diff --git a/benchmarks/baselines/ablations.py b/benchmarks/baselines/ablations.py
index 62e9504e6..894208bbe 100644
--- a/benchmarks/baselines/ablations.py
+++ b/benchmarks/baselines/ablations.py
@@ -2,8 +2,7 @@
 import json
 import sys
 import time
-from collections import defaultdict
-from dataclasses import asdict, dataclass, field
+from dataclasses import asdict
 
 import numpy as np
 from model2vec import StaticModel
@@ -17,13 +16,10 @@
     save_results,
     summarize_modes,
 )
-from benchmarks.metrics import ndcg_at_k, target_rank
+from benchmarks.run_benchmark import RepoResult, evaluate
 from semble import SembleIndex
 from semble.index.dense import _DEFAULT_MODEL_NAME
-from semble.types import SearchResult
-
-_TOP_K = 10
-_LATENCY_RUNS = 5
+from semble.types import SearchMode
 
 _MODES = ["bm25", "semantic", "semble-bm25", "semble-semantic"]
 
@@ -31,80 +27,14 @@
 # alpha=None  → raw mode, no ranking pipeline
 # alpha=0.0   → hybrid pipeline, BM25-only input
 # alpha=1.0   → hybrid pipeline, semantic-only input
-_MODE_PARAMS: dict[str, tuple[str, float | None]] = {
-    "bm25": ("bm25", None),
-    "semantic": ("semantic", None),
-    "semble-bm25": ("hybrid", 0.0),
-    "semble-semantic": ("hybrid", 1.0),
+_MODE_PARAMS: dict[str, tuple[SearchMode, float | None]] = {
+    "bm25": (SearchMode.BM25, None),
+    "semantic": (SearchMode.SEMANTIC, None),
+    "semble-bm25": (SearchMode.HYBRID, 0.0),
+    "semble-semantic": (SearchMode.HYBRID, 1.0),
 }
 
 
-@dataclass(frozen=True)
-class RepoResult:
-    """Per-repo benchmark result for one search mode."""
-
-    repo: str
-    language: str
-    mode: str
-    chunks: int
-    ndcg5: float
-    ndcg10: float
-    p50_ms: float
-    p90_ms: float
-    index_ms: float
-    by_category: dict[str, float] = field(default_factory=dict)
-
-
-def _evaluate(
-    index: SembleIndex,
-    tasks: list[Task],
-    mode: str,
-    alpha: float | None,
-    *,
-    verbose: bool = False,
-) -> tuple[float, float, list[float], dict[str, float]]:
-    """Return (mean NDCG@5, NDCG@10, latency list ms, per-category NDCG@10)."""
-    ndcg5_sum = 0.0
-    ndcg10_sum = 0.0
-    latencies: list[float] = []
-    category_ndcg10: dict[str, list[float]] = defaultdict(list)
-
-    for task in tasks:
-        query_latencies: list[float] = []
-        results: list[SearchResult] = []
-        for _ in range(_LATENCY_RUNS):
-            started = time.perf_counter()
-            results = index.search(task.query, top_k=_TOP_K, mode=mode, alpha=alpha)
-            query_latencies.append((time.perf_counter() - started) * 1000)
-        latencies.append(float(np.median(query_latencies)))
-
-        relevant_ranks = [rank for t in task.all_relevant if (rank := target_rank(results, t)) is not None]
-        n_relevant = len(task.all_relevant)
-        q_ndcg5 = ndcg_at_k(relevant_ranks, n_relevant, 5)
-        q_ndcg10 = ndcg_at_k(relevant_ranks, n_relevant, _TOP_K)
-        ndcg5_sum += q_ndcg5
-        ndcg10_sum += q_ndcg10
-        category_ndcg10[task.category or "unknown"].append(q_ndcg10)
-
-        if verbose:
-            category = task.category or "?"
-            targets_str = ", ".join(
-                t.path if not t.start_line else f"{t.path}:{t.start_line}-{t.end_line}" for t in task.all_relevant
-            )
-            top_files = [r.chunk.file_path for r in results[:5]]
-            print(
-                f"  [{category:<12}] ndcg@10={q_ndcg10:.3f}  ranks={relevant_ranks}"
-                f"  n_rel={n_relevant}  q={task.query!r}",
-                file=sys.stderr,
-            )
-            print(f"               targets: {targets_str}", file=sys.stderr)
-            print(f"               top-5:   {top_files}", file=sys.stderr)
-
-    total = len(tasks)
-    by_category = {cat: sum(vals) / len(vals) for cat, vals in sorted(category_ndcg10.items())}
-    return ndcg5_sum / total, ndcg10_sum / total, latencies, by_category
-
-
 def _bench(
     repo_tasks: dict[str, list[Task]],
     specs: dict[str, RepoSpec],
@@ -117,12 +47,12 @@ def _bench(
     results: list[RepoResult] = []
 
     header = (
-        f"{'Repo':<12} {'Language':<12} {'Mode':<16} {'Chunks':>6}"
+        f"{'Repo':<12} {'Language':<12} {'Mode':<16} {'Chunks':>6} {'Tokens':>8}"
         f" {'Index':>9} {'NDCG@5':>8} {'NDCG@10':>8} {'p50':>8} {'p90':>8}"
     )
     print(header, file=sys.stderr)
     print(
-        f"{'-' * 12} {'-' * 12} {'-' * 16} {'-' * 6} {'-' * 10} {'-' * 8} {'-' * 8} {'-' * 8} {'-' * 8}",
+        f"{'-' * 12} {'-' * 12} {'-' * 16} {'-' * 6} {'-' * 8} {'-' * 10} {'-' * 8} {'-' * 8} {'-' * 8} {'-' * 8}",
         file=sys.stderr,
     )
 
