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Google Gemini vs Vespa

Vespa scores higher on the AgentReady, 56/100 against 35/100. They differ on 16 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Google Gemini. Gemini is Google's AI assistant and conversational AI model.

Vespa. Vespa.ai develops the Vespa AI Search Platform, a distributed serving engine that unifies retrieval, ranking, machine learning inference, and real-time serving for business-critical AI applications.

Where Google Gemini is ahead

Google Gemini passes mcp discoverable, and Vespa does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: authentication documented. Vespa misses it.

And on adopt, mcp integration available. Vespa misses it.

Where Vespa is ahead

Vespa passes clear canonical domain, clear product positioning, public docs discoverable, llms.txt published and llms-full.txt / full agent docs, and Google Gemini does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: structured api reference, pricing understandable and limits / constraints documented. Google Gemini misses those.

And on adopt, self-service signup, free trial or free allowance, fast time to first request and copyable quickstart. Google Gemini misses those.

Finally, on operate, observable execution. Google Gemini misses it.

What neither does

Both fail openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified. If your agent needs any of those, you will be building it yourself either way.

Score, pillar by pillar

The AgentReady splits into four pillars, scored separately, because a product can be easy to find and still impossible to adopt.

Discover is whether an agent can find the product at all without being told it exists. Vespa leads 87 to 53. Google Gemini misses clear canonical domain, clear product positioning, public docs discoverable, llms.txt published, llms-full.txt / full agent docs; Vespa misses mcp discoverable.

Understand. Vespa leads 46 to 23. Google Gemini misses structured api reference, openapi / spec quality, pricing understandable, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented; Vespa misses openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented.

Adopt. Vespa leads 55 to 40. Google Gemini misses self-service signup, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, free trial or free allowance, fast time to first request, copyable quickstart; Vespa misses no mandatory sales call, agent-compatible signup flow, programmatic credential creation, mcp integration available.

Operate. Vespa leads 35 to 24. Google Gemini misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, observable execution, agent compatibility verified; Vespa misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified.

Pricing

Google Gemini does not publish a machine-readable starting price. Vespa starts at $0.05/hour with no free tier.

Signal by signal

Which to pick

Vespa clears more of the signals an agent needs, so it is the safer default for unattended use. Full profiles: Google Gemini and Vespa. Alternatives to each: Google Gemini, Vespa.

An agent can fetch this as data: POST /v1/compare {"slugs": ["gemini", "vespa"]}