diff --git a/docs/contributing/performance_benchmarks.md b/docs/contributing/performance_benchmarks.md
index 0c13b565d..06e7dbf59 100644
--- a/docs/contributing/performance_benchmarks.md
+++ b/docs/contributing/performance_benchmarks.md
@@ -79,10 +79,11 @@ fastvideo/performance/
 ```
 
 The HF dataset (`FastVideo/performance-tracking` by default) holds one
-normalized JSON per `(model_id, gpu_type, run)` tuple. The rolling baseline is
-the median of the last 5 successful, baseline-eligible records for that
-model+GPU. PR and local records are visible in the dashboard but are not
-baseline eligible.
+normalized JSON per run. For v2 records, the rolling baseline is the median of
+the last 5 successful, baseline-eligible records in the same comparison cohort:
+`model_id`, `gpu_type`, `workload_id`, `variant_id`, `benchmark_version`,
+`recipe_fingerprint`, `hardware_profile_id`, and `software_profile_id`. PR and
+local records are visible in the dashboard but are not baseline eligible.
 
 ## Planned Coverage
 
@@ -158,13 +159,16 @@ unrealistic memory growth, and optionally large component-specific slowdowns
 even when the rolling baseline is empty. They are hand-set with generous
 headroom and almost never need touching.
 
-### Rolling baseline (per `(model_id, gpu_type)`)
+### Rolling baseline (per comparison cohort)
 
 `compare_baseline.py` loads the last 5 successful, baseline-eligible records
-for the same `(model_id, gpu_type)` from the HF dataset, computes the median
-for each available metric, and evaluates the current run with the metric's
-rolling regression policy. For latency, memory, and component times, higher
-values are regressions. For throughput, lower values are regressions.
+for the same comparison cohort from the HF dataset, computes the median for
+each available metric, and evaluates the current run with the metric's
+rolling regression policy. For v2 records, that cohort is `model_id`,
+`gpu_type`, `workload_id`, `variant_id`, `benchmark_version`,
+`recipe_fingerprint`, `hardware_profile_id`, and `software_profile_id`. For
+latency, memory, and component times, higher values are regressions. For
+throughput, lower values are regressions.
 
 A metric exceeds its rolling threshold when both of these are true:
 
@@ -424,7 +428,7 @@ When the rolling-baseline phase runs, it emits:
   per-benchmark row with current vs. baseline values for latency, throughput,
   memory, text encoder time, DiT time, and VAE decode time.
 * **Plotly dashboard** — `dashboard_<sha>_<ts>.html` showing time-series for
-  each metric grouped by `(model_id, gpu_type)`.
+  each metric grouped by comparison cohort.
 * **Normalized records** — `normalized_perf_*.json`, one per benchmark.
   Useful as input to the
   [`reseed-performance-baseline`](https://github.com/hao-ai-lab/FastVideo/blob/main/.agents/skills/reseed-performance-baseline/SKILL.md)
@@ -498,8 +502,8 @@ When the rolling-baseline phase runs, it emits:
 
 ## Troubleshooting
 
-**"No baseline for ... Initializing"** — first run for this `(model_id,
-gpu_type)`. Run will pass and (if persisting) seed the first record.
+**"No baseline for ... Initializing"** — first run for this comparison cohort.
+Run will pass and (if persisting) seed the first record.
