Model overview
The **Vietnamese Speech-to-Text (ASR)** model is built on the **ZipFormer architecture** — an improved variant of the Conformer — featuring only **30 million parameters** yet achieving **exceptional performance** in both speed and accuracy. On CPU, the model can transcribe a **12-second audio clip in just 0.3 seconds**, significantly faster than most traditional ASR systems without requiring a GPU. This model was trained entirely on **self-funded, personal hardware** — every GPU hour and electricity bill came out of my own pocket. If this work is useful to you, a small contribution helps cover the cost of the next training run and keeps future models free and open. Every coffee is hugely appreciated 🙏 You can try the model directly here: 👉 https://huggingface.co/spaces/hynt/k2-automatic-speech-recognition-demo
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.
Are these real-time billing prices?
These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.
Sources & traceability
许可证：cc-by-nc-nd-4.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。