[
Vespa.ai Reviews
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[
Vespa.ai Reviews
](https://www.g2.com/products/vespa-ai/reviews)

# Vespa.ai Pricing Overview

[Editedit](https://my.g2.com/vespa-ai/pricings)

Free Trial

**Vespa.ai has not provided pricing information for this product or service.** This is common practice for software sellers and service providers. Contact Vespa.ai to obtain current pricing.

Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. 

Pricing information for Vespa.ai is supplied by the software provider or retrieved from publicly accessible pricing materials. Final cost negotiations to purchase Vespa.ai must be conducted with the seller.
https://vespa.ai/pricing/

Pricing information was last updated on June 16, 2026

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## Vespa.ai Pricing Reviews
(1)

 ![Verified User in Automotive](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Automotive")
UA

Verified User in Automotive

Enterprise (\> 1000 emp.)

12/18/2024

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"Powerful backend for vector and hybrid search with many bells and whistles."

3.5/5

What do you like best about Vespa.ai?

We purchased the Enclave product which was really well-suited for us because it let us run the hosts in our own Google cloud account (at our pricing with Google), and thus didn't require us to transfer any data out which was well-aligned with our security stance. It provided light-touch deployment and observability services that we lacked and helped us bootstrap quickly and with minimal investment.

The Vespa search backend itself provided a good match to our requirements of near-real time hybrid search, combining nearest neighbor embedding search with attribute filters, in a distributed and highly scalable way. Our target installation comprised \>12TB of memory across 24 hosts and held O(1B) vector embeddings. Review collected by and hosted on G2.com.

What do you dislike about Vespa.ai?

Vespa, in a scalable deployment, presents a fairly complex architecture with a lot of tuning knobs and bells and whistles. It took several months to get familiar with them. The Vespa consultant was very instrumental in this. Feeding Vespa from BigQuery was harder than expected.

Native extensions can only be written in Java which, without a native Java toolchain at our company, proved too challenging to pursue. The documentation is vast but could be better organized and have more contextual examples in places. Review collected by and hosted on G2.com.

What problems is Vespa.ai solving and how is that benefiting you?

We used the Vespa search backend for hybrid search, consisting of nearest neighbor search of indexed embeddings vectors and attribute filters. This powered a natural-language image search product for our internal users. Review collected by and hosted on G2.com.

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Validated ReviewerSource: Organic

##### Categories on G2

[
AI Search & Retrieval Infrastructure Platforms
](https://www.g2.com/categories/ai-search-retrieval-infrastructure-platforms)[
Vector Database
](https://www.g2.com/categories/vector-database)

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