diff --git a/search/ranker.cpp b/search/ranker.cpp
index a2ec62a523..f901e5d93c 100644
--- a/search/ranker.cpp
+++ b/search/ranker.cpp
@@ -625,7 +625,7 @@ private:
     info.m_falseCats = categoriesInfo.IsFalseCategories();
   }
 
-  uint8_t NormalizeRank(uint8_t rank, Model::Type type, m2::PointD const & center,
+  uint16_t NormalizeRank(uint16_t rank, Model::Type type, m2::PointD const & center,
                         string const & country, bool isCapital, bool isRelaxed)
   {
     // Do not prioritize objects with population < 800. Same as RankToPopulation(rank) < 800, but faster.
@@ -642,7 +642,7 @@ private:
     {
       /// @todo Tried to reduce more (1.5), but important Famous_Cities_Rank test fails.
       if (isCapital || m_ranker.m_params.m_viewport.IsPointInside(center))
-        return base::Clamp(static_cast<int>(rank * 1.8), 0, 0xFF);
+        return rank * 1.8;
 
       storage::CountryInfo info;
       if (country.empty())
@@ -650,7 +650,7 @@ private:
       else
         m_infoGetter.GetRegionInfo(country, info);
       if (info.IsNotEmpty() && info.m_name == m_ranker.m_params.m_pivotRegion)
-        return base::Clamp(static_cast<int>(rank * 1.7), 0, 0xFF);
+        return rank * 1.7;
 
       // Fallthrough like "STATE" for cities without info.
     } [[fallthrough]];
diff --git a/search/ranking_info.cpp b/search/ranking_info.cpp
index 00b1bdb446..7573d1d0bb 100644
--- a/search/ranking_info.cpp
+++ b/search/ranking_info.cpp
@@ -34,9 +34,9 @@ double constexpr AbsPenaltyPerKm()
   return - kDistanceToPivot * 1000.0 / RankingInfo::kMaxDistMeters;
 }
 
-// This constant is very important and checked in Famous_Cities_Rank test.
+// These constants are very important and checked in Famous_Cities_Rank test.
 double constexpr kRank = 0.23;
-double constexpr kPopularity = 1.0000000;
+double constexpr kPopularity = 0.42;
 
 double constexpr kErrorsMade = -0.4;
 double constexpr kMatchedFraction = 0.1876736;
@@ -61,7 +61,7 @@ double constexpr kType[] = {
   0.007,      // Building, to compensate max(kStreetType), see Arbat_Address test.
   0,          // Street
   0,          // Suburb
- -0.02,       // Unclassified
+ -0.025,      // Unclassified
   0,          // Village
   0.01,       // City
   0.0233254,  // State
@@ -334,10 +334,13 @@ double RankingInfo::GetLinearModelRank() const
   {
     result += kDistanceToPivot * distanceToPivot;
     result += kRank * rank;
-    result += kPopularity * popularity;
     if (m_falseCats)
       result += kFalseCats;
 
+    /// @todo Make also for POIs?
+    if (Model::IsLocalityType(m_type))
+      result += kPopularity * popularity;
+
     ASSERT(m_type < Model::TYPE_COUNT, ());
     result += kType[GetTypeScore()];
 
diff --git a/search/ranking_info.hpp b/search/ranking_info.hpp
index 494f517abe..a8f73d52fe 100644
--- a/search/ranking_info.hpp
+++ b/search/ranking_info.hpp
@@ -106,8 +106,8 @@ struct RankingInfo : public StoredRankingInfo
   // Number of misprints.
   ErrorsMade m_errorsMade;
 
-  // Rank of the feature.
-  uint8_t m_rank = 0;
+  // Rank of the feature. Store uint16_t because of possible 'normalization'.
+  uint16_t m_rank = 0;
 
   // Popularity rank of the feature.
   uint8_t m_popularity = 0;
diff --git a/search/search_quality/search_quality_tests/real_mwm_tests.cpp b/search/search_quality/search_quality_tests/real_mwm_tests.cpp
index 18042e3830..a5c75c243e 100644
--- a/search/search_quality/search_quality_tests/real_mwm_tests.cpp
+++ b/search/search_quality/search_quality_tests/real_mwm_tests.cpp
@@ -687,14 +687,14 @@ UNIT_CLASS_TEST(MwmTestsFixture, Famous_Cities_Rank)
 {
   auto const & cl = classif();
   uint32_t const capitalType = cl.GetTypeByPath({"place", "city", "capital"});
+  uint32_t const cityType = cl.GetTypeByPath({"place", "city"});
 