@@ -137,23 +67,28 @@ def _bench(
 
         for mode in modes:
             search_mode, alpha = _MODE_PARAMS[mode]
-            ndcg5, ndcg10, latencies, by_category = _evaluate(index, tasks, search_mode, alpha, verbose=verbose)
-            p50, p90 = np.percentile(latencies, [50, 90]).tolist()
+            ndcg5, ndcg10, latencies, by_category, tokens = evaluate(
+                index, tasks, mode=search_mode, alpha=alpha, verbose=verbose
+            )
+            p50, p90, p95, p99 = np.percentile(latencies, [50, 90, 95, 99]).tolist()
             result = RepoResult(
                 repo=repo,
                 language=spec.language,
                 mode=mode,
                 chunks=len(index.chunks),
+                tokens=tokens,
                 ndcg5=ndcg5,
                 ndcg10=ndcg10,
                 p50_ms=p50,
                 p90_ms=p90,
+                p95_ms=p95,
+                p99_ms=p99,
                 index_ms=index_ms,
                 by_category=by_category,
             )
             results.append(result)
             print(
-                f"{repo:<12} {spec.language:<12} {mode:<16} {len(index.chunks):>6}"
+                f"{repo:<12} {spec.language:<12} {mode:<16} {len(index.chunks):>6} {tokens:>8}"
                 f" {index_ms:>8.0f}ms {ndcg5:>8.3f} {ndcg10:>8.3f} {p50:>7.2f}ms {p90:>7.2f}ms",
                 file=sys.stderr,
             )
diff --git a/benchmarks/data.py b/benchmarks/data.py
index 78e7b289e..90198e7a5 100644
--- a/benchmarks/data.py
+++ b/benchmarks/data.py
@@ -171,6 +171,7 @@ def summarize_modes(results: Sequence[Any], modes: Sequence[str]) -> dict[str, d
         summary[mode] = {
             "avg_ndcg10": round(sum(r.ndcg10 for r in mode_results) / n, 4) if n else 0.0,
             "avg_p50_ms": round(sum(r.p50_ms for r in mode_results) / n, 1) if n else 0.0,
+            "avg_tokens": round(sum(r.tokens for r in mode_results) / n, 1) if n else 0.0,
         }
     return summary
 