 
 **Persistent failure right after a torch / kernel / image upgrade** —
 genuine regression *or* baseline drift. Compare the failing normalized record
diff --git a/fastvideo/performance_dashboard/service.py b/fastvideo/performance_dashboard/service.py
index fb070d277..8b6ef7cbf 100644
--- a/fastvideo/performance_dashboard/service.py
+++ b/fastvideo/performance_dashboard/service.py
@@ -86,20 +86,32 @@ def record_metadata(record: Record) -> Record:
     }
 
 
+def _cohort_metadata_value(value: Any) -> Any:
+    if value is None:
+        return ""
+    if isinstance(value, str) and not value.strip():
+        return ""
+    return value
+
+
+def _cohort_key_value(value: Any) -> str:
+    return str(_cohort_metadata_value(value))
+
+
 def record_comparison_metadata(record: Record) -> Record:
-    return {key: record.get(key) or "" for key in COMPARISON_COHORT_KEYS}
+    return {key: _cohort_metadata_value(record.get(key)) for key in COMPARISON_COHORT_KEYS}
 
 
 def comparison_cohort_key(record: Record) -> CohortKey:
     return (
         str(record.get("model_id") or "unknown"),
         str(record.get("gpu_type") or "unknown"),
-        str(record.get("workload_id") or ""),
-        str(record.get("variant_id") or ""),
-        str(record.get("benchmark_version") or ""),
-        str(record.get("recipe_fingerprint") or ""),
-        str(record.get("hardware_profile_id") or ""),
-        str(record.get("software_profile_id") or ""),
+        _cohort_key_value(record.get("workload_id")),
+        _cohort_key_value(record.get("variant_id")),
+        _cohort_key_value(record.get("benchmark_version")),
+        _cohort_key_value(record.get("recipe_fingerprint")),
+        _cohort_key_value(record.get("hardware_profile_id")),
+        _cohort_key_value(record.get("software_profile_id")),
     )
 
 
@@ -146,9 +158,10 @@ def build_latest_summary(records: list[Record],
             continue
 
         latest = latest_candidates[-1]
+        latest_index = next(index for index, record in enumerate(group) if record is latest)
         baseline_pool = [
-            record for record in group
-            if record is not latest and record.get("success", True) and is_baseline_eligible_record(record)
+            record for record in group[:latest_index]
+            if record.get("success", True) and is_baseline_eligible_record(record)
         ]
         baseline_records = baseline_pool[-baseline_window:]
         metric_policies = resolve_metric_policies(latest.get("regression_thresholds"))
diff --git a/fastvideo/tests/performance/test_dashboard_api.py b/fastvideo/tests/performance/test_dashboard_api.py
index 41a25bccf..d585b0b7e 100644
--- a/fastvideo/tests/performance/test_dashboard_api.py
+++ b/fastvideo/tests/performance/test_dashboard_api.py
@@ -154,8 +154,8 @@ def test_dashboard_endpoints_filter_and_return_run_source_metadata():
     assert summary["count"] == 1
     assert summary["rows"][0]["run_source"] == "pr"
     assert summary["rows"][0]["pr_number"] == "123"
-    assert summary["rows"][0]["baseline_n"] == 1
-    assert summary["rows"][0]["metrics"]["latency"]["baseline"] == 11.0
+    assert summary["rows"][0]["baseline_n"] == 0
+    assert summary["rows"][0]["metrics"]["latency"]["baseline"] is None
     assert summary["filters"]["run_source"] == "pr"
     assert trends["count"] == 1
     assert trends["groups"][0]["points"][0]["run_source"] == "pr"
diff --git a/fastvideo/tests/performance/test_dashboard_service.py b/fastvideo/tests/performance/test_dashboard_service.py
index 8fa3dfbcd..6ac52ff9b 100644
--- a/fastvideo/tests/performance/test_dashboard_service.py
+++ b/fastvideo/tests/performance/test_dashboard_service.py
@@ -142,6 +142,47 @@ def test_build_latest_summary_separates_informational_threshold_crossing():
     assert rows[0]["threshold_exceeded_metrics"] == ["latency"]
     assert rows[0]["failing_metrics"] == []
     assert rows[0]["computed_regression_status"] == "pass"
