ai2026_1005 is an open-weight model from ChanwooKim. It has 3.1B parameters. At 16-bit it needs about 7.5 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 ai2026_1005 (3.1B 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 | 6.3 GB | 7.5 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 3.1 GB | 3.8 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 1.6 GB | 1.9 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 Oct 22, 2026.
ai2026_1005 on every accelerator the SAVRN Index prices, at every precision
Model Card
The publisher has not written a card for this model.
Configuration
- Architecture
- Gr00tN1d7
- Hidden size
- 1,024
- Model type
- Gr00tN1d7
Identity and Version
- Repository
- chanwoochan/ai2026_1005
- Publisher
- ChanwooKim
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 3.1B parameters
- Languages
- Not stated by the source
- Revision
- 1e93958144908043614264fdaadce058419b91ae
- First published
- 2026-10-05
- Last updated
- 2026-10-05
Files and Weights
16 files, 12.6 GB in total. The weights are 4 files totalling 12.6 GB in bin, safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model-00001-of-00003.safetensors | Weights | 5.0 GB | cbcaea5ee88f |
| model-00002-of-00003.safetensors | Weights | 5.0 GB | 356fa0e84c7a |
| model-00003-of-00003.safetensors | Weights | 2.6 GB | e5bd10866109 |
| training_args.bin | Weights | 5.9 KB | 2fa5ab35e868 |
| config.json | Configuration | 2.1 KB | — |
| experiment_cfg/conf.yaml | Configuration | 6.0 KB | — |
| experiment_cfg/config.yaml | Configuration | 7.5 KB | — |
| experiment_cfg/dataset_statistics.json | Configuration | 22.0 KB | — |
| experiment_cfg/final_model_config.json | Configuration | 1.5 KB | — |
| experiment_cfg/final_processor_config.json | Configuration | 2.5 MB | — |
| model.safetensors.index.json | Configuration | 104.9 KB | — |
| processor/embodiment_id.json | Configuration | 2.2 KB | — |
| processor/processor_config.json | Configuration | 28.0 KB | — |
| processor/statistics.json | Configuration | 4.3 MB | — |
| wandb_config.json | Configuration | 61 B | — |
| .gitattributes | Repository | 1.5 KB | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 12.6 GB
Released by ChanwooKim through its official repository on Hugging Face.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 12.6 GB |
| 16-bit | 6.3 GB |
| 8-bit | 3.1 GB |
| 4-bit | 1.6 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About ai2026_1005
How much GPU memory does ai2026_1005 need?
About 7.5 GB at 16-bit and 1.9 GB at 4-bit: the weights (3.1B parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run ai2026_1005 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.