diff --git a/benchmarks/baselines/ablations.py b/benchmarks/baselines/ablations.py
index 894208b..63ca099 100644
--- a/benchmarks/baselines/ablations.py
+++ b/benchmarks/baselines/ablations.py
@@ -19,19 +19,19 @@
 from benchmarks.run_benchmark import RepoResult, evaluate
 from semble import SembleIndex
 from semble.index.dense import _DEFAULT_MODEL_NAME
-from semble.types import SearchMode
 
-_MODES = ["bm25", "semantic", "semble-bm25", "semble-semantic"]
-
-# Maps mode name -> (search_mode, alpha) for index.search()
-# alpha=None  → raw mode, no ranking pipeline
+# alpha=None  → raw mode, input depends on query
 # alpha=0.0   → hybrid pipeline, BM25-only input
 # alpha=1.0   → hybrid pipeline, semantic-only input
-_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),
+_MODE_PARAMS: dict[str, tuple[float | None, bool]] = {
+    "semble-bm25": (0.0, True),
+    "semble-semantic": (1.0, True),
+    "semble-auto": (None, True),
+    "semble-balanced": (0.5, True),
+    "unranked-bm25": (0.0, False),
+    "unranked-semantic": (1.0, False),
+    "unranked-auto": (None, False),
+    "unranked-balanced": (0.5, False),
 }
 
 
@@ -65,10 +65,9 @@ def _bench(
         index = SembleIndex.from_path(spec.benchmark_dir, model=model)
         index_ms = (time.perf_counter() - started) * 1000
 
-        for mode in modes:
-            search_mode, alpha = _MODE_PARAMS[mode]
+        for mode, (alpha, rerank) in sorted(_MODE_PARAMS.items()):
             ndcg5, ndcg10, latencies, by_category, tokens = evaluate(
-                index, tasks, mode=search_mode, alpha=alpha, verbose=verbose
+                index, tasks, alpha=alpha, verbose=verbose, rerank=rerank
             )
             p50, p90, p95, p99 = np.percentile(latencies, [50, 90, 95, 99]).tolist()
             result = RepoResult(
@@ -100,7 +99,7 @@ def _parse_args() -> argparse.Namespace:
     parser = argparse.ArgumentParser(description="semble ablation benchmarks.")
     add_filter_args(parser, verbose=True)
     parser.add_argument(
-        "--mode", action="append", default=[], choices=_MODES, help="Mode(s) to evaluate (default: all)."
+        "--mode", action="append", default=[], choices=sorted(_MODE_PARAMS), help="Mode(s) to evaluate (default: all)."
     )
     return parser.parse_args()
 
@@ -108,7 +107,7 @@ def _parse_args() -> argparse.Namespace:
 def main() -> None:
     """Run the semble ablation benchmarks."""
     args = _parse_args()
-    modes = args.mode or _MODES
+    modes = args.mode or sorted(_MODE_PARAMS)
 
     repo_specs, tasks = load_filtered_tasks(args.repo or None, args.language or None)
 
