WaveMind Living Benchmark Dashboard

Generated from checked-in benchmark artifacts. Planned rows are not claimed wins; external service evidence is shown separately.

Readiness

pass

36/36 criteria pass

Implemented

26

2 runner-ready and 6 planned public proof paths

Refresh

2026-07-07T09:19:54Z

source bfa60e31b87fe08bcdc4ec87e7bedc737bee8049

Visual Summary

WaveMind benchmark summary

Benchmark Leaderboard

benchmark category primary metric best WaveMind result best baseline result readout
Agent user-memory retrieval agent-memory precision@1 WaveMind: 0.82 / 2.249 ms Chroma: 0.82 / 0.933 ms Quality tie; WaveMind slower
Agent coherence and token savings agent-memory task success WaveMind: 0.917 / 2.12 ms Static vector: 0.333 / 0.39 ms WaveMind leads on quality
Dynamic memory policy agent-memory precision@1 WaveMind: 1 / 4.81 ms Chroma static: 0.571 / 1.756 ms WaveMind leads on quality
Field memory graph dynamics agent-memory precision@1 WaveMind graph: 1 / 0.374 ms - WaveMind-only check
WaveMind capacity curve capacity precision@1 WaveMind dynamic capacity: 1 / 48.4 ms - WaveMind-only check
Long-term memory evidence long-term-agent-memory evidence recall@k WaveMind: 1 / 6.103 ms Static vector: 1 / 0.648 ms Quality tie; WaveMind slower
BEIR-style open retrieval runner retrieval precision@1 WaveMind: 0.24 / 117.0 ms Chroma: 0.243 / 1.794 ms Baseline leads on quality
NoMIRACL Russian retrieval multilingual-retrieval precision@1 WaveMind: 0.41 / 10.2 ms Chroma: 0.41 / 2.603 ms Quality tie; WaveMind slower
LoCoMo evidence retrieval runner long-term-conversation-memory evidence recall@k WaveMind sentence: 0.547 / 3.438 ms Qdrant sentence: 0.409 / 124.3 ms WaveMind leads on quality
LongMemEval evidence retrieval long-term-agent-memory evidence recall@k WaveMind: 0.782 / 7.274 ms Static vector: 0.52 / 0.083 ms WaveMind leads on quality
LongMemEval evidence 50-query smoke long-term-agent-memory evidence recall@k WaveMind: 0.92 / 15.3 ms Static vector: 0.6 / 0.337 ms WaveMind leads on quality
ANN index latency curve index-latency Recall@k WaveMind numpy: 1 / 6.485 ms Qdrant local: 1 / 43.5 ms Quality tie; WaveMind faster
Production index profile index-latency Recall@k WaveMind faiss-persisted: 1 / 3.524 ms Qdrant service: 1 / 4.414 ms Quality tie; WaveMind faster
Production pgvector tuning profile index-latency Recall@k WaveMind pgvector-exact: 1 / 55.7 ms Qdrant service: 1 / 9.137 ms Quality tie; WaveMind slower
Production load profile 100k production-scale Recall@k WaveMind pgvector: 0.736 / 17.8 ms Qdrant service: 1 / 10.3 ms Baseline leads on quality; production SLO pass: Qdrant service; cost: Qdrant service $1.39/1M queries
Production load profile 1M production-scale Recall@k WaveMind faiss-persisted: 1 / 39.1 ms Qdrant service: 0.984 / 82.6 ms WaveMind leads on quality; production SLO needs scale: WaveMind faiss-persisted; cost: WaveMind faiss-persisted $4.17/1M queries
Qdrant 1M HNSW ef sweep production-scale Recall@k - hnsw_ef=2048: 0.977 / 64.8 ms No WaveMind result; production SLO miss; cost if SLO fixed: hnsw_ef=512 $4.86/1M queries
Production streaming load runner production-scale Recall@k 10k smoke / WaveMind numpy-streaming: 1 / 0.168 ms Qdrant sharded smoke / Qdrant sharded service streaming: 1 / 2.945 ms Quality tie; WaveMind faster; production SLO pass: 10k smoke / WaveMind numpy-streaming; cost: 10k smoke / WaveMind numpy-streaming $0.69/1M queries
Scale readiness profile production-scale precision@1 WaveMind structured payloads: 1 / 0.414 ms - WaveMind-only check
Production readiness gate production-scale readiness score WaveMind production readiness: 1 / - - WaveMind-only check
Memory competitor adapter profile agent-memory precision@1 WaveMind: 0.8 / 3.088 ms GraphRAG static graph: 1 / 0.013 ms Baseline leads on quality
LongMemEval answer generation long-term-agent-memory token F1 WaveMind + qwen2.5:1.5b: 0.333 / - Chroma static + qwen2.5:1.5b: 0.17 / - WaveMind leads on quality

