Open-weight model
T14b_14bad_S4b_klreg0.05_treftemp_1.0_checkpoint20
by Yunjae Won yunjae-won/T14b_14bad_S4b_klreg0.05_treftemp_1.0_checkpoint20
T14b_14bad_S4b_klreg0.05_treftemp_1.0_checkpoint20 is an open-weight model from Yunjae Won. It has 4B parameters and a 40,960-token context. At 16-bit it needs about 9.7 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 T14b_14bad_S4b_klreg0.05_treftemp_1.0_checkpoint20 (4B 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 | 8.0 GB | 9.7 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 4.0 GB | 4.8 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 2.0 GB | 2.4 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.
Model Card
The publisher has not written a card for this model.
Configuration
- Architecture
- Qwen3ForCausalLM
- Context length (tokens)
- 40,960
- Layers
- 36
- Hidden size
- 2,560
- Feed-forward size
- 9,728
- Attention heads
- 32
- Key/value heads
- 8
- Head dimension
- 128
- Vocabulary size
- 151,936
- Model type
- qwen3
Identity and Version
- Repository
- yunjae-won/T14b_14bad_S4b_klreg0.05_treftemp_1.0_checkpoint20
- Publisher
- Yunjae Won
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 4B parameters
- Languages
- Not stated by the source
- Revision
- 6b089ea885587f99ce7de6d5f6e229ea029c3535
- First published
- 2026-10-06
- Last updated
- 2026-10-06
Files and Weights
9 files, 8.1 GB in total. The weights are 2 files totalling 8.0 GB in bin, safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.safetensors | Weights | 8.0 GB | 8f6b90ddc7b5 |
| training_args.bin | Weights | 10.1 KB | 6a9920a02b8e |
| config.json | Configuration | 1.6 KB | — |
| generation_config.json | Configuration | 210 B | — |
| trainer_state.json | Configuration | 109.7 KB | — |
| chat_template.jinja | Other | 4.2 KB | — |
| .gitattributes | Repository | 1.6 KB | — |
| tokenizer.json | Tokenizer | 11.4 MB | be75606093db |
| tokenizer_config.json | Tokenizer | 693 B | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 8.0 GB
Released by Yunjae Won through its official repository on Hugging Face.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 8.0 GB |
| 16-bit | 8.0 GB |
| 8-bit | 4.0 GB |
| 4-bit | 2.0 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About T14b_14bad_S4b_klreg0.05_treftemp_1.0_checkpoint20
How much GPU memory does T14b_14bad_S4b_klreg0.05_treftemp_1.0_checkpoint20 need?
About 9.7 GB at 16-bit and 2.4 GB at 4-bit: the weights (4B parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run T14b_14bad_S4b_klreg0.05_treftemp_1.0_checkpoint20 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.
What is T14b_14bad_S4b_klreg0.05_treftemp_1.0_checkpoint20's context length?
40,960 tokens, from the maximum position embeddings in its published configuration.