KB Arena

Compare retrieval architectures on the same documentation and questions, then choose from recorded quality, latency, cost, and limits.

How it works

1

Same question

Send each question, from direct lookups to multi-topic chains, to the selected strategies.

2

4-pass evaluation

Structural checks, entity coverage, source attribution against your docs, then LLM-as-judge scoring.

3

Ranked report

Accuracy by tier, latency percentiles, reliability rates, and cross-strategy composite ranking across your documentation.

Strategy catalog

Naive Vector

Chunks documents, embeds each chunk, and retrieves top-k by cosine similarity as a dense baseline.

Runtime status unavailable

Contextual Vector

Prepends parent topic context to each chunk before embedding so you can measure whether document context changes retrieval.

Runtime status unavailable

QnA Pairs

Generates question-answer pairs at index time and retrieves against those pairs instead of only source chunks.

Runtime status unavailable

Knowledge Graph

Extracts entities and relationships into Neo4j, then queries the graph through intent-matched Cypher templates.

Runtime status unavailable

Hybrid

Routes by intent between vector and graph paths, then uses reciprocal rank fusion when both paths contribute.

Runtime status unavailable

RAPTOR

Builds a recursive tree of chunk clusters and summaries, then queries leaf and summary levels together.

Runtime status unavailable

PageIndex

Builds a hierarchical tree from document structure and uses model-guided traversal without an embedding index.

Runtime status unavailable

BM25

Uses BM25 keyword matching as a keyless lexical baseline with no embeddings or graph service.

Runtime status unavailable

Rerank Vector

Naive Vector retrieves a wide candidate pool, then a cross-encoder reranker (BGE, Cohere, or Voyage) rescores and keeps the top-k for a measured latency-quality tradeoff.

Runtime status unavailable

QISS (quantum)

Rescores dense candidates with a pure-NumPy state-fidelity calculation and offers an experimental multi-query mode.

Runtime status unavailable | Experimental

SQR (optional quantum)

Experimental Qiskit Aer SWAP-test reranker. It is excluded from the default benchmark and needs the optional quantum dependency group.

Runtime status unavailable | Experimental

5 difficulty tiers, auto-generated or hand-crafted

AWS Compute

Not labeled

Tier 1: FactoidTier 2: ProceduralTier 3: ComparativeTier 4: RelationalTier 5: Multi-hop

Built with

Python 3.11+Pydantic v2FastAPINeo4j 5ChromaDBAnthropic ClaudeOpenAI EmbeddingsNext.js 16Tailwind CSSRecharts