diff --git a/benchmarks/results/semble-ablations-608143f7f73f.json b/benchmarks/results/semble-ablations-608143f7f73f.json
deleted file mode 100644
index 47cf3f8..0000000
--- a/benchmarks/results/semble-ablations-608143f7f73f.json
+++ /dev/null
@@ -1,4764 +0,0 @@
-{
-  "tool": "semble-ablations",
-  "model": "minishlab/potion-code-16M",
-  "by_mode": {
-    "bm25": {
-      "avg_ndcg10": 0.682,
-      "avg_p50_ms": 0.1,
-      "avg_tokens": 3326.5
-    },
-    "semantic": {
-      "avg_ndcg10": 0.6576,
-      "avg_p50_ms": 0.2,
-      "avg_tokens": 3078.0
-    },
-    "semble-bm25": {
-      "avg_ndcg10": 0.8324,
-      "avg_p50_ms": 1.6,
-      "avg_tokens": 3340.8
-    },
-    "semble-semantic": {
-      "avg_ndcg10": 0.8216,
-      "avg_p50_ms": 1.5,
-      "avg_tokens": 2964.6
-    }
-  },
-  "repos": [
-    {
-      "repo": "abseil-cpp",
-      "language": "cpp",
-      "mode": "bm25",
-      "chunks": 3100,
-      "tokens": 3303,
-      "ndcg5": 0.8306102206338835,
-      "ndcg10": 0.8559838337906861,
-      "p50_ms": 0.0794375009718351,
-      "p90_ms": 0.0863204913912341,
-      "p95_ms": 0.08847049903124572,
-      "p99_ms": 0.10576049797236917,
-      "index_ms": 2246.204790993943,
-      "by_category": {
-        "architecture": 1.0,
-        "semantic": 0.8325831281494842,
-        "symbol": 0.8769765845238192
-      }
-    },
-    {
-      "repo": "abseil-cpp",
-      "language": "cpp",
-      "mode": "semantic",
-      "chunks": 3100,
-      "tokens": 3024,
-      "ndcg5": 0.8968005463483602,
-      "ndcg10": 0.8968005463483602,
-      "p50_ms": 0.40829200588632375,
-      "p90_ms": 0.4757086077006534,
-      "p95_ms": 0.47958924915292306,
-      "p99_ms": 0.5157842482731211,
-      "index_ms": 2246.204790993943,
-      "by_category": {
-        "architecture": 1.0,
-        "semantic": 0.8624007284644801,
-        "symbol": 1.0
-      }
-    },
-    {
-      "repo": "abseil-cpp",
-      "language": "cpp",
-      "mode": "semble-bm25",
-      "chunks": 3100,
-      "tokens": 3122,
-      "ndcg5": 0.9118153687184167,
-      "ndcg10": 0.9118153687184167,
-      "p50_ms": 1.2581874980241992,
-      "p90_ms": 11.257316406408796,
-      "p95_ms": 14.759925340331394,
-      "p99_ms": 15.915252262639113,
-      "index_ms": 2246.204790993943,
-      "by_category": {
-        "architecture": 0.8154648767857288,
-        "semantic": 0.9449800708482321,
-        "symbol": 0.8102255193577976
-      }
-    },
-    {
-      "repo": "abseil-cpp",
-      "language": "cpp",
-      "mode": "semble-semantic",
-      "chunks": 3100,
-      "tokens": 2704,
-      "ndcg5": 0.9306128427182248,
-      "ndcg10": 0.9306128427182248,
-      "p50_ms": 1.1265214925515465,
-      "p90_ms": 11.112536910513887,
-      "p95_ms": 14.545156254462201,
-      "p99_ms": 15.609631253319092,
-      "index_ms": 2246.204790993943,
-      "by_category": {
-        "architecture": 1.0,
-        "semantic": 0.9454386864194068,
-        "symbol": 0.8102255193577976
-      }
-    },
-    {
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-      "language": "haskell",
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-      "ndcg5": 0.8215338279036697,
-      "ndcg10": 0.8215338279036697,
-      "p50_ms": 0.07047950202831998,
-      "p90_ms": 0.076837204687763,
-      "p95_ms": 0.07969585494720378,
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-      }
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diff --git a/benchmarks/results/semble-ablations-757197f3967d.json b/benchmarks/results/semble-ablations-757197f3967d.json
new file mode 100644
index 0000000..23c1c34
--- /dev/null
+++ b/benchmarks/results/semble-ablations-757197f3967d.json
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+      "p90_ms": 0.5144625058164821,
+      "p95_ms": 0.5970666927169077,
+      "p99_ms": 0.6265805530711077,
+      "index_ms": 682.2228749806527,
+      "by_category": {
+        "architecture": 0.5430042850948544,
+        "semantic": 0.611975289501636
+      }
+    },
+    {
+      "repo": "zls",
+      "language": "zig",
+      "mode": "unranked-semantic",
+      "chunks": 1319,
+      "tokens": 2732,
+      "ndcg5": 0.6098332521130361,
+      "ndcg10": 0.624884751896235,
+      "p50_ms": 0.4336460115155205,
+      "p90_ms": 0.46800808631815016,
+      "p95_ms": 0.47383815544890245,
+      "p99_ms": 0.5043012267560698,
+      "index_ms": 682.2228749806527,
+      "by_category": {
+        "architecture": 0.6266932581763631,
+        "semantic": 0.62391094082232
+      }
+    },
+    {
+      "repo": "zod",
+      "language": "typescript",
+      "mode": "semble-auto",
+      "chunks": 1812,
+      "tokens": 2865,
+      "ndcg5": 0.595861623462428,
+      "ndcg10": 0.6136719828178292,
+      "p50_ms": 8.045667011174373,
+      "p90_ms": 10.104108424275182,
+      "p95_ms": 10.465408992604356,
+      "p99_ms": 13.5483489773469,
+      "index_ms": 857.6820000016596,
+      "by_category": {
+        "architecture": 0.6297620990369716,
+        "semantic": 0.586420115895172,
+        "symbol": 0.7103099178571526
+      }
+    },
+    {
+      "repo": "zod",
+      "language": "typescript",
+      "mode": "semble-balanced",
+      "chunks": 1812,
+      "tokens": 2821,
+      "ndcg5": 0.595861623462428,
+      "ndcg10": 0.6136719828178292,
+      "p50_ms": 7.925457990495488,
+      "p90_ms": 10.260308612487279,
+      "p95_ms": 10.4702100972645,
+      "p99_ms": 13.230942001100624,
+      "index_ms": 857.6820000016596,
+      "by_category": {
+        "architecture": 0.6297620990369716,
+        "semantic": 0.586420115895172,
+        "symbol": 0.7103099178571526
+      }
+    },
+    {
+      "repo": "zod",
+      "language": "typescript",
+      "mode": "semble-bm25",
+      "chunks": 1812,
+      "tokens": 3007,
+      "ndcg5": 0.522486247711064,
+      "ndcg10": 0.5827634665859462,
+      "p50_ms": 7.6838335080537945,
+      "p90_ms": 9.480995780904777,
+      "p95_ms": 10.001660106354397,
+      "p99_ms": 13.05993201967794,
+      "index_ms": 857.6820000016596,
+      "by_category": {
+        "architecture": 0.5660170306431477,
+        "semantic": 0.5584824196596058,
+        "symbol": 0.7103099178571526
+      }
+    },
+    {
+      "repo": "zod",
+      "language": "typescript",
+      "mode": "semble-semantic",
+      "chunks": 1812,
+      "tokens": 2692,
+      "ndcg5": 0.33209427612483317,
+      "ndcg10": 0.3993885146886994,
+      "p50_ms": 8.985896012745798,
+      "p90_ms": 10.551433899672702,
+      "p95_ms": 11.450255916861357,
+      "p99_ms": 17.044583996466816,
+      "index_ms": 857.6820000016596,
+      "by_category": {
+        "architecture": 0.29875546189751173,
+        "semantic": 0.3740055298546575,
+        "symbol": 0.643558852691131
+      }
+    },
+    {
+      "repo": "zod",
+      "language": "typescript",
+      "mode": "unranked-auto",
+      "chunks": 1812,
+      "tokens": 2879,
+      "ndcg5": 0.4696394630357187,
+      "ndcg10": 0.5007593710182797,
+      "p50_ms": 0.645562497084029,
+      "p90_ms": 1.089120513643138,
+      "p95_ms": 1.1485392504255287,
+      "p99_ms": 1.2428742609336039,
+      "index_ms": 857.6820000016596,
+      "by_category": {
+        "architecture": 0.2544456402014998,
+        "semantic": 0.5281903927683183,
+        "symbol": 0.7103099178571526
+      }
+    },
+    {
+      "repo": "zod",
+      "language": "typescript",
+      "mode": "unranked-balanced",
+      "chunks": 1812,
+      "tokens": 2882,
+      "ndcg5": 0.47618595071429154,
+      "ndcg10": 0.5073058586968526,
+      "p50_ms": 0.5712290003430098,
+      "p90_ms": 0.7472875149687752,
+      "p95_ms": 0.781295845808927,
+      "p99_ms": 0.8142927711014636,
+      "index_ms": 857.6820000016596,
+      "by_category": {
+        "architecture": 0.2544456402014998,
+        "semantic": 0.5281903927683183,
+        "symbol": 0.7539531690476383
+      }
+    },
+    {
+      "repo": "zod",
+      "language": "typescript",
+      "mode": "unranked-bm25",
+      "chunks": 1812,
+      "tokens": 3008,
+      "ndcg5": 0.37591052497168753,
+      "ndcg10": 0.4173000116024168,
+      "p50_ms": 0.4924789827782661,
+      "p90_ms": 0.5490784824360163,
+      "p95_ms": 0.6381305909599178,
+      "p99_ms": 0.6698925289674662,
+      "index_ms": 857.6820000016596,
+      "by_category": {
+        "architecture": 0.5,
+        "semantic": 0.3526262096081092,
+        "symbol": 0.5872865023809717
+      }
+    },
+    {
+      "repo": "zod",
+      "language": "typescript",
+      "mode": "unranked-semantic",
+      "chunks": 1812,
+      "tokens": 2731,
+      "ndcg5": 0.2943426403617271,
+      "ndcg10": 0.348114213453909,
+      "p50_ms": 0.46429148642346263,
+      "p90_ms": 0.5143458023667336,
+      "p95_ms": 0.5317225935868919,
+      "p99_ms": 0.5604445305652916,
+      "index_ms": 857.6820000016596,
+      "by_category": {
+        "architecture": 0.0,
+        "semantic": 0.39453468736498826,
+        "symbol": 0.611111111111111
+      }
+    }
+  ]
+}
diff --git a/benchmarks/run_benchmark.py b/benchmarks/run_benchmark.py
index a39b6f3..9e9a3e0 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 SearchMode, SearchResult
+from semble.types import SearchResult
 