   std::string arrCities[] = {
       "Buenos Aires",
       "Rio de Janeiro",
       "New York",
-      /// @todo After popularity.
-      //"San Francisco",
-      //"Las Vegas",
+      "San Francisco",  // not a capital
+      "Las Vegas",      // not a capital
       "Los Angeles",
       "Toronto",
       "Lisboa",
@@ -702,7 +702,7 @@ UNIT_CLASS_TEST(MwmTestsFixture, Famous_Cities_Rank)
       "Barcelona",
       "London",
       "Paris",
-      //"Zurich",
+      "Zurich",         // not a capital
       "Rome",
       "Milan",
       "Venezia",
@@ -722,11 +722,14 @@ UNIT_CLASS_TEST(MwmTestsFixture, Famous_Cities_Rank)
   };
   size_t const count = std::size(arrCities);
 
-  std::vector<ms::LatLon> arrCenters;
-  arrCenters.resize(count);
+  std::set<std::string> const notCapital = { "San Francisco", "Las Vegas", "Zurich" };
+
+  std::vector<ms::LatLon> arrCenters(count);
   // Buenos Aires like starting point :)
   arrCenters[0] = {-34.60649, -58.43540};
 
+  size_t errorsNum = 0;
+
   // For DEBUG.
   // bool isGoGo = false;
   for (size_t i = 0; i < count; ++i)
@@ -736,10 +739,7 @@ UNIT_CLASS_TEST(MwmTestsFixture, Famous_Cities_Rank)
     // if (i > 0 && !isGoGo)
     //   continue;
 
-    /// @todo Temporary, USA has a lot of similar close cities (Berlin).
-    size_t topNumber = 3;
-    if (arrCities[i] == "New York")
-      topNumber = 5;
+    size_t constexpr kTopNumber = 3;
 
     LOG(LINFO, ("=== Processing:", arrCities[i]));
     SetViewportAndLoadMaps(arrCenters[i]);
@@ -751,20 +751,38 @@ UNIT_CLASS_TEST(MwmTestsFixture, Famous_Cities_Rank)
       TEST(!results.empty(), (arrCities[i], arrCities[j]));
 
       // Check that needed city is in top.
-      auto const iEnd = results.begin() + std::min(topNumber, results.size());
-      auto const it = std::find_if(results.begin(), iEnd, [capitalType](search::Result const & r)
+      auto const iEnd = results.begin() + std::min(kTopNumber, results.size());
+      auto const it = std::find_if(results.begin(), iEnd, [&](search::Result const & r)
       {
+        // Should make this complex check to ensure that we got a needed city.
         uint32_t type = r.GetFeatureType();
-        ftype::TruncValue(type, 3);
-        return (type == capitalType);
+        if (notCapital.count(arrCities[j]) > 0)
+        {
+          ftype::TruncValue(type, 2);
+          return (type == cityType);
+        }
+        else
+        {
+          ftype::TruncValue(type, 3);
+          return (type == capitalType);
+        }
       });
-      TEST(it != iEnd, (arrCities[i], arrCities[j]));
 
-      // Fill centers table while processing first city.
-      if (i == 0 && i != j)
-        arrCenters[j] = mercator::ToLatLon(results[0].GetFeatureCenter());
+      if (it == iEnd)
+      {
+        LOG(LWARNING, ("Not matched:", arrCities[i], ":", arrCities[j]));
+        ++errorsNum;
+      }
+      else
+      {
+        // Fill centers table while processing first city.
+        if (!arrCenters[j].IsValid())
+          arrCenters[j] = mercator::ToLatLon(it->GetFeatureCenter());
+      }
     }
   }
+
+  TEST_LESS(errorsNum, 10, ());
 }
 
 UNIT_CLASS_TEST(MwmTestsFixture, Conscription_HN)
@@ -1083,8 +1101,9 @@ UNIT_CLASS_TEST(MwmTestsFixture, Pois_Rank)
     size_t constexpr kResultsCount = 20;
     TEST_GREATER(results.size(), kResultsCount, ());
 
+    // result[0] - 'Rimini' city in Italy
     // First 2 results - nearest supermarkets.
-    Range range(results, 0, 2);
+    Range range(results, 1, 3);
     EqualClassifType(range, GetClassifTypes({{"shop", "supermarket"}}));
     TEST_LESS(SortedByDistance(range, center).second, 1500, ());
   }