sn56-p2-FE3-CTL-f4920bf7 is an open-weight model from Zaydens. It has 521M parameters and a 16,384-token context. At 16-bit it needs about 1.3 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.
Research artefact of SN56 text tournament replay; validator-style round-trip. The other files are the trainer's output directory, uploaded unchanged.
Runs On
What it takes to serve sn56-p2-FE3-CTL-f4920bf7 (521M 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 | 1.0 GB | 1.3 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 0.5 GB | 0.6 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 0.3 GB | 0.3 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.
sn56-p2-FE3-CTL-f4920bf7 on every accelerator the SAVRN Index prices, at every precision
Model Card
Research artefact of SN56 text tournament replay; validator-style round-trip. The other files are the trainer's output directory, uploaded unchanged. The repo is downloaded again and scored on the task's held-out rows to check that the Hub copy scores exactly as the local copy did.
Excerpt from the card by Zaydens.
Configuration
- Architecture
- FalconH1ForCausalLM
- Context length (tokens)
- 16,384
- Layers
- 36
- Hidden size
- 1,024
- Feed-forward size
- 2,048
- Attention heads
- 8
- Key/value heads
- 2
- Head dimension
- 64
- Vocabulary size
- 32,784
- Model type
- falcon_h1
Identity and Version
- Repository
- zaydens/sn56-p2-FE3-CTL-f4920bf7
- Publisher
- Zaydens
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 521M parameters
- Languages
- Not stated by the source
- Revision
- 0d7ce46149a8c5bf5bf43ff47a5dc89ddb763f8f
- First published
- 2026-10-12
- Last updated
- 2026-10-12
Files and Weights
9 files, 1.0 GB in total. The weights are 1 file totalling 1.0 GB in safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.safetensors | Weights | 1.0 GB | baae3a562972 |
| config.json | Configuration | 1.7 KB | — |
| generation_config.json | Configuration | 123 B | — |
| trainer_state.json | Configuration | 12.2 KB | — |
| README.md | Documentation | 442 B | — |
| loss.txt | Other | 12 B | — |
| .gitattributes | Repository | 1.5 KB | — |
| tokenizer.json | Tokenizer | 2.4 MB | — |
| tokenizer_config.json | Tokenizer | 351 B | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 1.0 GB
Released by Zaydens through its official repository on Hugging Face.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 1.0 GB |
| 16-bit | 1.0 GB |
| 8-bit | 0.5 GB |
| 4-bit | 0.3 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About sn56-p2-FE3-CTL-f4920bf7
How much GPU memory does sn56-p2-FE3-CTL-f4920bf7 need?
About 1.3 GB at 16-bit and 0.3 GB at 4-bit: the weights (521M parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run sn56-p2-FE3-CTL-f4920bf7 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 sn56-p2-FE3-CTL-f4920bf7's context length?
16,384 tokens, from the maximum position embeddings in its published configuration.