 _LATENCY_RUNS = 5
 _DIRECT_TOP_K = 10
@@ -48,8 +48,8 @@ def evaluate(
     tasks: list[Task],
     *,
     verbose: bool = False,
-    mode: SearchMode = SearchMode.HYBRID,
     alpha: float | None = None,
+    rerank: bool = True,
 ) -> 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
@@ -63,7 +63,7 @@ def evaluate(
         results: list[SearchResult] = []
         for _ in range(_LATENCY_RUNS):
             started = time.perf_counter()
-            results = index.search(task.query, top_k=_DIRECT_TOP_K, mode=mode, alpha=alpha)
+            results = index.search(task.query, top_k=_DIRECT_TOP_K, alpha=alpha, rerank=rerank)
             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)
@@ -210,7 +210,7 @@ def _bench_quality(
         p50, p90, p95, p99 = np.percentile(latencies, [50, 90, 95, 99]).tolist()
         result = RepoResult(
             repo=repo,
-            mode=SearchMode.HYBRID.value,
+            mode="auto",
             language=spec.language,
             chunks=len(index.chunks),
             tokens=tokens,
diff --git a/src/semble/__init__.py b/src/semble/__init__.py
index 826a11e..ef61bdf 100644
--- a/src/semble/__init__.py
+++ b/src/semble/__init__.py
@@ -1,5 +1,5 @@
 from semble.index import SembleIndex
-from semble.types import Chunk, EmbeddingMatrix, Encoder, IndexStats, SearchMode, SearchResult
+from semble.types import Chunk, EmbeddingMatrix, Encoder, IndexStats, SearchResult
 from semble.version import __version__
 
 __all__ = [
@@ -7,7 +7,6 @@
     "EmbeddingMatrix",
     "Encoder",
     "IndexStats",
-    "SearchMode",
     "SearchResult",
     "SembleIndex",
     "__version__",
diff --git a/src/semble/cli.py b/src/semble/cli.py
index 5d7f886..9ee2df7 100644
--- a/src/semble/cli.py
+++ b/src/semble/cli.py
@@ -86,9 +86,6 @@ def _cli_main() -> None:
     search_p.add_argument("query", help="Natural language or code query.")
     search_p.add_argument("path", nargs="?", default=".", help="Local path or git URL (default: current directory).")
     search_p.add_argument("-k", "--top-k", type=int, default=5, help="Number of results (default: 5).")
-    search_p.add_argument(
-        "-m", "--mode", default="hybrid", choices=["hybrid", "semantic", "bm25"], help="Search mode (default: hybrid)."
-    )
     search_p.add_argument(
         "--include-text-files",
         action="store_true",
@@ -137,11 +134,11 @@ def _cli_main() -> None:
     )
 
