Open-weight model · Text generation
AMOR-GatedDeltaNet-1.5B
by Flyingodzilla FlyinGodzilla/AMOR-GatedDeltaNet-1.5B
AMOR-GatedDeltaNet-1.5B is an open-weight model for text generation from Flyingodzilla, released under MIT License. It has 1.5B parameters. At 16-bit it needs about 3.7 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.
Parameters1.5B
Context—
Weights—
Licensemit
AccessOpen weights
Monthly Downloads—
Runs On
What it takes to serve AMOR-GatedDeltaNet-1.5B (1.5B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.
| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
|---|---|---|---|---|---|
| 16-bit | 3.0 GB | 3.7 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 1.5 GB | 1.8 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 0.8 GB | 0.9 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 Sep 21, 2026.
AMOR-GatedDeltaNet-1.5B on every accelerator the SAVRN Index prices, at every precision
Model Card
Identity and Version
- Repository
- FlyinGodzilla/AMOR-GatedDeltaNet-1.5B
- Publisher
- Flyingodzilla
- Task
- Text generation
- Modality
- Text
- Library
- pytorch
- Parameters
- 1.5B parameters
- Languages
- en
- Revision
- f08f2d4c3d0dbf1225b0d9927c4340adb262deec
- First published
- 2026-09-21
- Last updated
- 2026-09-21
License and Download
- License
- mit
- Access
- Open weights, no gate
Download from Flyingodzilla
Released by Flyingodzilla through its official repository on Hugging Face. Read the license.
Built From
- Described by arXiv:2602.13215
- Trained on (disclosed) HuggingFaceFW/fineweb-edu
Memory Requirements
| Precision | Weights in memory |
|---|---|
| 16-bit | 3.0 GB |
| 8-bit | 1.5 GB |
| 4-bit | 0.8 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About AMOR-GatedDeltaNet-1.5B
How much GPU memory does AMOR-GatedDeltaNet-1.5B need?
About 3.7 GB at 16-bit and 0.9 GB at 4-bit: the weights (1.5B parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run AMOR-GatedDeltaNet-1.5B 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 AMOR-GatedDeltaNet-1.5B commercially?
Yes. AMOR-GatedDeltaNet-1.5B is released under MIT License. The MIT License is a short permissive license. It permits commercial use, modification and redistribution, provided the copyright notice and permission notice are included.
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