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LlamaIndex vs turbopuffer

turbopuffer scores higher on the AgentReady, 53/100 against 52/100. They differ on 6 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

LlamaIndex. LlamaIndex provides document parsing and extraction tools that turn complex documents into AI-ready context.

turbopuffer. turbopuffer is a fast, object-storage native search engine providing vector and full-text search built on object storage.

Where LlamaIndex is ahead

LlamaIndex passes structured api reference and limits / constraints documented, and turbopuffer does not. That is understand, whether an agent can read the docs and work out how the API behaves before calling it.

It also holds adopt: agent-compatible signup flow. turbopuffer misses it.

Where turbopuffer is ahead

turbopuffer passes clear product positioning, and LlamaIndex does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds adopt: no mandatory sales call. LlamaIndex misses it.

And on operate, structured, predictable output. LlamaIndex misses it.

What neither does

Both fail clear canonical domain, mcp discoverable, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented, programmatic credential creation, cli available, mcp integration available, 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. turbopuffer leads 80 to 67. LlamaIndex misses clear canonical domain, clear product positioning, mcp discoverable; turbopuffer misses clear canonical domain, mcp discoverable.

Understand is whether an agent can read the docs and work out how the API behaves before calling it. LlamaIndex leads 46 to 23. LlamaIndex misses openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented; turbopuffer misses structured api reference, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented.

Adopt. Both sit at 60/100 here. LlamaIndex misses no mandatory sales call, programmatic credential creation, cli available, mcp integration available; turbopuffer misses agent-compatible signup flow, programmatic credential creation, cli available, mcp integration available.

Operate. turbopuffer leads 47 to 35. LlamaIndex misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified; turbopuffer misses machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified.

Pricing

LlamaIndex starts at $0/mo and has a free tier. turbopuffer starts at $16/month with no free tier.

Signal by signal

Which to pick

Signal counts are level here, so fit and price decide it. Full profiles: LlamaIndex and turbopuffer. Alternatives to each: LlamaIndex, turbopuffer.

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