     if args.command == "search":
-        results = index.search(args.query, top_k=args.top_k, mode=args.mode)
+        results = index.search(args.query, top_k=args.top_k)
         if not results:
             print("No results found.")
         else:
-            print(_format_results(f"Search results for: {args.query!r} (mode={args.mode})", results))
+            print(_format_results(f"Search results for: {args.query!r}", results))
 
     elif args.command == "find-related":
         chunk = _resolve_chunk(index.chunks, args.file_path, args.line)
diff --git a/src/semble/index/index.py b/src/semble/index/index.py
index b3be69a..56d51e3 100644
--- a/src/semble/index/index.py
+++ b/src/semble/index/index.py
@@ -13,9 +13,9 @@
 
 from semble.index.create import create_index_from_path
 from semble.index.dense import SelectableBasicBackend, load_model
-from semble.search import search_bm25, search_hybrid, search_semantic
+from semble.search import _search_semantic, search
 from semble.stats import save_search_stats
-from semble.types import CallType, Chunk, Encoder, IndexStats, SearchMode, SearchResult
+from semble.types import CallType, Chunk, Encoder, IndexStats, SearchResult
 
 _GIT_CLONE_TIMEOUT = int(os.environ.get("SEMBLE_CLONE_TIMEOUT", 60))
 
@@ -178,7 +178,7 @@ def find_related(self, source: Chunk | SearchResult, *, top_k: int = 5) -> list[
         """
         target = source.chunk if isinstance(source, SearchResult) else source
         selector = self._get_selector_vector(filter_languages=[target.language]) if target.language else None
-        results = search_semantic(target.content, self.model, self._semantic_index, self.chunks, top_k + 1, selector)
+        results = _search_semantic(target.content, self.model, self._semantic_index, self.chunks, top_k + 1, selector)
         results = [r for r in results if r.chunk != target][:top_k]
         save_search_stats(results, CallType.FIND_RELATED, self._file_sizes)
         return results
@@ -199,16 +199,15 @@ def search(
         self,
         query: str,
         top_k: int = 10,
-        mode: SearchMode | str = SearchMode.HYBRID,
         alpha: float | None = None,
         filter_languages: list[str] | None = None,
         filter_paths: list[str] | None = None,
+        rerank: bool = True,
     ) -> list[SearchResult]:
         """Search the index and return the top-k most relevant chunks.
 
         :param query: Natural-language or keyword query string.
         :param top_k: Maximum number of results to return.
-        :param mode: Search strategy — "hybrid" (default), "semantic", or "bm25".
         :param alpha: Blend weight for hybrid score combination; 1.0 = full semantic
             weight, 0.0 = full BM25 weight. File-path penalties and diversity reranking
             are applied regardless. ``None`` auto-detects from query type.
@@ -216,8 +215,8 @@ def search(
             these languages are returned.
         :param filter_paths: Optional list of repo-relative file paths; if set, only
             chunks from these files are returned.
+        :param rerank: Whether to rerank the top-k results using custom reranking logic.
         :return: Ranked list of :class:`SearchResult` objects, best match first.
-        :raises ValueError: If `mode` is not a recognised search strategy.
         """
         bm25_index, semantic_index = self._bm25_index, self._semantic_index
         if not self.chunks or not query.strip():
@@ -225,15 +224,16 @@ def search(
 
         selector = self._get_selector_vector(filter_languages, filter_paths)
 
-        if mode == SearchMode.BM25:
-            results = search_bm25(query, bm25_index, self.chunks, top_k, selector=selector)
-        elif mode == SearchMode.SEMANTIC:
-            results = search_semantic(query, self.model, semantic_index, self.chunks, top_k, selector=selector)
-        elif mode == SearchMode.HYBRID:
-            results = search_hybrid(
-                query, self.model, semantic_index, bm25_index, self.chunks, top_k, alpha=alpha, selector=selector
-            )
-        else:
-            raise ValueError(f"Unknown search mode: {mode!r}")
+        results = search(
+            query,
+            self.model,
+            semantic_index,
+            bm25_index,
+            self.chunks,
+            top_k,
+            alpha=alpha,
+            selector=selector,
+            rerank=rerank,
+        )
         save_search_stats(results, CallType.SEARCH, self._file_sizes)
         return results
diff --git a/src/semble/mcp.py b/src/semble/mcp.py
index 38d170c..a9c533d 100644
--- a/src/semble/mcp.py
+++ b/src/semble/mcp.py
@@ -4,7 +4,7 @@
 import logging
 from collections import OrderedDict
 from pathlib import Path
-from typing import Annotated, Literal
+from typing import Annotated
 
 import watchfiles
 from mcp.server.fastmcp import FastMCP
@@ -63,10 +63,6 @@ def create_server(cache: _IndexCache, default_source: str | None = None) -> Fast
     async def search(
         query: Annotated[str, Field(description="Natural language or code query.")],
         repo: Annotated[str | None, Field(description=_REPO_DESCRIPTION)] = None,
-        mode: Annotated[
-            Literal["hybrid", "semantic", "bm25"],
-            Field(description="Search mode. 'hybrid' is best for most queries."),
-        ] = "hybrid",
         top_k: Annotated[int, Field(description="Number of results to return.", ge=1)] = 5,
     ) -> str:
         """Search a codebase with a natural-language or code query.
@@ -78,10 +74,10 @@ async def search(
             index = await _get_index(repo, default_source, cache)
         except ValueError as exc:
             return str(exc)
-        results = index.search(query, top_k=top_k, mode=mode)
+        results = index.search(query, top_k=top_k)
         if not results:
             return "No results found."
-        return _format_results(f"Search results for: {query!r} (mode={mode})", results)
+        return _format_results(f"Search results for: {query!r}", results)
 
