sn92-df-q9-both-s2.0-g is a model from Ana Conda (access requested at publisher). It has 9B parameters. At 16-bit it needs about 21.5 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 sn92-df-q9-both-s2.0-g (9B 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 | 17.9 GB | 21.5 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 9.0 GB | 10.7 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 4.5 GB | 5.4 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 18, 2026.
sn92-df-q9-both-s2.0-g on every accelerator the SAVRN Index prices, at every precision
Model Card
The publisher has not written a card for this model.
Identity and Version
- Repository
- 0xbidkslj1/sn92-df-q9-both-s2.0-g
- Publisher
- Ana Conda
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 9B parameters
- Languages
- Not stated by the source
- Revision
- 105b73b25b933cba527b43065600a727db28c8e1
- First published
- 2026-10-16
- Last updated
- 2026-10-16
Files and Weights
11 files, 17.9 GB in total. The weights are 4 files totalling 17.9 GB in safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model-00001-of-00004.safetensors | Weights | 4.9 GB | — |
| model-00002-of-00004.safetensors | Weights | 5.0 GB | — |
| model-00003-of-00004.safetensors | Weights | 5.0 GB | — |
| model-00004-of-00004.safetensors | Weights | 3.0 GB | — |
| config.json | Configuration | 1.9 KB | — |
| model.safetensors.index.json | Configuration | 42.1 KB | — |
| reax-specialist.json | Configuration | 238 B | — |
| LICENSE | Documentation | 11.5 KB | — |
| .gitattributes | Repository | 1.6 KB | — |
| tokenizer.json | Tokenizer | 20.0 MB | — |
| tokenizer_config.json | Tokenizer | 1.4 KB | — |
License and Download
- License
- Not stated by the source
- Access
- Access requested at publisher
- Download size
- 17.9 GB
Ana Conda grants access through its official repository on Hugging Face.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 17.9 GB |
| 16-bit | 17.9 GB |
| 8-bit | 9.0 GB |
| 4-bit | 4.5 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About sn92-df-q9-both-s2.0-g
How much GPU memory does sn92-df-q9-both-s2.0-g need?
About 21.5 GB at 16-bit and 5.4 GB at 4-bit: the weights (9B parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run sn92-df-q9-both-s2.0-g 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.