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+# Benchmark Matrix v1.2 — internal results
+
+Run: 2026-06-12 evening. Local, zero API spend (answerer `claude:claude-haiku-4-5`,
+judge `claude:claude-sonnet-4-6` via plan; mem0/embeddings via local Ollama).
+
+**BM under test: `main` @ d46c6880** (before the FTS-revival fix, PR #994).
+mem0 run in raw-add mode (`MEM0_INFER` unset → `infer=false`); see fairness note.
+
+## QA accuracy (the headline metric)
+
+| Benchmark | bm-local | mem0-local | baseline-grep | baseline-fullcontext |
+|---|---|---|---|---|
+| LongMemEval-S (n=60, stratified 6 cats) | **0.617** | 0.417 | 0.300 | 0.217 |
+| ConvoMem cs10 (n=274) | 0.792 | 0.474 | 0.398 | **0.825** |
+
+## Retrieval (deterministic)
+
+| Benchmark | provider | recall@5 | MRR | content-hit | mean lat |
+|---|---|---|---|---|---|
+| LongMemEval-S | bm-local | 0.951 | 0.900 | 0.467 | 754ms |
+| LongMemEval-S | mem0-local | 0.979 | 0.876 | 0.500 | 146ms |
+| LongMemEval-S | baseline-grep | 0.846 | 0.832 | 0.350 | 5ms |
+| ConvoMem cs10 | bm-local | 0.982 | 0.929 | 0.128 | 140ms |
+| ConvoMem cs10 | mem0-local | 0.996 | 0.956 | 0.131 | 122ms |
+| ConvoMem cs10 | baseline-grep | 0.954 | 0.863 | 0.062 | 1ms |
+
+(full-context retrieval metrics are N/A by design — single whole-corpus hit.)
+
+## Findings
+
+1. **BM leads QA accuracy on LongMemEval-S and is a close 2nd on ConvoMem**,
+   despite mem0 edging it on retrieval recall. BM's retrieved chunks are more
+   answer-bearing: mem0 abstains far more (LME 30/60, ConvoMem 169/274 vs BM
+   20/60, 86/274). Retrieval recall ≠ answer quality.
+
+2. **Full-context is a poor baseline at small-model scale.** On LongMemEval-S
+   (~124K-token haystacks, 496K-char assembled context) qwen2.5:3b-class
+   answering drops to 0.217 — it cannot use the whole haystack and abstains.
+   On the smaller ConvoMem cs10 it wins (0.825). Confirms the published
+   pattern: full-context beats retrieval only while the corpus fits the
+   model's effective working window.
+
+3. **mem0 raw-add caveat (fairness).** mem0's published numbers use
+   `infer=true` (LLM fact extraction). We ran raw-add to match the June 10
+   baseline and avoid a local-3B extraction step of unknown quality. A future
+   matrix should run mem0 both ways and report both, with the extraction model
+   documented.
+
+## PR #994 (FTS-revival) impact — corrected LoCoMo
+
+Two measurements, each stating exactly what it covers:
+
+**Retrieval — full 1,986-query set, same pre-built index, code-only A/B**
+(`/tmp/replay_fusion.py` against `matrix-locomo-v2-full`'s index). Definitive.
+
+| metric | BM main | BM #994 | Δ |
+|---|---|---|---|
+| recall@5 | 0.745 | 0.823 | **+7.9** |
+| MRR | 0.618 | 0.718 | **+10.0** |
+
+Every category improves; largest on adversarial (+0.12 r5) and open_domain
+(+0.095 r5), smallest on temporal (+0.003).
+
+**QA accuracy — q300 non-adversarial subset, fresh re-index, full QA stage**
+(`m994-locomo-q300` vs `matrix-locomo-v2-q300`).
+
+| | BM main | BM #994 | Δ |
+|---|---|---|---|
+| accuracy | 0.439 | **0.475** | **+3.7** |
+| abstain | 95 | 87 | -8 |
+
+By category (correct/total): open_domain 105→112, single_hop 18→23,
+multi_hop 4→5, temporal 5→3 (n=19, noise).
+
+The QA gain is smaller than the retrieval gain because the largest retrieval
+improvements land in the adversarial category (excluded from QA-meaningful
+scoring) and **multi_hop stays ~0.08 — bottlenecked by a separate gap, not
+FTS**: BM returns bullet-level matched chunks that strip document-level
+context (the session date lives in the title). That is the next product fix.
+
+## Pending
+- supermemory-local provider validated against the real server but not yet in
+  a matrix run (Ollama extraction hits upstream issue #1096; needs the
+  Responses→ChatCompletions shim).