     @server.tool()
     async def find_related(
diff --git a/src/semble/search.py b/src/semble/search.py
index 2a50a17..d0a9d25 100644
--- a/src/semble/search.py
+++ b/src/semble/search.py
@@ -6,7 +6,7 @@
 from semble.index.sparse import selector_to_mask
 from semble.ranking import apply_query_boost, boost_multi_chunk_files, rerank_topk, resolve_alpha
 from semble.tokens import tokenize
-from semble.types import Chunk, Encoder, SearchMode, SearchResult
+from semble.types import Chunk, Encoder, SearchResult
 
 _RRF_K = 60
 
@@ -19,7 +19,7 @@ def _rrf_scores(scores: dict[Chunk, float]) -> dict[Chunk, float]:
     return {chunk: 1.0 / (_RRF_K + rank) for rank, chunk in enumerate(ranked, 1)}
 
 
-def search_semantic(
+def _search_semantic(
     query: str,
     model: Encoder,
     semantic_index: SelectableBasicBackend,
@@ -31,10 +31,7 @@ def search_semantic(
     query_embedding = model.encode([query])
     indices, scores = semantic_index.query(query_embedding, k=top_k, selector=selector)[0]
     # Vicinity returns cosine distance; convert to similarity so higher = better.
-    return [
-        SearchResult(chunk=chunks[index], score=1.0 - float(distance), source=SearchMode.SEMANTIC)
-        for index, distance in zip(indices, scores)
-    ]
+    return [SearchResult(chunk=chunks[index], score=1.0 - float(distance)) for index, distance in zip(indices, scores)]
 
 
 def _sort_top_k(arr: npt.NDArray, top_k: int) -> npt.NDArray[np.int_]:
@@ -46,7 +43,7 @@ def _sort_top_k(arr: npt.NDArray, top_k: int) -> npt.NDArray[np.int_]:
     return partitioned[np.argsort(neg_arr[partitioned])]
 
 
-def search_bm25(
+def _search_bm25(
     query: str,
     bm25_index: bm25s.BM25,
     chunks: list[Chunk],
@@ -62,12 +59,10 @@ def search_bm25(
     indices = _sort_top_k(scores, top_k)
 
     # Exclude chunks with zero score, no query tokens matched.
-    return [
-        SearchResult(chunk=chunks[i], score=float(scores[i]), source=SearchMode.BM25) for i in indices if scores[i] > 0
-    ]
+    return [SearchResult(chunk=chunks[i], score=float(scores[i])) for i in indices if scores[i] > 0]
 
 
-def search_hybrid(
+def search(
     query: str,
     model: Encoder,
     semantic_index: SelectableBasicBackend,
@@ -76,6 +71,7 @@ def search_hybrid(
     top_k: int,
     alpha: float | None = None,
     selector: npt.NDArray[np.int_] | None = None,
+    rerank: bool = True,
 ) -> list[SearchResult]:
     """Hybrid search: alpha-weighted combination of semantic and BM25 scores.
 
@@ -90,6 +86,7 @@ def search_hybrid(
     :param top_k: Number of results to return.
     :param alpha: Weight for semantic score (1-alpha goes to BM25). None = auto-detect based on query type.
     :param selector: Optional array of chunk indices to filter results by.
+    :param rerank: Whether to perform reranking. This should be done, and is mainly here for benchmarking.
     :return: List of search results sorted by combined score descending.
     """
     alpha_weight = resolve_alpha(query, alpha)
@@ -97,10 +94,10 @@ def search_hybrid(
     # Over-fetch candidates so the merged pool is large enough after union and re-ranking.
     candidate_count = top_k * 5
 
-    semantic = search_semantic(query, model, semantic_index, chunks, candidate_count, selector)
+    semantic = _search_semantic(query, model, semantic_index, chunks, candidate_count, selector)
     semantic_scores: dict[Chunk, float] = {result.chunk: result.score for result in semantic}
     bm25_scores = {}
-    for result in search_bm25(query, bm25_index, chunks, candidate_count, selector):
+    for result in _search_bm25(query, bm25_index, chunks, candidate_count, selector):
         if result.score:
             bm25_scores[result.chunk] = result.score
 
@@ -119,10 +116,14 @@ def search_hybrid(
         for chunk in all_candidates
     }
 
-    # Boost files with multiple relevant chunks.
-    boost_multi_chunk_files(combined_scores)
-    # Boost queries with specific identifiers in them.
-    combined_scores = apply_query_boost(combined_scores, query, chunks)
-    # Rerank the top-k results by applying path-based penalties.
-    ranked = rerank_topk(combined_scores, top_k, penalise_paths=alpha_weight < 1.0)
-    return [SearchResult(chunk=chunk, score=score, source=SearchMode.HYBRID) for chunk, score in ranked]
+    if rerank:
+        # Boost files with multiple relevant chunks.
+        boost_multi_chunk_files(combined_scores)
+        # Boost queries with specific identifiers in them.
+        combined_scores = apply_query_boost(combined_scores, query, chunks)
+        # Rerank the top-k results by applying path-based penalties.
+        ranked = rerank_topk(combined_scores, top_k, penalise_paths=alpha_weight < 1.0)
+    else:
+        sorted_by_score = sorted(combined_scores.items(), key=lambda x: x[1], reverse=True)
+        ranked = sorted_by_score[:top_k]
+    return [SearchResult(chunk=chunk, score=score) for chunk, score in ranked]
diff --git a/src/semble/types.py b/src/semble/types.py
index 5871db1..d01c774 100644
--- a/src/semble/types.py
+++ b/src/semble/types.py
@@ -9,14 +9,6 @@
 EmbeddingMatrix: TypeAlias = npt.NDArray[np.float32]
 
 
-class SearchMode(str, Enum):
-    """Search mode for SembleIndex.search()."""
-
-    HYBRID = "hybrid"
-    SEMANTIC = "semantic"
-    BM25 = "bm25"
-
-
 class CallType(str, Enum):
     """Call type for token-savings tracking."""
 