Evidence Source Status

area current source claim status next action
Artifact freshness weekly-fast matrix refresh at 2026-07-07T09:19:54Z source bfa60e31b87fe08bcdc4ec87e7bedc737bee8049; audit gate enforced by validate_benchmark_artifacts.py Keep weekly refresh green before public claims.
Serverless telemetry loopback API pool; loopback-api-capacity-estimate; 4 measured replicas observed SLO True; loopback evidence, not a managed-serverless claim Run .github/workflows/serverless-observed-telemetry.yml against deployed API nodes.
External HTTP cluster load local-loopback; loopback-api-processes; 4 nodes SLO True; local loopback service-node evidence Run .github/workflows/external-http-cluster-load.yml with a remote node manifest.
External HTTP active-active no checked-in remote region artifact action required before remote active-active production claim Run .github/workflows/external-http-active-active.yml with a remote region manifest.
pgvector tuning real PostgreSQL/pgvector service profile at 50k vectors iterative recall 0.97, iterative p99 55.2 ms; exact recall 1 Promote pgvector-iterative into the 100k and 1M production load SLO profiles.
10M streaming load local WaveMind faiss-ivfpq-persisted streaming profile target recall 0.99, p99 60.1 ms, SLO scale_required Repeat at 50M and add service-backed Qdrant/pgvector 10M artifacts.
50M streaming preflight WaveMind faiss-ivfpq-persisted streaming plan-only contract action_required; index 1.12 GB; app storage 119.2 GB; blockers missing_env:WAVEMIND_FAISS_IVFPQ_PATH Run .github/workflows/production-streaming-load.yml with faiss-ivfpq-persisted and publish benchmarks/production_streaming_load_ivfpq_50m_results.json.
Qdrant streaming real Qdrant service smoke plus 10M preflight smoke recall 1, smoke p99 17.9 ms; 10M preflight action_required Run .github/workflows/production-streaming-load.yml with qdrant-service against sized Qdrant storage.
Qdrant sharded streaming real two-service fanout smoke plus horizontal Qdrant preflight smoke recall 1, smoke p99 3.333 ms; 10M preflight action_required; 100M preflight action_required; planned shards 4; blockers missing_env:WAVEMIND_QDRANT_URLS Run .github/workflows/production-streaming-load.yml with qdrant-sharded-service and publish benchmarks/production_streaming_load_qdrant_sharded_10m_results.json or benchmarks/production_streaming_load_qdrant_sharded_100m_results.json.
Qdrant 1M streaming real Qdrant service run before and after warmup/chunking tuning cold p99 3014.0 ms; tuned recall 1, tuned p99 26.4 ms, SLO pass Use the tuned warmup/chunking profile for the 10M Qdrant service run.
pgvector streaming real PostgreSQL/pgvector service smoke plus 10M preflight smoke recall 1, smoke p99 7.624 ms; 10M preflight action_required Run .github/workflows/production-streaming-load.yml with pgvector-service against sized Postgres storage.
Production readiness gate checked-in benchmark artifacts pass; 36/36 pass Keep the gate at readiness_score 1.0 while repeating larger service-backed runs and moving external competitor evidence into the separate adapter profile.
Competitor adapters checked local adapters plus optional external services configured 4; skipped Zep Configure skipped external services before claiming full competitor coverage.

Reading Rules

Quality wins and latency wins are separate. A row can lead on recall while still being slower.

WaveMind-only rows are regression and capacity checks, not competitor claims.

Production SLO rows use checked recall, p99, QPS, replica count, autoscaling, and cost assumptions.

Remote active-active, managed serverless, and live competitor rows stay marked as external evidence until real service artifacts are checked in.