diff --git a/benchmarks/results/semble-ablations-1ea77add4c1b.json b/benchmarks/results/semble-ablations-1ea77add4c1b.json
deleted file mode 100644
index 0e9393998..000000000
--- a/benchmarks/results/semble-ablations-1ea77add4c1b.json
+++ /dev/null
@@ -1,2096 +0,0 @@
-{
-  "tool": "semble-ablations",
-  "model": "minishlab/potion-code-16M",
-  "by_mode": {
-    "bm25": {
-      "avg_ndcg10": 0.6755,
-      "avg_p50_ms": 0.0
-    },
-    "semantic": {
-      "avg_ndcg10": 0.65,
-      "avg_p50_ms": 0.1
-    }
-  },
-  "repos": [
-    {
-      "repo": "abseil-cpp",
-      "language": "cpp",
-      "mode": "bm25",
-      "chunks": 3083,
-      "ndcg5": 0.8306102206338835,
-      "ndcg10": 0.8559838337906861,
-      "p50_ms": 0.0262709945673123,
-      "p90_ms": 0.031045306241139776,
-      "index_ms": 1677.3219159804285,
-      "by_category": {
-        "architecture": 1.0,
-        "semantic": 0.8325831281494842,
-        "symbol": 0.8769765845238192
-      }
-    },
-    {
-      "repo": "abseil-cpp",
-      "language": "cpp",
-      "mode": "semantic",
-      "chunks": 3083,
-      "ndcg5": 0.8968005463483602,
-      "ndcg10": 0.8968005463483602,
-      "p50_ms": 0.15139598690439016,
-      "p90_ms": 0.1649958052439615,
-      "index_ms": 1677.3219159804285,
-      "by_category": {
-        "architecture": 1.0,
-        "semantic": 0.8624007284644801,
-        "symbol": 1.0
-      }
-    },
-    {
-      "repo": "aeson",
-      "language": "haskell",
-      "mode": "bm25",
-      "chunks": 393,
-      "ndcg5": 0.8215338279036697,
-      "ndcg10": 0.8215338279036697,
-      "p50_ms": 0.020062507246620953,
-      "p90_ms": 0.02380840596742928,
-      "index_ms": 169.3293749995064,
-      "by_category": {
-        "architecture": 0.6,
-        "semantic": 0.895378437204893
-      }
-    },
-    {
-      "repo": "aeson",
-      "language": "haskell",
-      "mode": "semantic",
-      "chunks": 393,
-      "ndcg5": 0.8380929753571458,
-      "ndcg10": 0.8380929753571458,
-      "p50_ms": 0.06395850505214185,
-      "p90_ms": 0.06945029890630394,
-      "index_ms": 169.3293749995064,
-      "by_category": {
-        "architecture": 0.7,
-        "semantic": 0.884123967142861
-      }
-    },
-    {
-      "repo": "aiohttp",
-      "language": "python",
-      "mode": "bm25",
-      "chunks": 756,
-      "ndcg5": 0.5160765933241726,
-      "ndcg10": 0.5530893746563034,
-      "p50_ms": 0.014958000974729657,
-      "p90_ms": 0.019458006136119366,
-      "index_ms": 243.4504170087166,
-      "by_category": {
-        "architecture": 0.551842334782678,
-        "semantic": 0.492057189501762,
-        "symbol": 0.6646931637575532
-      }
-    },
-    {
-      "repo": "aiohttp",
-      "language": "python",
-      "mode": "semantic",
-      "chunks": 756,
-      "ndcg5": 0.5597347919369571,
-      "ndcg10": 0.6354048507429948,
-      "p50_ms": 0.07150002056732774,
-      "p90_ms": 0.07562502287328243,
-      "index_ms": 243.4504170087166,
-      "by_category": {
-        "architecture": 0.8733067418236369,
-        "semantic": 0.5786089798958602,
-        "symbol": 0.40457477075493775
-      }
-    },
-    {
-      "repo": "alamofire",
-      "language": "swift",
-      "mode": "bm25",
-      "chunks": 649,
-      "ndcg5": 0.7192265582238557,
-      "ndcg10": 0.762406947865875,
-      "p50_ms": 0.018770500901155174,
-      "p90_ms": 0.021087215282022953,
-      "index_ms": 222.48283299268223,
-      "by_category": {
-        "architecture": 0.8036233607701616,
-        "semantic": 0.7124789886370015,
-        "symbol": 0.8333333333333334
-      }
-    },
-    {
-      "repo": "alamofire",
-      "language": "swift",
-      "mode": "semantic",
-      "chunks": 649,
-      "ndcg5": 0.8179244987222131,
-      "ndcg10": 0.8357348580776142,
-      "p50_ms": 0.07000000914558768,
-      "p90_ms": 0.07505359535571188,
-      "index_ms": 222.48283299268223,
-      "by_category": {
-        "architecture": 0.7956176024115139,
-        "semantic": 0.8156033788372472,
-        "symbol": 0.892701197851337
-      }
-    },
-    {
-      "repo": "axios",
-      "language": "javascript",
-      "mode": "bm25",
-      "chunks": 166,
-      "ndcg5": 0.5941130715208459,
-      "ndcg10": 0.6498829469115347,
-      "p50_ms": 0.013708006008528173,
-      "p90_ms": 0.018216398893855512,
-      "index_ms": 60.610749991610646,
-      "by_category": {
-        "architecture": 0.45603968978715625,
-        "semantic": 0.6367026165128258,
-        "symbol": 0.8311894901132466
-      }
-    },
-    {
-      "repo": "axios",
-      "language": "javascript",
-      "mode": "semantic",
-      "chunks": 166,
-      "ndcg5": 0.6846241811764741,
-      "ndcg10": 0.7551105142269356,
-      "p50_ms": 0.05352050357032567,
-      "p90_ms": 0.05688280216418207,
-      "index_ms": 60.610749991610646,
-      "by_category": {
-        "architecture": 0.6914767706674343,
-        "semantic": 0.795298832280229,
-        "symbol": 0.7478561567799132
-      }
-    },
-    {
-      "repo": "axum",
-      "language": "rust",
-      "mode": "bm25",
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-      "ndcg5": 0.6380929753571458,
-      "ndcg10": 0.6892366680458802,
-      "p50_ms": 0.018853999790735543,
-      "p90_ms": 0.022504222579300404,
-      "index_ms": 179.37525000888854,
-      "by_category": {
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-        "semantic": 0.7470219239087327,
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-    },
-    {
-      "repo": "axum",
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-      "ndcg5": 0.5336215664331644,
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-      "by_category": {
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-        "semantic": 0.5687290841624842,
-        "symbol": 0.6666666666666666
-      }
-    },
-    {
-      "repo": "bash-it",
-      "language": "bash",
-      "mode": "bm25",
-      "chunks": 723,
-      "ndcg5": 0.6375696397737991,