@@ -59,7 +51,6 @@ class SearchResult:
 
     chunk: Chunk
     score: float
-    source: SearchMode
 
 
 @dataclass(frozen=True, slots=True)
diff --git a/tests/test_cli.py b/tests/test_cli.py
index 76bc1d8..2c71a72 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -6,7 +6,7 @@
 import pytest
 
 from semble.cli import Agent, _agent_path, _cli_main, _run_init, main
-from semble.types import SearchMode, SearchResult
+from semble.types import SearchResult
 from tests.conftest import make_chunk
 
 _CLAUDE_FILE_PATH = _agent_path(Agent.CLAUDE)
@@ -34,7 +34,7 @@ def test_main_calls_asyncio_run(argv: list[str], monkeypatch: pytest.MonkeyPatch
     "argv, expected_in_output",
     [
         (["semble", "search", "query text", "/some/path"], ["query text", "0.9"]),
-        (["semble", "search", "nothing", "/some/path", "--top-k", "3", "--mode", "bm25"], ["No results found"]),
+        (["semble", "search", "nothing", "/some/path", "--top-k", "3"], ["No results found"]),
     ],
 )
 def test_cli_search(
@@ -47,9 +47,7 @@ def test_cli_search(
     chunk = make_chunk("def foo(): pass", "src/foo.py")
     fake_index = MagicMock()
     has_results = "No results" not in expected_in_output[0]
-    fake_index.search.return_value = (
-        [SearchResult(chunk=chunk, score=0.9, source=SearchMode.HYBRID)] if has_results else []
-    )
+    fake_index.search.return_value = [SearchResult(chunk=chunk, score=0.9)] if has_results else []
     monkeypatch.setattr(sys, "argv", argv)
     with patch("semble.cli.SembleIndex.from_path", return_value=fake_index):
         _cli_main()
@@ -78,9 +76,7 @@ def test_cli_find_related(
     chunk = make_chunk("class Bar: pass", "src/bar.py")
     fake_index = MagicMock()
     fake_index.chunks = [] if scenario == "unknown_chunk" else [chunk]
-    fake_index.find_related.return_value = (
-        [SearchResult(chunk=chunk, score=0.8, source=SearchMode.SEMANTIC)] if scenario == "with_results" else []
-    )
+    fake_index.find_related.return_value = [SearchResult(chunk=chunk, score=0.8)] if scenario == "with_results" else []
     file_path = "unknown.py" if scenario == "unknown_chunk" else "src/bar.py"
     monkeypatch.setattr(sys, "argv", ["semble", "find-related", file_path, "1", "/some/path"])
     with patch("semble.cli.SembleIndex.from_path", return_value=fake_index):
@@ -145,7 +141,7 @@ def test_main_dispatches_to_cli(
     """main() routes to _cli_main when first argument is a CLI subcommand."""
     chunk = make_chunk("def foo(): pass", "src/foo.py")
     fake_index = MagicMock()
-    fake_index.search.return_value = [SearchResult(chunk=chunk, score=0.9, source=SearchMode.HYBRID)]
+    fake_index.search.return_value = [SearchResult(chunk=chunk, score=0.9)]
     monkeypatch.setattr(sys, "argv", ["semble", "search", "query text", "/some/path"])
     with patch("semble.cli.SembleIndex.from_path", return_value=fake_index):
         main()
@@ -169,7 +165,7 @@ def test_cli_entrypoint_works_without_mcp_installed(
     """CLI entrypoint paths succeed even when the mcp package is not installed."""
     chunk = make_chunk("def foo(): pass", "src/foo.py")
     fake_index = MagicMock()
-    fake_index.search.return_value = [SearchResult(chunk=chunk, score=0.9, source=SearchMode.HYBRID)]
+    fake_index.search.return_value = [SearchResult(chunk=chunk, score=0.9)]
     monkeypatch.setattr(sys, "argv", argv)
     monkeypatch.setitem(sys.modules, "mcp", None)
     monkeypatch.setitem(sys.modules, "mcp.server", None)
diff --git a/tests/test_index.py b/tests/test_index.py
index 8e87ddd..3f90fcb 100644
--- a/tests/test_index.py
+++ b/tests/test_index.py
@@ -1,5 +1,6 @@
 from pathlib import Path
 from typing import Any
+from unittest.mock import patch
 
 import pytest
 
@@ -49,43 +50,45 @@ def test_index_language_counts(indexed_index: SembleIndex) -> None:
 
 
 @pytest.mark.parametrize(
-    "query, mode",
-    [("authenticate token", "hybrid"), ("authenticate", "bm25"), ("authentication", "semantic")],
+    "query",
+    [("authenticate token"), ("authenticate"), ("authentication")],
 )
-def test_search_modes(indexed_index: SembleIndex, query: str, mode: str) -> None:
+def test_search_modes(indexed_index: SembleIndex, query: str) -> None:
     """Each search mode returns a valid list of at most top_k results."""
-    results = indexed_index.search(query, top_k=3, mode=mode)
+    results = indexed_index.search(query, top_k=3)
     assert isinstance(results, list)
     assert len(results) <= 3
 
