log_16000.jsonlOther49.9 KB —
logs/log_16400.jsonlOther52.6 KB —
logs/log_16800.jsonlOther55.4 KB —
logs/log_17200.jsonlOther58.2 KB —
logs/log_17600.jsonlOther60.9 KB —
logs/log_18000.jsonlOther63.7 KB —
logs/log_18400.jsonlOther66.4 KB —
logs/log_18800.jsonlOther3.0 KB —
logs/log_19200.jsonlOther5.7 KB —
logs/log_19600.jsonlOther8.5 KB —
logs/log_2000.jsonlOther13.9 KB —
logs/log_20000.jsonlOther11.3 KB —
logs/log_20400.jsonlOther14.1 KB —
logs/log_20800.jsonlOther16.8 KB —
logs/log_21200.jsonlOther19.6 KB —
logs/log_21600.jsonlOther22.4 KB —
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logs/log_22400.jsonlOther28.0 KB —
logs/log_22800.jsonlOther30.7 KB —
logs/log_23200.jsonlOther33.5 KB —
logs/log_23600.jsonlOther36.3 KB —
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logs/log_27600.jsonlOther64.1 KB —
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logs/log_28800.jsonlOther8.5 KB —
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logs/log_30400.jsonlOther19.6 KB —
logs/log_30800.jsonlOther22.4 KB —
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logs/log_32800.jsonlOther36.3 KB —
logs/log_33200.jsonlOther39.1 KB —
logs/log_33600.jsonlOther41.9 KB —
logs/log_34000.jsonlOther44.6 KB —
logs/log_34400.jsonlOther47.4 KB —
logs/log_34800.jsonlOther50.2 KB —
logs/log_35200.jsonlOther53.0 KB —
logs/log_35600.jsonlOther55.8 KB —
logs/log_3600.jsonlOther24.9 KB —
logs/log_36000.jsonlOther58.5 KB —
logs/log_36400.jsonlOther61.3 KB —
logs/log_36800.jsonlOther64.1 KB —
logs/log_37200.jsonlOther66.9 KB —
logs/log_37600.jsonlOther3.0 KB —
logs/log_38000.jsonlOther5.7 KB —
logs/log_38400.jsonlOther8.5 KB —
logs/log_38800.jsonlOther11.3 KB —
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logs/log_4400.jsonlOther30.3 KB —
logs/log_44000.jsonlOther47.4 KB —
logs/log_44400.jsonlOther50.2 KB —
logs/log_44800.jsonlOther53.0 KB —
logs/log_45200.jsonlOther55.7 KB —
logs/log_45600.jsonlOther58.5 KB —
logs/log_46000.jsonlOther61.3 KB —
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logs/log_46800.jsonlOther66.8 KB —
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logs/log_47600.jsonlOther5.7 KB —
logs/log_4800.jsonlOther33.1 KB —
logs/log_48000.jsonlOther8.5 KB —
logs/log_48400.jsonlOther11.3 KB —
logs/log_48800.jsonlOther14.1 KB —
logs/log_49200.jsonlOther16.8 KB —
logs/log_49600.jsonlOther19.6 KB —
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logs/log_68000.jsonlOther5.7 KB —
logs/log_68400.jsonlOther8.5 KB —
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logs/log_69200.jsonlOther14.1 KB —
logs/log_69600.jsonlOther16.8 KB —
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logs/log_70800.jsonlOther25.2 KB —
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logs/log_71600.jsonlOther30.7 KB —
logs/log_7200.jsonlOther49.6 KB —
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logs/log_80400.jsonlOther25.1 KB —
logs/log_80800.jsonlOther27.9 KB —
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logs/log_81600.jsonlOther33.5 KB —
logs/log_82000.jsonlOther36.3 KB —
logs/log_82400.jsonlOther39.0 KB —
logs/log_82800.jsonlOther41.8 KB —
logs/log_83200.jsonlOther44.6 KB —
logs/log_83600.jsonlOther47.4 KB —
logs/log_8400.jsonlOther57.8 KB —
logs/log_84000.jsonlOther50.1 KB —
logs/log_84400.jsonlOther52.9 KB —
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logs/log_85200.jsonlOther58.5 KB —
logs/log_85600.jsonlOther61.2 KB —
logs/log_86000.jsonlOther64.0 KB —
logs/log_86400.jsonlOther66.8 KB —
logs/log_86800.jsonlOther3.0 KB —
logs/log_87200.jsonlOther5.8 KB —
logs/log_87600.jsonlOther8.5 KB —
logs/log_8800.jsonlOther60.5 KB —
logs/log_88000.jsonlOther11.3 KB —
logs/log_88400.jsonlOther14.1 KB —
logs/log_88800.jsonlOther16.8 KB —
logs/log_89200.jsonlOther19.6 KB —
logs/log_89600.jsonlOther22.4 KB —
logs/log_90000.jsonlOther25.1 KB —
logs/log_90400.jsonlOther27.9 KB —
logs/log_90800.jsonlOther30.7 KB —
logs/log_91200.jsonlOther33.5 KB —
logs/log_91600.jsonlOther36.2 KB —
logs/log_9200.jsonlOther2.9 KB —
logs/log_92000.jsonlOther39.0 KB —
logs/log_92400.jsonlOther41.8 KB —
logs/log_92800.jsonlOther44.5 KB —
logs/log_93200.jsonlOther47.3 KB —
logs/log_93600.jsonlOther50.1 KB —
logs/log_94000.jsonlOther52.9 KB —
logs/log_94400.jsonlOther55.6 KB —
logs/log_9600.jsonlOther5.7 KB —
resume/latest_step.txtOther5 B —
.gitattributesRepository1.5 KB —
tokenizer.jsonTokenizer2.3 MB —
tokenizer_config.jsonTokenizer439 B —

License and Download

License
apache-2.0
Access
Access requested at publisher
Download size
1.9 GB
Request access from Mr. Black Beard

Mr. Black Beard grants access through its official repository on Hugging Face. Read the license.

Memory Requirements

PrecisionWeights in memory
As published1.9 GB
16-bit0.3 GB
8-bit0.1 GB
4-bit0.1 GB

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

Questions About TestSubject-1

How much GPU memory does TestSubject-1 need?

About 0.4 GB at 16-bit and 0.1 GB at 4-bit: the weights (149M parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run TestSubject-1 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 TestSubject-1 commercially?

Yes. TestSubject-1 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.