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-      "by_category": {
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-      }
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-    {
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-      "mode": "semantic",
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-      "ndcg5": 0.5964125015971157,
-      "ndcg10": 0.6353623526728491,
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-      "ndcg5": 0.7235643897382131,
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-      "by_category": {
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-    {
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diff --git a/benchmarks/results/semble-ablations-215a04760692.json b/benchmarks/results/semble-ablations-215a04760692.json
deleted file mode 100644
index 90fc5135b..000000000
--- a/benchmarks/results/semble-ablations-215a04760692.json
+++ /dev/null
@@ -1,2096 +0,0 @@
-{
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diff --git a/benchmarks/results/semble-ablations-608143f7f73f.json b/benchmarks/results/semble-ablations-608143f7f73f.json
new file mode 100644
index 000000000..47cf3f837
--- /dev/null
+++ b/benchmarks/results/semble-ablations-608143f7f73f.json
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diff --git a/benchmarks/results/semble-hybrid-0332378809c5.json b/benchmarks/results/semble-hybrid-0332378809c5.json
deleted file mode 100644
index 9bd2a7e7f..000000000
--- a/benchmarks/results/semble-hybrid-0332378809c5.json
+++ /dev/null
@@ -1,1252 +0,0 @@
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diff --git a/benchmarks/results/semble-hybrid-1529eb900e03.json b/benchmarks/results/semble-hybrid-1529eb900e03.json
new file mode 100644
index 000000000..20cb95b89
--- /dev/null
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+      "index_ms": 120.10412498784717,
+      "by_category": {
+        "architecture": 1.0,
+        "semantic": 0.8561606311644849,
+        "symbol": 1.0
+      }
+    },
+    {
+      "repo": "rails",
+      "language": "ruby",
+      "mode": "hybrid",
+      "chunks": 480,
+      "tokens": 2488,
+      "ndcg5": 0.8424426241273885,
+      "ndcg10": 0.8526617440068127,
+      "p50_ms": 0.8136250035022385,
+      "p90_ms": 5.78059999388643,
+      "p95_ms": 7.92522289630142,
+      "p99_ms": 8.310510981973493,
+      "index_ms": 200.3997919964604,
+      "by_category": {
+        "architecture": 0.8407779776854644,
+        "semantic": 0.8596832229722856,
+        "symbol": 0.8671126300402693
+      }
+    },
+    {
+      "repo": "redis",
+      "language": "c",
+      "mode": "hybrid",
+      "chunks": 6367,
+      "tokens": 3434,
+      "ndcg5": 0.9158764682653967,
+      "ndcg10": 0.9158764682653967,
+      "p50_ms": 1.6168544971151277,
+      "p90_ms": 1.839174993801862,
+      "p95_ms": 1.8652833452506459,
+      "p99_ms": 2.050090265256585,
+      "index_ms": 3394.3092499976046,
+      "by_category": {
+        "architecture": 0.9430676558073394,
+        "semantic": 0.8886852807234542
+      }
+    },
+    {
+      "repo": "redux",
+      "language": "javascript",
+      "mode": "hybrid",
+      "chunks": 53,
+      "tokens": 2834,
+      "ndcg5": 0.8863147192765458,
+      "ndcg10": 0.9137963988128106,
+      "p50_ms": 0.5073330030427314,
+      "p90_ms": 3.3224618920939974,
+      "p95_ms": 3.455506242607955,
+      "p99_ms": 5.334701251849761,
+      "index_ms": 27.28395898884628,
+      "by_category": {
+        "architecture": 0.9032867981913646,
+        "semantic": 0.872911909678669,
+        "symbol": 1.0
+      }
+    },
+    {
+      "repo": "requests",
+      "language": "python",
+      "mode": "hybrid",
+      "chunks": 169,
+      "tokens": 3016,
+      "ndcg5": 0.9652540586697873,
+      "ndcg10": 0.9652540586697873,
+      "p50_ms": 0.47441700735362247,
+      "p90_ms": 4.540421403362416,
+      "p95_ms": 4.631245505152037,
+      "p99_ms": 4.6660154934215825,
+      "index_ms": 68.44233299489133,
+      "by_category": {
+        "architecture": 0.9709908720694624,
+        "semantic": 0.9385181336136883,
+        "symbol": 1.0
+      }
+    },
+    {
+      "repo": "serde",
+      "language": "rust",
+      "mode": "hybrid",
+      "chunks": 1178,
+      "tokens": 3023,
+      "ndcg5": 0.7965338279036697,
+      "ndcg10": 0.8301174310983572,
+      "p50_ms": 1.3143124961061403,
+      "p90_ms": 7.847875000152275,
+      "p95_ms": 10.408910393744009,
+      "p99_ms": 11.04974847883568,
+      "index_ms": 503.1043750059325,
+      "by_category": {
+        "architecture": 0.8543823750838853,
+        "semantic": 0.6764208118547154,
+        "symbol": 1.0
+      }
+    },
+    {
+      "repo": "sinatra",
+      "language": "ruby",
+      "mode": "hybrid",
+      "chunks": 70,
+      "tokens": 2831,
+      "ndcg5": 0.9530803155822426,
+      "ndcg10": 0.9530803155822426,
+      "p50_ms": 0.47072900633793324,
+      "p90_ms": 7.945425306388643,
+      "p95_ms": 8.074152105837129,
+      "p99_ms": 8.23416402505245,
+      "index_ms": 33.77162499236874,
+      "by_category": {
+        "architecture": 0.8123212623289702,
+        "semantic": 1.0,
+        "symbol": 1.0
+      }
+    },
+    {
+      "repo": "snapkit",
+      "language": "swift",
+      "mode": "hybrid",
+      "chunks": 107,
+      "tokens": 3153,
+      "ndcg5": 0.7723856192940887,
+      "ndcg10": 0.7872645734184941,
+      "p50_ms": 3.9077080000424758,
+      "p90_ms": 8.37871660187375,
+      "p95_ms": 10.841124999569722,
+      "p99_ms": 13.099224996985862,
+      "index_ms": 43.42112499580253,
+      "by_category": {
+        "architecture": 0.6399069297160626,
+        "semantic": 0.7592455236131767,
+        "symbol": 1.0
+      }
+    },
+    {
+      "repo": "starlette",
+      "language": "python",
+      "mode": "hybrid",
+      "chunks": 214,
+      "tokens": 2876,
+      "ndcg5": 0.9339593901316886,
+      "ndcg10": 0.9427487090259538,