+
+
+def test_build_latest_summary_run_source_filter_excludes_future_baselines():
+    records = [
+        _record(
+            "2026-01-01T00:00:00+00:00",
+            "a" * 40,
+            10.0,
+            10.0,
+            run_source="scheduled_main",
+            baseline_eligible=True,
+        ),
+        _record(
+            "2026-01-02T00:00:00+00:00",
+            "b" * 40,
+            11.0,
+            9.0,
+            run_source="pr",
+            baseline_eligible=False,
+            pr_number="123",
+        ),
+        _record(
+            "2026-01-03T00:00:00+00:00",
+            "c" * 40,
+            30.0,
+            3.0,
+            run_source="scheduled_main",
+            baseline_eligible=True,
+        ),
+    ]
+
+    rows = build_latest_summary(records, run_source="pr")
+
+    assert len(rows) == 1
+    assert rows[0]["run_source"] == "pr"
+    assert rows[0]["baseline_n"] == 1
+    assert rows[0]["metrics"]["latency"]["baseline"] == 10.0
+    assert rows[0]["metrics"]["throughput"]["baseline"] == 10.0
+
+
+
 def test_build_latest_summary_keeps_identity_cohorts_separate():
     records = [
         _record(
@@ -186,7 +227,7 @@ def test_build_latest_summary_keeps_identity_cohorts_separate():
         ),
     ]
 
-    rows = build_latest_summary(records, max_regression=0.05)
+    rows = build_latest_summary(records)
     recipe_b_row = next(row for row in rows if row["recipe_fingerprint"] == "recipe-b")
 
     assert len(rows) == 2
@@ -241,7 +282,7 @@ def test_build_latest_summary_keeps_variant_versions_separate():
         ),
     ]
 
-    rows = build_latest_summary(records, max_regression=0.05)
+    rows = build_latest_summary(records)
     version_2_row = next(row for row in rows if row["benchmark_version"] == 2)
 
     assert len(rows) == 2
@@ -249,6 +290,58 @@ def test_build_latest_summary_keeps_variant_versions_separate():
     assert version_2_row["metrics"]["latency"]["baseline"] == 20.0
 
 
+def test_dashboard_identity_preserves_zero_benchmark_version():
+    records = [
+        _record(
+            "2026-01-01T00:00:00+00:00",
+            "a" * 40,
+            10.0,
+            10.0,
+            workload_id="wan-t2v",
+            variant_id="1.3b-sp2",
+            benchmark_version=0,
+            recipe_fingerprint="recipe-a",
+            hardware_profile_id="hw-l40s",
+            software_profile_id="sw-cu130",
+            run_source="scheduled_main",
+            baseline_eligible=True,
+        ),
+        _record(
+            "2026-01-02T00:00:00+00:00",
+            "b" * 40,
+            11.0,
+            9.0,
+            workload_id="wan-t2v",
+            variant_id="1.3b-sp2",
+            benchmark_version=0,
+            recipe_fingerprint="recipe-a",
+            hardware_profile_id="hw-l40s",
+            software_profile_id="sw-cu130",
+        ),
+        _record(
+            "2026-01-03T00:00:00+00:00",
+            "c" * 40,
+            20.0,
+            5.0,
+        ),
+    ]
+
+    rows = build_latest_summary(records)
+    version_zero_row = next(row for row in rows if row["benchmark_version"] == 0)
+    legacy_row = next(row for row in rows if row["benchmark_version"] == "")
+    trends = build_trends(records)
+    version_zero_trend = next(trend for trend in trends if trend["benchmark_version"] == 0)
+    legacy_trend = next(trend for trend in trends if trend["benchmark_version"] == "")
+
+    assert len(rows) == 2
+    assert version_zero_row["baseline_n"] == 1
+    assert version_zero_row["metrics"]["latency"]["baseline"] == 10.0
+    assert legacy_row["baseline_n"] == 0
+    assert len(trends) == 2
+    assert version_zero_trend["points"][0]["benchmark_version"] == 0
+    assert legacy_trend["points"][0]["benchmark_version"] == ""
+
+
 def test_filter_records_and_trends_preserve_metric_points():
     records = [
         _record("2026-01-01T00:00:00+00:00", "a" * 40, 10.0, 10.0),