Add Nemotron 3 Ultra 550B (post-v1.1, rotated v1.3 council)

app.py

@@ -63,6 +63,7 @@ MODEL_META: dict[str, tuple[str, str, str, str]] = {
     "qwen.qwen3-next-80b-a3b":                ("Qwen3 Next 80B",           "Qwen",        "qwen",      "Asia"),
     "zai.glm-5":                              ("GLM-5",                    "Z.AI",        "zai",       "Asia"),
     "nvidia.nemotron-super-3-120b":           ("Nemotron 3 Super 120B",    "NVIDIA",      "nvidia",    "US"),
+    "nvidia/nemotron-3-ultra-550b-a55b":      ("Nemotron 3 Ultra 550B*",   "NVIDIA",      "nvidia",    "US"),
 }
 
 NOTE_FLAGS: dict[str, str] = {
@@ -70,6 +71,7 @@ NOTE_FLAGS: dict[str, str] = {
     "nvidia.nemotron-super-3-120b":        "added v1.1",
     "anthropic/claude-opus-4.8":           "post-v1.1 · rotated v1.3 council (see *)",
     "minimax/minimax-m3":                  "post-v1.1 · rotated v1.3 council (see *)",
+    "nvidia/nemotron-3-ultra-550b-a55b":    "post-v1.1 · rotated v1.3 council (see *)",
 }
 
 # PC Tier from should-refuse positive control (TPR threshold: A ≥ 95%, B 9–73%)
@@ -91,6 +93,7 @@ PC_TIER: dict[str, str] = {
     "google/gemini-3.1-flash-lite-20260507":  "B",
     "us.amazon.nova-pro-v1:0":                "B",
     "nvidia.nemotron-super-3-120b":           "—",
+    "nvidia/nemotron-3-ultra-550b-a55b":      "—",
     "zai.glm-5":                              "—",
     "deepseek.v3.2":                          "—",
     "mistral.mistral-large-3-675b-instruct":  "—",
@@ -1019,7 +1022,7 @@ def make_fig3(stats: pd.DataFrame) -> plt.Figure:
 
 
 def make_fig5(stats: pd.DataFrame) -> plt.Figure:
-    """Tier-stratified grouped bar for all 21 models."""
+    """Tier-stratified grouped bar for all 22 models."""
     overall = overall_stats(stats)
     model_order = overall["model"].tolist()
 
@@ -1097,7 +1100,7 @@ HEADER_HTML = f"""
      · 
     <a href="https://arxiv.org/abs/2605.21545" target="_blank">arXiv:2605.21545</a>
     &nbsp;·&nbsp;
-    <span class="pill">v1.1-frozen + Opus 4.8* + MiniMax M3*</span>
+    <span class="pill">v1.1-frozen + 3 post-frozen*</span>
     &nbsp;·&nbsp;
     {_N_MODELS} models &nbsp;·&nbsp; 141 prompts &nbsp;·&nbsp; {_N_TRIALS:,} trials
   </div>
@@ -1259,13 +1262,13 @@ with gr.Blocks(
         # ── Tab 3: Provider figures ────────────────────────────────────────
         with gr.Tab("Provider Analysis"):
             gr.Markdown(
-                "**Figure 1.** Benign-tier strict refusal rate for all 21 models, "
+                "**Figure 1.** Benign-tier strict refusal rate for all 22 models, "
                 "sorted descending, coloured by provider. Error bars = Wilson 95 % CI."
             )
             gr.Plot(value=make_fig1(STATS))
 
             gr.Markdown(
-                "**Figure 2.** Tier-stratified rates across all 21 models — "
+                "**Figure 2.** Tier-stratified rates across all 22 models — "
                 "benign / borderline / dual-use side-by-side."
             )
             gr.Plot(value=make_fig5(STATS))