 
-def test_search_invalid_mode(indexed_index: SembleIndex) -> None:
-    """An unrecognised mode string raises ValueError."""
-    with pytest.raises(ValueError):
-        indexed_index.search("query", mode="invalid")
-
-
 def test_search_constraints(indexed_index: SembleIndex) -> None:
     """search: top_k is respected; no duplicate chunks are returned."""
-    assert len(indexed_index.search("function", top_k=1, mode="bm25")) <= 1
+    assert len(indexed_index.search("function", top_k=1)) <= 1
 
     results = indexed_index.search("authenticate", top_k=5)
     assert len(results) == len(set(r.chunk for r in results))
 
 
-@pytest.mark.parametrize("mode", ["bm25", "hybrid", "semantic"])
-def test_search_with_filter_paths_does_not_crash(indexed_index: SembleIndex, mode: str) -> None:
+def test_search_with_filter_paths_does_not_crash(indexed_index: SembleIndex) -> None:
     """Filtered search works regardless of where the selected chunk lives in the corpus."""
     target_path = indexed_index.chunks[-1].file_path
-    results = indexed_index.search("function", top_k=3, mode=mode, filter_paths=[target_path])
+    results = indexed_index.search("function", top_k=3, filter_paths=[target_path])
     assert all(r.chunk.file_path == target_path for r in results)
 
 
-@pytest.mark.parametrize("mode", ["bm25", "hybrid", "semantic"])
+def test_search_without_reranking(indexed_index: SembleIndex) -> None:
+    """Filtered search works regardless of where the selected chunk lives in the corpus."""
+    with patch("semble.search.rerank_topk") as mock:
+        indexed_index.search("function", top_k=3, rerank=False)
+        mock.assert_not_called()
+    with patch("semble.search.rerank_topk") as mock:
+        indexed_index.search("function", top_k=3, rerank=True)
+        mock.assert_called()
+
+
 @pytest.mark.parametrize("query", ["", "   ", "\n\n"])
-def test_search_empty_query_returns_empty(indexed_index: SembleIndex, mode: str, query: str) -> None:
+def test_search_empty_query_returns_empty(indexed_index: SembleIndex, query: str) -> None:
     """Empty / whitespace-only queries return [] across all modes."""
-    assert indexed_index.search(query, mode=mode) == []
+    assert indexed_index.search(query) == []
 
 
 @pytest.mark.parametrize(
diff --git a/tests/test_mcp.py b/tests/test_mcp.py
index f9a1c80..ef4dcce 100644
--- a/tests/test_mcp.py
+++ b/tests/test_mcp.py
@@ -5,7 +5,7 @@
 import pytest
 
 from semble.mcp import _CACHE_MAX_SIZE, _IndexCache, create_server, serve
-from semble.types import Chunk, Encoder, SearchMode, SearchResult
+from semble.types import Chunk, Encoder, SearchResult
 from semble.utils import _format_results, _is_git_url, _resolve_chunk
 from tests.conftest import make_chunk
 
@@ -87,9 +87,7 @@ def test_format_results() -> None:
     assert "```" not in empty_out
 
     chunks = [make_chunk(f"def fn_{i}(): pass", f"f{i}.py") for i in range(3)]
-    results = [
-        SearchResult(chunk=c, score=round(0.1 * (i + 1), 3), source=SearchMode.HYBRID) for i, c in enumerate(chunks)
-    ]
+    results = [SearchResult(chunk=c, score=round(0.1 * (i + 1), 3)) for i, c in enumerate(chunks)]
     out = _format_results("Results for: 'foo'", results)
     assert "Results for: 'foo'" in out
     assert out.count("```") >= len(results) * 2  # opening + closing fence each
@@ -183,7 +181,7 @@ async def test_tool_index_failure(cache: _IndexCache, tool: str, args: dict[str,
             "search",
             {"query": "bar"},
             "search",
-            [SearchResult(chunk=make_chunk("def bar(): pass", "src/bar.py"), score=0.9, source=SearchMode.HYBRID)],
+            [SearchResult(chunk=make_chunk("def bar(): pass", "src/bar.py"), score=0.9)],
             None,
             ["bar", "0.900"],
             id="search_with_results",
@@ -201,7 +199,7 @@ async def test_tool_index_failure(cache: _IndexCache, tool: str, args: dict[str,
             "find_related",
             {"file_path": "src/foo.py", "line": 1},
             "find_related",
-            [SearchResult(chunk=make_chunk("class Foo: pass", "src/foo.py"), score=0.8, source=SearchMode.SEMANTIC)],
+            [SearchResult(chunk=make_chunk("class Foo: pass", "src/foo.py"), score=0.8)],
             [make_chunk("class Foo: pass", "src/foo.py")],
             ["src/foo.py:1", "0.800"],
             id="find_related_with_results",
diff --git a/tests/test_search.py b/tests/test_search.py
index 2a0d487..56bd2f1 100644
--- a/tests/test_search.py
+++ b/tests/test_search.py
@@ -8,9 +8,9 @@
 from vicinity.backends.basic import BasicArgs
 
 from semble.index.dense import SelectableBasicBackend, embed_chunks, load_model
-from semble.search import _sort_top_k, search_bm25, search_hybrid, search_semantic
+from semble.search import _search_bm25, _search_semantic, _sort_top_k, search
 from semble.tokens import tokenize
-from semble.types import Chunk, Encoder, SearchMode
+from semble.types import Chunk, Encoder
 from tests.conftest import make_chunk
 
