Model overview
**Word-level forced alignment for OpenASR transcripts -- a non-autoregressive Qwen3 audio+text model that refines per-word timestamps** A capability-pack support model for the **OpenASR** runtime — pure-Rust inference, **no Python at inference time**. Not a standalone transcription model: it augments another OpenASR ASR model's own decode path. Qwen3-ForcedAligner-0.6B is a **word-level forced-alignment** model from **Qwen**, sharing its audio-encoder + LM `thinker` tensor layout byte-for-byte with **Qwen3-ASR** (same `Qwen3ASRForConditionalGeneration` architecture). The only structural difference is the final head: instead of a tied vocabulary `lm_head`, it uses an independent `Linear(hidden_size, 5000)` classification head over 80ms-wide timestamp bins. Given a transcript's text and its source audio, it runs a single non-autoregressive forward pass and reads off word-boundary timestamps at argmax ` ` positions -- refining a model family's own (typically decode-time-approximate) per-word timestamps. This OpenASR repo repackages the weights as `.oasr` packs that run natively in the OpenASR runtime -- no Python at inference, all decoding local. OpenASR recommends the validated **q4_k** tier and also ships **q8_0** and an **fp16** full-precision reference tier. The q4_k label is the catalog's unified product name, not a claim that every matrix uses Q4_K: the audio encoder, token embedding, and timestamp head remain Q8_0, and pack verification replays the exact per-tensor policy. Q3 and legacy all-Q4 packs are rejected because small logit perturbations can move a word boundary across multiple 80ms bins.
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：apache-2.0。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。