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Update qdrant-cloud-inference-launch.md

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daniel-azoulai
2025-07-14 13:29:00 -07:00
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@@ -29,7 +29,7 @@ Traditionally, building application data pipelines means juggling separate embed
## Supported Models for Multimodal and Hybrid Search Applications
At launch, Qdrant Cloud Inference includes six curated models to start with. Choose from dense models like `all-MiniLM-L6-v2` for fast semantic matching, `mxbai/embed-large-v1` for richer understanding, or sparse models like `splade-pp-en-v1` and `bm25`. For multimodal workloads, Qdrant uniquely supports `OpenAI CLIP`-style models for both text and images.
At launch, Qdrant Cloud Inference includes six curated models to start with. Choose from dense models like `all-MiniLM-L6-v2` for fast semantic matching, `mxbai/embed-large-v1` for richer understanding, or sparse models like `splade-pp-en-v1` and `bm25` ([Check out this hybrid search tutorial to see it in action](https://qdrant.tech/documentation/tutorials-and-examples/cloud-inference-hybrid-search/)). For multimodal workloads, Qdrant uniquely supports `OpenAI CLIP`-style models for both text and images.
*Want to request a different model to integrate? You can do this at [https://support.qdrant.io/](https://support.qdrant.io/).*
@@ -66,4 +66,5 @@ We'll show you how to:
<li style="margin-bottom: 0;">Power multimodal (an industry first) and hybrid search with just one API</li>
<li style="margin-bottom: 0;">Reduce network egress fees and simplify your AI stack</li>
</ul>
[**Save your spot**](https://try.qdrant.tech/cloud-inference).