+      "p50_ms": 0.5873329937458038,
+      "p90_ms": 4.390792004414834,
+      "p95_ms": 4.849791992455721,
+      "p99_ms": 4.865458398126066,
+      "index_ms": 90.21633298834786,
+      "by_category": {
+        "architecture": 0.8907020808677296,
+        "semantic": 1.0,
+        "symbol": 1.0
+      }
+    },
+    {
+      "repo": "telescope.nvim",
+      "language": "lua",
+      "mode": "hybrid",
+      "chunks": 544,
+      "tokens": 3061,
+      "ndcg5": 0.8024434932958862,
+      "ndcg10": 0.8024434932958862,
+      "p50_ms": 0.6600414926651865,
+      "p90_ms": 0.7375785906333476,
+      "p95_ms": 0.9762440924532745,
+      "p99_ms": 4.581716014072293,
+      "index_ms": 235.38995800481644,
+      "by_category": {
+        "architecture": 0.8805425336407291,
+        "semantic": 0.760390163879432
+      }
+    },
+    {
+      "repo": "tokio",
+      "language": "rust",
+      "mode": "hybrid",
+      "chunks": 2758,
+      "tokens": 3486,
+      "ndcg5": 0.9438607657669025,
+      "ndcg10": 0.9530895506058809,
+      "p50_ms": 1.0996044948115014,
+      "p90_ms": 9.666079202725088,
+      "p95_ms": 10.479194096114952,
+      "p99_ms": 11.422006025968583,
+      "index_ms": 1222.9317919991445,
+      "by_category": {
+        "architecture": 0.8436318353529363,
+        "semantic": 1.0,
+        "symbol": 1.0
+      }
+    },
+    {
+      "repo": "trpc",
+      "language": "typescript",
+      "mode": "hybrid",
+      "chunks": 363,
+      "tokens": 2942,
+      "ndcg5": 0.8117219727220212,
+      "ndcg10": 0.8318711294019078,
+      "p50_ms": 4.722396006400231,
+      "p90_ms": 6.073933700099587,
+      "p95_ms": 6.500069408502898,
+      "p99_ms": 9.555047484172968,
+      "index_ms": 151.68104199983645,
+      "by_category": {
+        "architecture": 0.7751964340658473,
+        "semantic": 0.7765501593587683,
+        "symbol": 1.0
+      }
+    },
+    {
+      "repo": "vapor",
+      "language": "swift",
+      "mode": "hybrid",
+      "chunks": 796,
+      "tokens": 2553,
+      "ndcg5": 0.7740663550396519,
+      "ndcg10": 0.828789449954672,
+      "p50_ms": 0.9356454975204542,
+      "p90_ms": 5.97867890028283,
+      "p95_ms": 6.119454449071782,
+      "p99_ms": 6.262523691548267,
+      "index_ms": 343.6642909946386,
+      "by_category": {
+        "architecture": 0.5394794582550125,
+        "semantic": 0.8540964731663144,
+        "symbol": 1.0
+      }
+    },
+    {
+      "repo": "vitest",
+      "language": "typescript",
+      "mode": "hybrid",
+      "chunks": 1090,
+      "tokens": 2797,
+      "ndcg5": 0.6573465818787765,
+      "ndcg10": 0.6929673005895788,
+      "p50_ms": 0.9439165005460382,
+      "p90_ms": 6.939696203335189,
+      "p95_ms": 7.915740196767732,
+      "p99_ms": 11.307714438007674,
+      "index_ms": 447.617124998942,
+      "by_category": {
+        "architecture": 0.6132788343159646,
+        "semantic": 0.6862493865749392,
+        "symbol": 0.8769765845238192
+      }
+    },
+    {
+      "repo": "xmonad",
+      "language": "haskell",
+      "mode": "hybrid",
+      "chunks": 124,
+      "tokens": 3034,
+      "ndcg5": 0.8039694436225424,
+      "ndcg10": 0.8141885635019669,
+      "p50_ms": 0.48554150271229446,
+      "p90_ms": 4.837362193211448,
+      "p95_ms": 5.144191647559637,
+      "p99_ms": 5.375104730046587,
+      "index_ms": 60.82770899229217,
+      "by_category": {
+        "architecture": 0.7691051895584848,
+        "semantic": 0.8442441461309548
+      }
+    },
+    {
+      "repo": "zig",
+      "language": "zig",
+      "mode": "hybrid",
+      "chunks": 13307,
+      "tokens": 3112,
+      "ndcg5": 0.9196394630357186,
+      "ndcg10": 0.9196394630357186,
+      "p50_ms": 3.1986040048650466,
+      "p90_ms": 32.74232530093287,
+      "p95_ms": 36.29184790042928,
+      "p99_ms": 40.6842359850998,
+      "index_ms": 5426.529041011236,
+      "by_category": {
+        "architecture": 0.7103099178571526,
+        "semantic": 0.9565799710084067
+      }
+    },
+    {
+      "repo": "zig-clap",
+      "language": "zig",
+      "mode": "hybrid",
+      "chunks": 100,
+      "tokens": 2525,
+      "ndcg5": 0.9380929753571458,
+      "ndcg10": 0.9380929753571458,
+      "p50_ms": 0.5309585030772723,
+      "p90_ms": 4.4691338916891254,
+      "p95_ms": 4.6746767475269735,
+      "p99_ms": 4.748301755171269,
+      "index_ms": 67.56016598956194,
+      "by_category": {
+        "architecture": 1.0,
+        "semantic": 0.9312144170634953
+      }
+    },
+    {
+      "repo": "zls",
+      "language": "zig",
+      "mode": "hybrid",
+      "chunks": 1319,
+      "tokens": 2934,
+      "ndcg5": 0.8761859507142915,
+      "ndcg10": 0.8761859507142915,
+      "p50_ms": 0.8124579981085844,
+      "p90_ms": 0.8837878078338691,
+      "p95_ms": 1.3312083472556024,
+      "p99_ms": 7.192075267230384,
+      "index_ms": 734.8769590025768,
+      "by_category": {
+        "architecture": 0.804418536224494,
+        "semantic": 0.9148299431318748
+      }
+    },
+    {
+      "repo": "zod",
+      "language": "typescript",
+      "mode": "hybrid",
+      "chunks": 1812,
+      "tokens": 2865,
+      "ndcg5": 0.595861623462428,
+      "ndcg10": 0.6136719828178292,
+      "p50_ms": 7.1065625015762635,
+      "p90_ms": 8.842266905412544,
+      "p95_ms": 9.122495204064766,
+      "p99_ms": 12.017399040487357,
+      "index_ms": 1027.3836249980377,
+      "by_category": {
+        "architecture": 0.6297620990369716,
+        "semantic": 0.586420115895172,
+        "symbol": 0.7103099178571526
+      }
+    }
+  ]
+}
diff --git a/benchmarks/run_benchmark.py b/benchmarks/run_benchmark.py
index 470240ede..a39b6f3c3 100644
--- a/benchmarks/run_benchmark.py
+++ b/benchmarks/run_benchmark.py
@@ -18,7 +18,7 @@
 from benchmarks.metrics import ndcg_at_k, target_rank
 from semble import SembleIndex
 from semble.index.dense import _DEFAULT_MODEL_NAME
-from semble.types import SearchResult
+from semble.types import SearchMode, SearchResult
 
