diff --git a/dev/benchmark/compare_tables.py b/dev/benchmark/compare_tables.py
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+++ b/dev/benchmark/compare_tables.py
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+#!/usr/bin/env python3
+"""Compare final sequence tables (seqtab / seqtab_nochim JSON) across runs.
+
+A standalone version of the ASV-table equivalence that bench_pooled.py reports
+in its WFA sweep CSV (`jaccard_vs_nw`, `count_frac_vs_nw`). Use it to compare any
+two+ runs' tables directly — e.g. nw vs wfa arms, k5 vs k7, two pool modes —
+without re-running a sweep.
+
+The `load_table` / `table_equiv` definitions are kept byte-for-byte identical to
+bench_pooled.py so the numbers here match that CSV exactly. (compare_asvs.py is
+the richer tool — abundance-stratified churn + nearest-neighbour Hamming — when
+you need to characterize *what* diverged; this one is the quick jaccard/count
+equivalence check.)
+
+Metrics (each comparison vs the baseline):
+  jaccard     — |shared ASVs| / |union ASVs| (sequence sets; 1.0 = same ASV set)
+  count_frac  — of the SHARED ASVs, fraction whose full per-sample count vector
+                is identical (the CSV's count_frac_vs_nw)
+  identical   — True iff same ASV set AND every per-sample count matches
+  +only / -only — ASVs the comparison has that the baseline lacks / vice-versa
+
+Usage:
+  compare_tables.py BASELINE=path/seqtab_nochim.json LABEL=path ... [--abundance N]
+
+  --abundance N  also report jaccard restricted to ASVs with total count >= N
+                 (mirrors the MIN_ABUNDANCE filter; default 1 = no filter)
+
+Example:
+  compare_tables.py \\
+      nw=tmp/pb_k7/nw/seqtab_nochim.json \\
+      e30=tmp/pb_k7/e30/seqtab_nochim.json \\
+      e0=tmp/pb_k7/e0/seqtab_nochim.json
+"""
+import json
+import sys
+
+
+def load_table(nochim_json):
+    """Load a make-sequence-table / remove-bimera-denovo JSON into a dict
+    {sequence -> {sample -> count}} (per-sample, order-independent). Returns None
+    if the file is missing/unreadable."""
+    try:
+        with open(nochim_json) as fh:
+            d = json.load(fh)
+        samples, seqs, counts = d["samples"], d["sequences"], d["counts"]
+    except (OSError, ValueError, KeyError):
+        return None
+    # counts[i][j] = sample i, sequence j
+    table = {}
+    for j, seq in enumerate(seqs):
+        table[seq] = {samples[i]: counts[i][j] for i in range(len(samples))}
+    return table
+
+
+def table_equiv(a, b):
+    """Compare two {seq -> {sample -> count}} tables. Returns
+    (jaccard, exact_frac, identical) where jaccard is over the ASV sequence sets,
+    exact_frac is the fraction of shared ASVs whose full per-sample count vector
+    matches, and identical is True iff the tables are byte-equal (same ASV set
+    AND every count). None-safe: returns (None, None, None) if either is None."""
+    if a is None or b is None:
+        return (None, None, None)
+    sa, sb = set(a), set(b)
+    union = sa | sb
+    shared = sa & sb
+    jaccard = 1.0 if not union else len(shared) / len(union)
+    exact = sum(1 for s in shared if a[s] == b[s])
+    exact_frac = 1.0 if not shared else exact / len(shared)
+    identical = (sa == sb) and all(a[s] == b[s] for s in shared)
+    return (jaccard, exact_frac, identical)
+
+
+def total_count(table):
+    """ASV -> summed-over-samples count, for abundance filtering."""
+    return {seq: sum(per.values()) for seq, per in table.items()}
+
+
+def filter_abundance(table, min_abund):
+    if min_abund <= 1:
+        return table
+    tot = total_count(table)
+    return {s: table[s] for s in table if tot[s] >= min_abund}
+
+
+def main(argv):
+    # Parse --abundance[=N | N] first, then treat the rest as LABEL=path specs.
+    args, min_abund = [], 1
+    it = iter(argv[1:])
+    for a in it:
+        if a.startswith("--abundance"):
+            min_abund = int(a.split("=", 1)[1]) if "=" in a else int(next(it))
+        else:
+            args.append(a)
+    specs = [a for a in args if "=" in a]
+    if len(specs) < 2:
+        sys.exit(f"usage: {argv[0]} BASELINE=path LABEL=path [...] [--abundance N]")
+
+    base_label, base_path = specs[0].split("=", 1)
+    base = load_table(base_path)
+    if base is None:
+        sys.exit(f"baseline {base_label} ({base_path}) unreadable")
+    base_f = filter_abundance(base, min_abund)
+
+    width = max(len(s.split("=", 1)[0]) for s in specs)
+    af = f" (abundance>={min_abund})" if min_abund > 1 else ""
+    print(f"baseline: {base_label} = {base_path}  ({len(base_f)} ASVs{af})\n")
+    hdr = (f"{'label':>{width}}  {'ASVs':>6} {'jaccard':>8} {'count_frac':>11} "
+           f"{'+only':>6} {'-only':>6} {'identical':>9}")
+    print(hdr)
+    print("-" * len(hdr))
+    for spec in specs[1:]:
+        label, path = spec.split("=", 1)
+        t = load_table(path)
+        if t is None:
+            print(f"{label:>{width}}  <unreadable: {path}>")
+            continue
+        tf = filter_abundance(t, min_abund)
+        jac, cnt, ident = table_equiv(base_f, tf)
+        plus = len(set(tf) - set(base_f))   # ASVs in comparison not in baseline
+        minus = len(set(base_f) - set(tf))  # ASVs in baseline not in comparison
+        print(f"{label:>{width}}  {len(tf):>6} {jac:>8.4f} {cnt:>11.4f} "
+              f"{plus:>6} {minus:>6} {str(ident):>9}")
+
+
+if __name__ == "__main__":
+    main(sys.argv)