shan-stt-v3 is an open-weight model from K1ng Tai. It has 242M parameters. At 16-bit it needs about 0.6 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.
Runs On
What it takes to serve shan-stt-v3 (242M 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 | 0.5 GB | 0.6 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 0.2 GB | 0.3 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 18, 2026.
shan-stt-v3 on every accelerator the SAVRN Index prices, at every precision
Model Card
The publisher has not written a card for this model.
Configuration
- Architecture
- WhisperForConditionalGeneration
- Layers
- 12
- Vocabulary size
- 51,865
- Model type
- whisper
Identity and Version
- Repository
- k1ngtai/shan-stt-v3
- Publisher
- K1ng Tai
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 242M parameters
- Languages
- Not stated by the source
- Revision
- 195a8393996d0ab5de30a62d01e93f00cf6ac27f
- First published
- 2026-10-04
- Last updated
- 2026-10-04
Files and Weights
8 files, 970.9 MB in total. The weights are 2 files totalling 967.0 MB in bin, safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.safetensors | Weights | 967.0 MB | ab682721248e |
| training_args.bin | Weights | 5.4 KB | 158d7592af8a |
| config.json | Configuration | 1.2 KB | — |
| generation_config.json | Configuration | 3.7 KB | — |
| processor_config.json | Configuration | 409 B | — |
| .gitattributes | Repository | 1.5 KB | — |
| tokenizer.json | Tokenizer | 3.9 MB | — |
| tokenizer_config.json | Tokenizer | 2.1 KB | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 967.0 MB
Released by K1ng Tai through its official repository on Hugging Face.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 967.0 MB |
| 16-bit | 0.5 GB |
| 8-bit | 0.2 GB |
| 4-bit | 0.1 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About shan-stt-v3
How much GPU memory does shan-stt-v3 need?
About 0.6 GB at 16-bit and 0.1 GB at 4-bit: the weights (242M parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run shan-stt-v3 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.