HydraQE is an open-weight model from Ohio State Speech and Language Technologies Lab, released under Apache License 2.0. It has 214M parameters. At 16-bit it needs about 0.5 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 HydraQE (214M 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 | 0.4 GB | 0.5 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 23, 2026.
HydraQE on every accelerator the SAVRN Index prices, at every precision
Model Card
Identity and Version
- Repository
- osu-slatelab/HydraQE
- Publisher
- Ohio State Speech and Language Technologies Lab
- Task
- Not stated by the source
- Modality
- Other
- Library
- hydraqe
- Parameters
- 214M parameters
- Languages
- en, de, zh
- Revision
- 5c93fcb7ef8fed6dbdca98f8606ac55852584ebf
- First published
- 2026-10-22
- Last updated
- 2026-10-22
License and Download
- License
- apache-2.0
- Access
- Open weights, no gate
Released by Ohio State Speech and Language Technologies Lab through its official repository on Hugging Face. Read the license.
Built From
- Adapter of Qwen/Qwen3-ASR-1.7B
- Derived from Qwen/Qwen3-ASR-1.7B
- Trained on (disclosed) maikezu/iwslt2026-metrics-shared-train-dev
Memory Requirements
| Precision | Weights in memory |
|---|---|
| 16-bit | 0.4 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 HydraQE
How much GPU memory does HydraQE need?
About 0.5 GB at 16-bit and 0.1 GB at 4-bit: the weights (214M parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run HydraQE 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.
Can I use HydraQE commercially?
Yes. HydraQE is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.