 
@@ -51,24 +51,24 @@ def semantic(embeddings: npt.NDArray[np.float32]) -> SelectableBasicBackend:
 
 def test_search_bm25(bm25: bm25s.BM25, chunks: list[Chunk]) -> None:
     """search_bm25: returns most relevant chunk first; selector restricts to given indices."""
-    results = search_bm25("authenticate token", bm25, chunks, top_k=4, selector=None)
+    results = _search_bm25("authenticate token", bm25, chunks, top_k=4, selector=None)
     assert len(results) > 0
     assert "authenticate" in results[0].chunk.content
 
     selector = np.array([len(chunks) - 1], dtype=np.int_)
-    filtered = search_bm25("format", bm25, chunks, top_k=4, selector=selector)
+    filtered = _search_bm25("format", bm25, chunks, top_k=4, selector=selector)
     assert all(r.chunk is chunks[len(chunks) - 1] for r in filtered)
 
 
 @pytest.mark.parametrize("query", ["", "   ", "\n\n", "zzzznonexistentterm"])
 def test_bm25_returns_empty_for_no_match(bm25: bm25s.BM25, chunks: list[Chunk], query: str) -> None:
     """Empty / whitespace-only / token-less queries return [] instead of crashing bm25s."""
-    assert search_bm25(query, bm25, chunks, top_k=3, selector=None) == []
+    assert _search_bm25(query, bm25, chunks, top_k=3, selector=None) == []
 
 
 def test_semantic_search(semantic: SelectableBasicBackend, chunks: list[Chunk], mock_model: Any) -> None:
     """Semantic search returns results with scores in [-1, 1]."""
-    results = search_semantic("login", mock_model, semantic, chunks, top_k=3, selector=None)
+    results = _search_semantic("login", mock_model, semantic, chunks, top_k=3, selector=None)
     assert len(results) > 0
     assert all(-1.0 <= r.score <= 1.0 for r in results)
 
@@ -77,7 +77,7 @@ def test_search_hybrid(
     chunks: list[Chunk], semantic: SelectableBasicBackend, bm25: bm25s.BM25, mock_model: Any
 ) -> None:
     """search_hybrid: returns combined results; identical content in different files produces separate results."""
-    results = search_hybrid("authenticate token", mock_model, semantic, bm25, chunks, top_k=3)
+    results = search("authenticate token", mock_model, semantic, bm25, chunks, top_k=3)
     assert len(results) > 0
 
     shared_content = "def helper():\n    pass"
@@ -93,23 +93,22 @@ def test_search_hybrid(
     bm25_index = bm25s.BM25()
     bm25_index.index([tokenize(c.content) for c in all_chunks], show_progress=False)
 
-    deduped = search_hybrid("helper", mock_model, sem_index, bm25_index, all_chunks, top_k=5)
+    deduped = search("helper", mock_model, sem_index, bm25_index, all_chunks, top_k=5)
     result_locations = {r.chunk.file_path for r in deduped}
     assert "module_a.py" in result_locations
     assert "module_b.py" in result_locations
 
 
 @pytest.mark.parametrize(
-    ("search_fn", "mode", "query", "top_k"),
+    ("search_fn", "query", "top_k"),
     [
-        (lambda q, m, s, b, c, k: search_bm25(q, b, c, k, selector=None), SearchMode.BM25, "authenticate", 3),
-        (lambda q, m, s, b, c, k: search_semantic(q, m, s, c, k, selector=None), SearchMode.SEMANTIC, "query", 4),
-        (lambda q, m, s, b, c, k: search_hybrid(q, m, s, b, c, k), SearchMode.HYBRID, "login", 4),
+        (lambda q, m, s, b, c, k: _search_bm25(q, b, c, k, selector=None), "authenticate", 3),
+        (lambda q, m, s, b, c, k: _search_semantic(q, m, s, c, k, selector=None), "query", 4),
+        (lambda q, m, s, b, c, k: search(q, m, s, b, c, k), "login", 4),
     ],
 )
 def test_search_source_labels(
     search_fn: Any,
-    mode: SearchMode,
     query: str,
     top_k: int,
     chunks: list[Chunk],
@@ -120,7 +119,6 @@ def test_search_source_labels(
     """Each result carries a source label matching the search mode used."""
     results = search_fn(query, mock_model, semantic, bm25, chunks, top_k)
     assert len(results) > 0
-    assert all(result.source is mode for result in results)
 
 
 def test_sort_top_k() -> None:
diff --git a/tests/test_stats.py b/tests/test_stats.py
index 21973ad..d3c7689 100644
--- a/tests/test_stats.py
+++ b/tests/test_stats.py
@@ -8,7 +8,7 @@
 
 from semble.cli import _cli_main
 from semble.stats import build_savings_summary, format_savings_report, save_search_stats
-from semble.types import CallType, SearchMode, SearchResult
+from semble.types import CallType, SearchResult
 from tests.conftest import make_chunk
 
 
@@ -30,7 +30,7 @@ def sample_stats_file(tmp_path: Path) -> Path:
 def test_save_search_stats(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
     """save_search_stats deduplicates file paths and silences write errors."""
     chunk = make_chunk("hello", "src/foo.py")
-    result = SearchResult(chunk=chunk, score=0.9, source=SearchMode.HYBRID)
+    result = SearchResult(chunk=chunk, score=0.9)
     stats_file = tmp_path / "stats.jsonl"
     monkeypatch.setattr("semble.stats._STATS_FILE", stats_file)
     save_search_stats([result, result], CallType.SEARCH, {"src/foo.py": 42})
diff --git a/uv.lock b/uv.lock
index 9ce6273..1d492fe 100644
--- a/uv.lock
+++ b/uv.lock
@@ -10,7 +10,7 @@ resolution-markers = [
 
 [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"