Text2vec Base Chinese
Embedding model by Shibing624.
shibing624 dense vector embedding model. Transforms natural language text into rich semantic embeddings for search and retrieval.
Context window
Maximum input context length.
512
Maker
Shibing624
Specifications
Context window, ranked against other embedding models
Proportional scale: 0 to 8.2K tokens. Not ranked, no published context window: text-embedding-3-large.
512
tokens—
embedding
Pricing
Rates are read live
Pricing for shibing624/text2vec-base-chinese is fetched from the live catalogue on load, so it is never served from a cache that could outlive a repricing.
Availability
Not enough data yet
We have not collected enough health probes for this model to publish an uptime or latency figure. A percentage from a handful of samples is fabricated precision, so none is shown until the sample count supports one.
How Text2vec Base Chinese is billed
Billed at the provider's list price, with no per-token markup.
- Exact list price
- Tokens settle at the published rate of the model that served your call.
- Cache discounts passed through
- Provider prompt-caching discounts reach your balance with no added fee.
- Cost on every response
- Each response carries the
x-nr-request-costheader, so you can reconcile spend per request.
FAQs
What is Text2vec Base Chinese?
shibing624 dense vector embedding model. Transforms natural language text into rich semantic embeddings for search and retrieval.
How much does Text2vec Base Chinese cost?
Text2vec Base Chinese is billed at the provider's list price on nRouter with no per-token markup — tokens settle at the exact upstream rate. Input and output rates are read live, so see the pricing section above for the current figures.
What is the context length of Text2vec Base Chinese?
Text2vec Base Chinese supports a 512-token context window.
Does Text2vec Base Chinese support tool calling and structured outputs?
No. Text2vec Base Chinese does not support tool calling, so it cannot invoke external tools or functions.
What inputs and outputs does Text2vec Base Chinese support?
Text2vec Base Chinese is an embedding model: it takes text as input and returns vector embeddings as output.
How do I use Text2vec Base Chinese via nRouter?
Use any OpenAI-compatible client: point it at https://api.nrouter.ai/v1 with your nRouter API key and set the model to "deepinfra/shibing624/text2vec-base-chinese".
When was Text2vec Base Chinese released?
Text2vec Base Chinese was released on October 7, 2026.
Where is the Text2vec Base Chinese documentation?
Start at nrouter.ai/docs. The quick-start guide (nrouter.ai/docs/getting-started/quick-start) covers API keys and your first request, and the API reference (nrouter.ai/docs/api-reference) lists every parameter.