Clip ViT B 32
Embedding model by Sentence Transformers.
sentence-transformers dense vector embedding model. Transforms natural language text into rich semantic embeddings for search and retrieval.
Context window
Maximum input context length.
77
Maker
Sentence Transformers
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.
77
tokens—
embedding
Pricing
Rates are read live
Pricing for sentence-transformers/clip-ViT-B-32 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 Clip ViT B 32 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 Clip ViT B 32?
sentence-transformers dense vector embedding model. Transforms natural language text into rich semantic embeddings for search and retrieval.
How much does Clip ViT B 32 cost?
Clip ViT B 32 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 Clip ViT B 32?
Clip ViT B 32 supports a 77-token context window.
Does Clip ViT B 32 support tool calling and structured outputs?
No. Clip ViT B 32 does not support tool calling, so it cannot invoke external tools or functions.
What inputs and outputs does Clip ViT B 32 support?
Clip ViT B 32 is an embedding model: it takes text as input and returns vector embeddings as output.
How do I use Clip ViT B 32 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/sentence-transformers/clip-ViT-B-32".
When was Clip ViT B 32 released?
Clip ViT B 32 was released on October 7, 2026.
Where is the Clip ViT B 32 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.