 _LATENCY_RUNS = 5
 _DIRECT_TOP_K = 10
@@ -30,7 +30,9 @@ class RepoResult:
 
     repo: str
     language: str
+    mode: str
     chunks: int
+    tokens: int
     ndcg5: float
     ndcg10: float
     p50_ms: float
@@ -41,23 +43,30 @@ class RepoResult:
     by_category: dict[str, float] = field(default_factory=dict)
 
 
-def _evaluate(
-    index: SembleIndex, tasks: list[Task], *, verbose: bool = False
-) -> tuple[float, float, list[float], dict[str, float]]:
+def evaluate(
+    index: SembleIndex,
+    tasks: list[Task],
+    *,
+    verbose: bool = False,
+    mode: SearchMode = SearchMode.HYBRID,
+    alpha: float | None = None,
+) -> tuple[float, float, list[float], dict[str, float], int]:
     """Return mean NDCG@5, NDCG@10, median query latency (ms), and per-category NDCG@10."""
     ndcg5_sum = 0.0
     ndcg10_sum = 0.0
     latencies: list[float] = []
     category_ndcg10: dict[str, list[float]] = defaultdict(list)
+    tokens = 0
 
     for task in tasks:
         query_latencies: list[float] = []
         results: list[SearchResult] = []
         for _ in range(_LATENCY_RUNS):
             started = time.perf_counter()
-            results = index.search(task.query, top_k=_DIRECT_TOP_K)
+            results = index.search(task.query, top_k=_DIRECT_TOP_K, mode=mode, alpha=alpha)
             query_latencies.append((time.perf_counter() - started) * 1000)
         latencies.append(float(np.median(query_latencies)))
+        tokens += sum(len(r.chunk.content) // 4 for r in results)
 
         relevant_ranks = [rank for t in task.all_relevant if (rank := target_rank(results, t)) is not None]
         n_relevant = len(task.all_relevant)
@@ -83,7 +92,7 @@ def _evaluate(
 
     total = len(tasks)
     by_category = {cat: sum(vals) / len(vals) for cat, vals in sorted(category_ndcg10.items())}
-    return ndcg5_sum / total, ndcg10_sum / total, latencies, by_category
+    return ndcg5_sum / total, ndcg10_sum / total, latencies, by_category, tokens // total
 
 
 def _print_summary(results: list[RepoResult]) -> None:
@@ -95,6 +104,9 @@ def _print_summary(results: list[RepoResult]) -> None:
     language_ndcg10 = [
         sum(r.ndcg10 for r in language_results) / len(language_results) for language_results in by_language.values()
     ]
+    language_tokens = [
+        sum(r.tokens for r in language_results) / len(language_results) for language_results in by_language.values()
+    ]
     language_p50 = [
         sum(r.p50_ms for r in language_results) / len(language_results) for language_results in by_language.values()
     ]
@@ -111,6 +123,7 @@ def _print_summary(results: list[RepoResult]) -> None:
         sum(r.index_ms for r in language_results) / len(language_results) for language_results in by_language.values()
     ]
     avg_ndcg10 = sum(language_ndcg10) / len(language_ndcg10)
+    avg_tokens = sum(language_tokens) / len(language_tokens)
     avg_p50 = sum(language_p50) / len(language_p50)
     avg_p90 = sum(language_p90) / len(language_p90)
     avg_p95 = sum(language_p95) / len(language_p95)
@@ -123,6 +136,7 @@ def _print_summary(results: list[RepoResult]) -> None:
         print(
             f"  {language}: repos={len(grouped)}"
             + f"  ndcg@5={sum(r.ndcg5 for r in grouped) / len(grouped):.3f}"
+            + f"  tokens={sum(r.tokens for r in grouped) / len(grouped):.0f}"
             + f"  ndcg@10={sum(r.ndcg10 for r in grouped) / len(grouped):.3f}"
             + f"  p50={sum(r.p50_ms for r in grouped) / len(grouped):.2f}ms"
             + f"  p90={sum(r.p90_ms for r in grouped) / len(grouped):.2f}ms"
@@ -140,6 +154,7 @@ def _print_summary(results: list[RepoResult]) -> None:
     print(f"  {'-' * 28}  " + "  ".join(f"{'-' * 9:>9}" for _ in columns), file=sys.stderr)
 
     ndcg_row = [f"{avg_ndcg10:>9.3f}"]
+    tokens_row = [f"{avg_tokens:>9.0f}"]
     p50_row = [f"{avg_p50:>8.2f}ms"]
     p90_row = [f"{avg_p90:>8.2f}ms"]
     p95_row = [f"{avg_p95:>8.2f}ms"]
@@ -147,6 +162,7 @@ def _print_summary(results: list[RepoResult]) -> None:
     index_row = [f"{avg_index:>7.0f}ms"]
     for language, language_results in by_language.items():
         ndcg_row.append(f"{sum(r.ndcg10 for r in language_results) / len(language_results):>9.3f}")
+        tokens_row.append(f"{sum(r.tokens for r in language_results) / len(language_results):>9.0f}")
         p50_row.append(f"{sum(r.p50_ms for r in language_results) / len(language_results):>8.2f}ms")
         p90_row.append(f"{sum(r.p90_ms for r in language_results) / len(language_results):>8.2f}ms")
         p95_row.append(f"{sum(r.p95_ms for r in language_results) / len(language_results):>8.2f}ms")
@@ -154,6 +170,7 @@ def _print_summary(results: list[RepoResult]) -> None:
         index_row.append(f"{sum(r.index_ms for r in language_results) / len(language_results):>7.0f}ms")
 
     print(f"  {'NDCG@10':<28}  " + "  ".join(ndcg_row), file=sys.stderr)
+    print(f"  {'tokens':<28}  " + "  ".join(tokens_row), file=sys.stderr)
     print(f"  {'q-p50':<28}  " + "  ".join(p50_row), file=sys.stderr)
     print(f"  {'q-p90':<28}  " + "  ".join(p90_row), file=sys.stderr)
     print(f"  {'q-p95':<28}  " + "  ".join(p95_row), file=sys.stderr)
@@ -175,12 +192,12 @@ def _bench_quality(
 ) -> list[RepoResult]:
     """Run quality benchmarks (NDCG@5, NDCG@10, latency) for each repo."""
     print(
-        f"{'Repo':<12} {'Language':<12} {'Chunks':>6} {'index':>9} {'NDCG@5':>8} {'NDCG@10':>8} {'p50':>8} {'p90':>8}"
-        f" {'p95':>8} {'p99':>8}",
+        f"{'Repo':<12} {'Language':<12} {'Chunks':>6} {'Tokens':>8} {'index':>9} {'NDCG@5':>8} {'NDCG@10':>8} "
+        f"{'p50':>8} {'p90':>8} {'p95':>8} {'p99':>8}",
         file=sys.stderr,
     )
     print(
-        f"{'-' * 12} {'-' * 12} {'-' * 6} {'-' * 10} {'-' * 8} {'-' * 8} {'-' * 8} {'-' * 8} {'-' * 8} {'-' * 8}",
+        f"{'-' * 12} {'-' * 12} {'-' * 6} {'-' * 8} {'-' * 9} {'-' * 8} {'-' * 8} {'-' * 8} {'-' * 8} {'-' * 8}",
         file=sys.stderr,
     )
     results: list[RepoResult] = []
@@ -189,12 +206,14 @@ def _bench_quality(
         started = time.perf_counter()
         index = SembleIndex.from_path(spec.benchmark_dir, model=model)
         index_ms = (time.perf_counter() - started) * 1000
-        ndcg5, ndcg10, latencies, by_category = _evaluate(index, tasks, verbose=verbose)
+        ndcg5, ndcg10, latencies, by_category, tokens = evaluate(index, tasks, verbose=verbose)
         p50, p90, p95, p99 = np.percentile(latencies, [50, 90, 95, 99]).tolist()
         result = RepoResult(
             repo=repo,
+            mode=SearchMode.HYBRID.value,
             language=spec.language,
             chunks=len(index.chunks),
+            tokens=tokens,
             ndcg5=ndcg5,
             ndcg10=ndcg10,
             p50_ms=p50,
@@ -206,7 +225,7 @@ def _bench_quality(
         )
         results.append(result)
         print(
-            f"{repo:<12} {spec.language:<12} {len(index.chunks):>6} "
+            f"{repo:<12} {spec.language:<12} {len(index.chunks):>6} {tokens:>8}"
             f"{index_ms:>8.0f}ms {ndcg5:>8.3f} {ndcg10:>8.3f} {p50:>7.2f}ms {p90:>7.2f}ms {p95:>7.2f}ms {p99:>7.2f}ms",
             file=sys.stderr,
         )
@@ -221,6 +240,7 @@ def _save_results(results: list[RepoResult]) -> None:
     lang_means = {
         lang: {
             "ndcg10": sum(r.ndcg10 for r in grouped) / len(grouped),
+            "tokens": sum(r.tokens for r in grouped) / len(grouped),
             "p50_ms": sum(r.p50_ms for r in grouped) / len(grouped),
             "p90_ms": sum(r.p90_ms for r in grouped) / len(grouped),
             "p95_ms": sum(r.p95_ms for r in grouped) / len(grouped),
@@ -243,6 +263,7 @@ def _save_results(results: list[RepoResult]) -> None:
         "model": _DEFAULT_MODEL_NAME,
         "summary": {
             "ndcg10": round(sum(r.ndcg10 for r in results) / n_repos, 4),
+            "tokens": round(sum(r.tokens for r in results) / n_repos, 0),
             "p50_ms": round(sum(r.p50_ms for r in results) / n_repos, 3),
             "p90_ms": round(sum(r.p90_ms for r in results) / n_repos, 3),
             "p95_ms": round(sum(r.p95_ms for r in results) / n_repos, 3),
@@ -253,6 +274,7 @@ def _save_results(results: list[RepoResult]) -> None:
         "by_language": {
             lang: {
                 "repos": len(by_language[lang]),
+                "tokens": round(sum(r.tokens for r in by_language[lang]) / len(by_language[lang]), 0),
                 "ndcg10": round(v["ndcg10"], 4),
                 "p50_ms": round(v["p50_ms"], 3),
                 "p90_ms": round(v["p90_ms"], 3),
diff --git a/uv.lock b/uv.lock
index 0330d1422..ef3a1390d 100644
--- a/uv.lock
+++ b/uv.lock
@@ -3,16 +3,14 @@ revision = 3
 requires-python = ">=3.10"
 resolution-markers = [
     "python_full_version >= '3.15'",
-    "python_full_version == '3.14.*'",
-    "python_full_version == '3.13.*'",
-    "python_full_version == '3.12.*'",
+    "python_full_version >= '3.12' and python_full_version < '3.15'",
     "python_full_version == '3.11.*'",
     "python_full_version < '3.11'",
 ]
 
 [options]
 exclude-newer = "0001-01-01T00:00:00Z" # This has no effect and is included for backwards compatibility when using relative exclude-newer values.
-exclude-newer-span = "P1W"
+exclude-newer-span = "P3D"
 
 [[package]]
 name = "annotated-doc"
@@ -46,6 +44,44 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/da/42/e921fccf5015463e32a3cf6ee7f980a6ed0f395ceeaa45060b61d86486c2/anyio-4.13.0-py3-none-any.whl", hash = "sha256:08b310f9e24a9594186fd75b4f73f4a4152069e3853f1ed8bfbf58369f4ad708", size = 114353, upload-time = "2026-03-24T12:59:08.246Z" },
 ]
 
+[[package]]
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+version = "0.3.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/a9/9d/912fefab0e30aee6a3af8a62bbea4a81b29afa4ba2c973d31170620a26de/ast_serialize-0.3.0.tar.gz", hash = "sha256:1bc3ca09a63a021376527c4e938deedd11d11d675ce850e6f9c7487f5889992b", size = 60689, upload-time = "2026-04-30T23:24:48.104Z" }
+wheels = [
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+    { url = "https://files.pythonhosted.org/packages/ee/9e/a5db014bb0f91b209236b57c429389e31290c0093532b8436d577699b2fa/ast_serialize-0.3.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:a6fb063bf040abf8321e7b8113a0554eda445ffc508aa51287f8808886a5ae22", size = 1171316, upload-time = "2026-04-30T23:23:59.63Z" },
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+]
+
 [[package]]
 name = "attrs"
 version = "26.1.0"
@@ -57,15 +93,15 @@ wheels = [
 
 [[package]]
 name = "bm25s"
-version = "0.3.6"
+version = "0.3.8"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/82/c2/e5dbdbf8e99ec504432f9bd82cdf990faff1ffcdd5316272cb7fccce31ed/bm25s-0.3.8-py3-none-any.whl", hash = "sha256:b5ff52a0633ee5add26ca89619f5c5fff66127dcce0984976a2a09e1871a33f9", size = 74452, upload-time = "2026-04-29T02:18:43.892Z" },
 ]
 
 [[package]]
@@ -370,9 +406,7 @@ version = "1.3.3"
 source = { registry = "https://pypi.org/simple" }
 resolution-markers = [
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-    "python_full_version == '3.14.*'",
-    "python_full_version == '3.13.*'",
-    "python_full_version == '3.12.*'",
+    "python_full_version >= '3.12' and python_full_version < '3.15'",
     "python_full_version == '3.11.*'",
 ]
 dependencies = [
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